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    "textoCompleto" => "<span class="elsevierStyleSections"><span id="sec0001" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0007">Introduction</span><p id="para0005" class="elsevierStylePara elsevierViewall">Pneumonia is one of the leading causes of death in children under the age of five all around the world&#46;<a class="elsevierStyleCrossRef" href="#bib0001"><span class="elsevierStyleSup">1</span></a><span class="elsevierStyleSup">&#44;</span><a class="elsevierStyleCrossRef" href="#bib0002"><span class="elsevierStyleSup">2</span></a> According to statistics&#44; pneumonia caused more than 800&#44;000 childhood deaths in 2017&#44; which accounts for 15&#37; of all deaths of under-five children that year&#46;<a class="elsevierStyleCrossRef" href="#bib0002"><span class="elsevierStyleSup">2</span></a> In China&#44; the prevalence of childhood pneumonia is also very high&#46;<a class="elsevierStyleCrossRef" href="#bib0003"><span class="elsevierStyleSup">3</span></a> The disease not only seriously affects the children&#39;s health&#44; but also significantly increases the financial burden on their families and the psychological burden on their guardians&#46;<a class="elsevierStyleCrossRef" href="#bib0004"><span class="elsevierStyleSup">4</span></a> Although doctors have made great efforts to treat pneumonia and reduce mortality&#44; the results have not been satisfactory&#46;<a class="elsevierStyleCrossRef" href="#bib0005"><span class="elsevierStyleSup">5</span></a> One very important reason for this is that a great number of factors may influence the susceptibility and prognosis of pneumonia&#44; such as socioeconomic status&#44; malnutrition&#44; and so on&#46;<a class="elsevierStyleCrossRef" href="#bib0002"><span class="elsevierStyleSup">2</span></a></p><p id="para0006" class="elsevierStylePara elsevierViewall">Currently&#44; obesity has gradually become a new global health problem in children under the age of five&#46;<a class="elsevierStyleCrossRef" href="#bib0006"><span class="elsevierStyleSup">6</span></a> One published study reported a prognostic significance of obesity and overweight on pneumonia in this group of children&#46;<a class="elsevierStyleCrossRef" href="#bib0007"><span class="elsevierStyleSup">7</span></a> Then&#44; whether lipid metabolism was also related to childhood pneumonia attracted the attention of researchers&#46; But a series of related studies failed to provide consistent results&#46; Some studies believed that the increased levels of some lipid metabolic markers such as triglycerides may worsen the prognosis of childhood pneumonia&#46;<a class="elsevierStyleCrossRef" href="#bib0008"><span class="elsevierStyleSup">8</span></a> Others suggested that cholesterol metabolism and the elevated levels of several apolipoproteins may have a protective effect on the disease&#46;<a class="elsevierStyleCrossRef" href="#bib0009"><span class="elsevierStyleSup">9</span></a><span class="elsevierStyleSup">&#44;</span><a class="elsevierStyleCrossRef" href="#bib0010"><span class="elsevierStyleSup">10</span></a> So&#44; a firmed conclusion has not been drawn until then&#46;</p><p id="para0007" class="elsevierStylePara elsevierViewall">Therefore&#44; the present study enrolled 3000 children under the age of five in China to reveal the association of several lipids&#44; lipoproteins&#44; and apolipoproteins with the risk of childhood pneumonia&#44; and to further explore the association of these lipid metabolic markers with the risk of hypoxemia induced by pneumonia and the levels of C-reactive protein &#40;CRP&#41; in serums&#46; The results obtained from the study may help people to determine whether lipid metabolism may be a potential effective factor in childhood pneumonia&#46;</p></span><span id="sec0002" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0008">Materials and methods</span><span id="sec0003" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0009">Ethics statement</span><p id="para0008" class="elsevierStylePara elsevierViewall">The study was approved by the ethics committee of Henan provincial people&#39;s hospital and was performed in accordance with the Declaration of Helsinki &#40;Supplemental Fig&#46; 1&#41;&#46; The guardians of the included children agreed to participate in the study and signed the written consents&#46;</p></span><span id="sec0004" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0010">Data source</span><p id="para0009" class="elsevierStylePara elsevierViewall">The data of the study were collected from the medical records of Henan provincial people&#39;s hospital&#46; Briefly&#44; all patients admitted to the hospital were told that their medical records might be used anonymously for scientific research&#46; If the patients or their families agreed&#44; the written informed consent forms would be signed&#46; After the patients were discharged from the hospital&#44; their medical records would be included in the scientific research database&#46;</p></span><span id="sec0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0011">Subjects</span><p id="para0010" class="elsevierStylePara elsevierViewall">A total of 1000 children with common pneumonia&#44; and 1000 children with severe pneumonia were randomly included from the database&#44; and all of them were admitted to the hospital between January 2010 and December 2020 due to pneumonia&#46; Their age was limited to 18 to 60 months&#46;</p><p id="para0011" class="elsevierStylePara elsevierViewall">Pneumonia was diagnosed and classified using the criteria of the World Health Organization &#40;WHO&#41;&#44; which included&#58; a history of cough or difficulty breathing&#44; and if present&#44; respiratory rate &#62; 50 breaths&#47;minute &#40;age &#60; 12 months&#41; or &#62; 40 breaths&#47;minute &#40;age &#8805; 12 months&#41;&#46;<a class="elsevierStyleCrossRef" href="#bib0011"><span class="elsevierStyleSup">11</span></a> Severe pneumonia indicated that the disease met the above diagnostic criteria and was accompanied by at least one of the danger signs&#44; which included &#40;1&#41; nasal flaring&#44; &#40;2&#41; subcostal retractions&#44; &#40;3&#41; convulsions&#44; &#40;4&#41; Blantyre coma scale &#60; 5&#44; &#40;5&#41; &#8220;alert&#44; voice&#44; pain&#44; unresponsive&#8221; scale less than &#8220;alert&#8221; and &#40;6&#41; inability to drink or feed&#46; Common pneumonia was defined as meeting the above diagnostic criteria without the danger signs&#46; Children with tuberculosis infection&#44; congenital lung diseases&#44; dysplasia disorders and other serious diseases were excluded&#46; All the children with pneumonia were treated according to the protocolized guidelines for the diagnosis and treatment of pneumonia in China and the world&#46;<a class="elsevierStyleCrossRef" href="#bib0011"><span class="elsevierStyleSup">11</span></a></p><p id="para0012" class="elsevierStylePara elsevierViewall">Other 1000 healthy children were randomly included from the database&#44; and all of them came to the hospital for consultation at the same period&#44; but no obvious disease was detected&#46; They served as controls&#46; Their ages ranged from 18 to 60 months&#46;</p></span><span id="sec0006" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0012">Data collection and definition</span><p id="para0013" class="elsevierStylePara elsevierViewall">Research data were obtained from the database using predefined questionnaires&#46; For the children with pneumonia&#44; age&#44; gender&#44; ethnic group&#44; height&#44; weight&#44; household income&#44; clinical manifestations &#40;i&#46;e&#46;&#44; hyperpyrexia&#44; dehydration&#44; diarrhea and hypoxemia&#41;&#44; serological data &#40;i&#46;e&#46;&#44; serum white blood cell &#40;WBC&#41; count&#44; creatinine level and CRP&#41; and use of antibiotics were collected&#46; For the controls&#44; age&#44; gender&#44; ethnic group&#44; height&#44; weight and household income were collected&#46;</p><p id="para0014" class="elsevierStylePara elsevierViewall">Hyperpyrexia was a body temperature greater than 39&#176;C&#46; Hypoxaemia was defined as SpO<span class="elsevierStyleInf">2</span> &#60; 90&#37;&#46; High creatinine referred to plasma creatinine levels greater than 35&#160;mmol&#47;l in infants and greater than 62&#160;mmol&#47;l in children&#46;</p><p id="para0015" class="elsevierStylePara elsevierViewall">Generally&#44; obesity is assessed using the body mass index &#40;BMI&#41;&#44; which is calculated based on weight and height&#46; However&#44; children under 60 months of age are in a rapid growth and development phase&#46; To increase the comparability&#44; BMI Z-scores were calculated in the study to standardize the data&#44; and its formula was &#40;BMI - mean of BMI&#41; &#47; &#40;standard deviation of BMI&#41;&#46;<a class="elsevierStyleCrossRef" href="#bib0012"><span class="elsevierStyleSup">12</span></a> The mean and standard deviation of BMI for the local population were obtained from the local Center for Disease Control and Prevention&#46; A BMIZ score greater than 2&#46;00 was considered overweight&#44; a score greater than 3&#46;00 was diagnosed as obesity&#44; and the score between &#8722;2&#46;00 and 2&#46;00 was defined as normal&#46;<a class="elsevierStyleCrossRef" href="#bib0012"><span class="elsevierStyleSup">12</span></a></p></span><span id="sec0007" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0013">Lipid metabolism</span><p id="para0016" class="elsevierStylePara elsevierViewall">The serum levels of several lipids&#44; lipoproteins and apolipoproteins were adopted to reflect lipid metabolism&#46; The lipid metabolic markers included triglycerides &#40;TG&#41;&#44; total cholesterol &#40;TC&#41;&#44; low-density lipoprotein cholesterol &#40;LDL-C&#41;&#44; very low-density lipoprotein cholesterol &#40;VLDL-C&#41;&#44; high-density lipoprotein cholesterol &#40;HDL-C&#41;&#44; apolipoprotein A1 &#40;ApoA1&#41;&#44; apolipoprotein B &#40;ApoB&#41; and lipoprotein A &#40;Lp-a&#41;&#46;</p><p id="para0017" class="elsevierStylePara elsevierViewall">These data were also collected from the database&#44; and the blood specimen collection and testing process was briefly described below&#46; When each child presented to the hospital&#44; his or her fasting venous blood was routinely collected to measure a range of serological markers &#40;such as blood lipids&#41; in order to guide the diagnosis and treatment&#46; The blood sample was immediately sent to the laboratory center of the hospital&#46; After centrifugation and extraction&#44; the serum sample was used to measure the levels of these lipid metabolic markers mentioned above&#46; Serum levels of TG&#44; TC&#44; LDL-C&#44; VLDL-C and HDL-C were detected using an ADVIA-1650 Chemistry System &#40;Bayer Co&#46;&#44; USA&#41;&#46; Serum levels of ApoA1&#44; ApoB and Lp-a were determined by several latex-particle-enhanced immunonephelometric assays on a BN ProSpec nephelometer &#40;Dade Behring Co&#46;&#44; Germany&#41;&#46; Each serological marker was measured twice&#44; and their average value was recorded in the database&#46;</p></span><span id="sec0008" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0014">Statistical analysis</span><p id="para0018" class="elsevierStylePara elsevierViewall">According to the Shapiro-Wilk test&#44; all continuous variables in this study did not follow a normal distribution&#46; Therefore&#44; these variables were expressed by medians &#40;25th quartiles&#44; 75th quartiles&#41;&#44; while the differences between groups were compared by Kruskal-Wallis H test&#46; Categorical variables were expressed by frequencies&#44; and the difference of the two categorical variables was measured using the Chi-square test&#46; If there were three categorical variables to be compared at the same time&#44; the maximum and minimum values were compared&#46; The linear association of two continuous variables was determined using spearman correlation analysis&#46; A P-value less than 0&#46;05 was considered statistically significant&#46; The Association of the lipids&#44; lipoproteins and apolipoproteins with the risk of childhood pneumonia and hypoxemia was determined using univariate and multivariate logistic regression&#46; The odds ratios &#40;ORs&#41; and 95&#37; confidence intervals &#40;CIs&#41; were reported&#46; In the multivariate analyses&#44; demography data&#44; clinical manifestations&#44; serological data and use of antibiotics were adjusted&#46; If a 95&#37;CI did not include value one&#44; it was considered statistically significant&#46; All analyses were conducted using SPSS 23&#46;0 &#40;USA&#41;&#46;</p></span></span><span id="sec0009" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0015">Results</span><span id="sec0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0016">Characteristics of the subjects in the study</span><p id="para0019" class="elsevierStylePara elsevierViewall">As shown in <a class="elsevierStyleCrossRef" href="#tbl0001">Table 1</a>&#44; compared with the common case group&#44; the children in the severe case group had more opportunities to suffer from hyperpyrexia&#44; dehydration&#44; diarrhea&#44; hypoxemia&#44; high creatinine&#44; high CRP &#40;<span class="elsevierStyleItalic">P&#160;&#60;</span>&#160;0&#46;001&#44; <span class="elsevierStyleItalic">P&#160;&#60;</span>&#160;0&#46;001&#44; <span class="elsevierStyleItalic">P&#160;&#60;</span>&#160;0&#46;001&#44; <span class="elsevierStyleItalic">P&#160;&#60;</span>&#160;0&#46;001&#44; <span class="elsevierStyleItalic">P&#160;&#60;</span>&#160;0&#46;001&#44; <span class="elsevierStyleItalic">P&#160;&#60;</span>&#160;0&#46;001&#41;&#44; to receive the cephalosporins treatment &#40;<span class="elsevierStyleItalic">P&#160;&#60;</span>&#160;0&#46;001&#41; and to change the antibiotics &#40;<span class="elsevierStyleItalic">P&#160;&#60;</span>&#160;0&#46;001&#41;&#46; Compared with the severe case group&#44; the children in the common case group had more possibilities to receive the macrolides treatment &#40;<span class="elsevierStyleItalic">P&#160;&#60;</span>&#160; 0&#46;001&#41;&#46; In addition&#44; there was no difference in WBC count between the common case and severe case groups &#40;<span class="elsevierStyleItalic">P</span>&#160;&#61;&#160;0&#46;106&#41;&#46; There was no difference in age&#44; gender&#44; and nationality&#44; BMI Z-score&#44; and household income among all the three groups &#40;<span class="elsevierStyleItalic">P</span>&#160;&#61;&#160;0&#46;826&#44; <span class="elsevierStyleItalic">P</span>&#160;&#61;&#160;0&#46;267&#44; <span class="elsevierStyleItalic">P</span>&#160;&#61;&#160;0&#46;214&#44; <span class="elsevierStyleItalic">P</span>&#160;&#61;&#160;0&#46;080&#44; <span class="elsevierStyleItalic">P</span>&#160;&#61;&#160;0&#46;199&#41;&#46; Among them&#44; household income indicated average monthly income per capita&#46;</p><elsevierMultimedia ident="tbl0001"></elsevierMultimedia><p id="para0020" class="elsevierStylePara elsevierViewall">As shown in <a class="elsevierStyleCrossRef" href="#tbl0002">Table 2</a>&#44; with the exception of Lp-a &#40;<span class="elsevierStyleItalic">P</span>&#160;&#61;&#160;0&#46;433&#41;&#44; the serum levels of the other lipid metabolic markers differed significantly in the control&#44; common case&#44; and severe case groups &#40;<span class="elsevierStyleItalic">P&#160;&#60;</span>&#160;0&#46;001&#44; <span class="elsevierStyleItalic">P&#160;&#60;</span>&#160; 0&#46;001&#44; <span class="elsevierStyleItalic">P&#160;&#60;</span>&#160;0&#46;001&#44; <span class="elsevierStyleItalic">P&#160;&#60;</span>&#160;0&#46;001&#44; <span class="elsevierStyleItalic">P&#160;&#60;</span>&#160;0&#46;001&#44; <span class="elsevierStyleItalic">P&#160;&#60;</span>&#160;0&#46;001&#44; <span class="elsevierStyleItalic">P</span>&#160;&#61;&#160;0&#46;014&#41;&#46; Briefly&#44; compared with the common case group&#44; the serum levels of TG&#44; TC&#44; LDL-C&#44; and VLDL-C were significantly higher and the serum levels of HDL-C and ApoA1 were significantly lower in the severe case group &#40;<span class="elsevierStyleItalic">P&#160;&#60;</span>&#160;0&#46;05&#41;&#46; Compared with the control group&#44; the serum level of TC was significantly higher in the common case group &#40;<span class="elsevierStyleItalic">P&#160;&#60;</span>&#160;0&#46;05&#41;&#46;</p><elsevierMultimedia ident="tbl0002"></elsevierMultimedia></span><span id="sec0011" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0017">Association of the lipid metabolic markers with the risk of pneumonia</span><p id="para0021" class="elsevierStylePara elsevierViewall">As shown in <a class="elsevierStyleCrossRef" href="#tbl0003">Table 3</a>&#44; the higher level of TC in serum was associated with the increased risk of common pneumonia &#40;OR&#160;&#61;&#160;1&#46;110&#44; 95&#37;CI&#160;&#61;&#160;1&#46;014 &#8764; 1&#46;214&#41;&#46; In addition&#44; the other lipid metabolic markers were not related to the risk of the disease &#40;<a class="elsevierStyleCrossRef" href="#tbl0003">Table 3</a>&#41;&#46;</p><elsevierMultimedia ident="tbl0003"></elsevierMultimedia><p id="para0022" class="elsevierStylePara elsevierViewall">Besides&#44; the higher levels of TG&#44; TC&#44; LDL-C&#44; VLDL-C and ApoB were associated with the elevated risk of severe pneumonia &#40;OR&#160;&#61;&#160;1&#46;407&#44; 95&#37;CI&#160;&#61;&#160;1&#46;336 &#8764; 1&#46;480&#59; OR&#160;&#61;&#160;1&#46;947&#44; 95&#37;CI&#160;&#61;&#160;1&#46;741 &#8764; 2&#46;175&#59; OR&#160;&#61;&#160;1&#46;153&#44; 95&#37;CI&#160;&#61;&#160;1&#46;116 &#8764; 1&#46;189&#59; OR&#160;&#61;&#160;1&#46;310&#44; 95&#37;CI&#160;&#61;&#160;1&#46;222 &#8764; 1&#46;404&#59; OR&#160;&#61;&#160;1&#46;075&#44; 95&#37;CI&#160;&#61;&#160;1&#46;003 &#8764; 1&#46;151&#41;&#46; On the contrary&#44; the lower levels of HDL-C and ApoA1 were related to the increased risk of severe pneumonia &#40;OR&#160;&#61;&#160;0&#46;903&#44; 95&#37;CI&#160;&#61;&#160;0&#46;873 &#8764; 0&#46;933&#59; OR&#160;&#61;&#160;0&#46;921&#44; 95&#37;CI&#160;&#61;&#160;0&#46;891 &#8764; 0&#46;952&#41;&#46; In addition&#44; the serum of Lp-a was not associated with the risk of the disease &#40;OR&#160;&#61;&#160;1&#46;012&#44; 95&#37;CI&#160;&#61;&#160;0&#46;979 &#8764; 1&#46;046&#41;&#46;</p></span><span id="sec0012" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0018">Association of the lipid metabolic markers with the risk of hypoxemia</span><p id="para0023" class="elsevierStylePara elsevierViewall">As shown in <a class="elsevierStyleCrossRef" href="#tbl0004">Table 4</a>&#44; the higher level of TG in serum was associated with the risk of hypoxemia in this group &#40;OR&#160;&#61;&#160;1&#46;172&#44; 95&#37;CI&#160;&#61;&#160;1&#46;028 &#8764; 1&#46;336&#41;&#46; However&#44; the serum levels of the other lipid metabolic markers were not related to the risk of hypoxemia in the common case group &#40;<a class="elsevierStyleCrossRef" href="#tbl0004">Table 4</a>&#41;&#46;</p><elsevierMultimedia ident="tbl0004"></elsevierMultimedia><p id="para0024" class="elsevierStylePara elsevierViewall">Similar to the common case group&#44; only the higher level of TG in serum was relate to the increased risk of hypoxemia in the severe case group &#40;OR&#160;&#61;&#160;1&#46;142&#44; 95&#37;CI&#160;&#61;&#160;1&#46;072 &#8764; 1&#46;215&#41;&#46; And the serum levels of the other lipid metabolic markers were not related to the risk of hypoxemia in this group &#40;<a class="elsevierStyleCrossRef" href="#tbl0004">Table 4</a>&#41;&#46;</p></span><span id="sec0013" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0019">Linear association of the lipid metabolic markers with serum C-reactive protein</span><p id="para0025" class="elsevierStylePara elsevierViewall">As shown in supplemental Table 1&#44; in the common case group&#44; the serum level of HDL-C was inversely associated with the serum level of C-reactive protein &#40;&#961;&#160;&#61;&#160;&#8722;0&#46;097&#44; <span class="elsevierStyleItalic">P</span>&#160;&#61;&#160;0&#46;002&#41;&#46; In the severe case group&#44; the serum level of HDL-C was also inversely associated with the serum level of C-reactive protein &#40;&#961;&#160;&#61;&#160;&#8722;0&#46;343&#44; <span class="elsevierStyleItalic">P</span>&#160;&#60;&#160;0&#46;001&#41;&#44; and the serum level of TC was positively correlated with the serum level of the inflammatory marker &#40;&#961;&#160;&#61;&#160;0&#46;064&#44; <span class="elsevierStyleItalic">P</span>&#160;&#61;&#160;0&#46;042&#41;&#46;</p></span></span><span id="sec0014" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0020">Discussion</span><p id="para0026" class="elsevierStylePara elsevierViewall">As mentioned above&#44; pneumonia is one of the major health challenges in children under 5 years of age&#44; and obesity is another emerging health issue for these children that have become increasingly important in recent years&#46;<a class="elsevierStyleCrossRef" href="#bib0013"><span class="elsevierStyleSup">13</span></a><span class="elsevierStyleSup">&#44;</span><a class="elsevierStyleCrossRef" href="#bib0014"><span class="elsevierStyleSup">14</span></a> And the Han Chinese are the dominant ethnic group in China and are also widely distributed in Southeast Asia&#44; North America and Western Europe&#44; with a population of over 1&#46;2 billion&#46; These two diseases mentioned above also severely affect Han Chinese children&#46;<a class="elsevierStyleCrossRefs" href="#bib0013"><span class="elsevierStyleSup">13-15</span></a> Therefore&#44; it is of great scientific and practical importance to explore the correlation between lipid metabolism and pneumonia in Han Chinese children of this age group&#46;</p><p id="para0027" class="elsevierStylePara elsevierViewall">Based on the results of this study&#44; the authors found that lipid metabolism was more closely related to severe pneumonia than common pneumonia&#46; For severe pneumonia&#44; the elevated levels of TG&#44; TC&#44; LDL-C&#44; VLDL-C and ApoB were implicated in the increased risk of severe pneumonia by about 7&#37; to 90&#37;&#44; while the elevated levels of HDL-C and ApoA1 were associated with the decreased risk of the disease by about 8&#37; to 10&#37;&#46; For common pneumonia&#44; only one lipid metabolic marker TC was related to the risk of common pneumonia&#44; and the elevated levels of it in serum was related to the increased risk of the disease by 10&#37;&#46; The study did not find any relationship between the other lipid metabolic markers and the risk of common pneumonia&#46; Thus&#44; the present study was partially consistent with the previous study&#44; although it did not cover so many lipid metabolic markers and did not distinguish pneumonia into common and severe groups&#46;<a class="elsevierStyleCrossRef" href="#bib0008"><span class="elsevierStyleSup">8</span></a></p><p id="para0028" class="elsevierStylePara elsevierViewall">It is well known that lipid metabolism disorders are often implicated in low-intensity metabolic inflammation in the body&#46;<a class="elsevierStyleCrossRef" href="#bib0016"><span class="elsevierStyleSup">16</span></a> In childhood pneumonia&#44; inflammation is also a pathophysiological process that is inextricably linked to the disease progression and prognosis&#44; accompanied by altered levels of numerous inflammatory factors &#40;including CRP&#41;&#46; More importantly&#44; the present study confirmed that there was a certain inversely linear relationship between serum HDL and CRP both in the common and severe cases&#44; while serum TC had a positive linear association with serum CRP in the severe cases&#46; Therefore&#44; both the previous knowledge as well as the authors&#8217; findings implied that the correlation between lipid metabolism and childhood pneumonia might be explained by inflammation&#46; However&#44; the exact mechanisms remained unclear and need to be explored in further research&#46;</p><p id="para0029" class="elsevierStylePara elsevierViewall">Hypoxaemia should be a serious clinical manifestation in childhood pneumonia&#44; which is often associated with a fatal prognosis&#46;<a class="elsevierStyleCrossRef" href="#bib0017"><span class="elsevierStyleSup">17</span></a> The present study found a correlation between serum TG and hypoxemia both in the common case and severe case groups&#46; Briefly&#44; the higher TG level in serum may suggest an increased risk of hypoxemia by more than 10&#37; in these two groups&#46; In fact&#44; an association between obesity and hypoxemia had long been established in sleep apnea syndrome&#44; and its mechanism was that obesity led to stricture of the respiratory tracts&#44; promoting apnea and hypoxemia&#46;<a class="elsevierStyleCrossRef" href="#bib0018"><span class="elsevierStyleSup">18</span></a><span class="elsevierStyleSup">&#44;</span><a class="elsevierStyleCrossRef" href="#bib0019"><span class="elsevierStyleSup">19</span></a> However&#44; because the present study failed to find any significant difference in obesity &#40;BMI Z-score&#41; levels among all three groups&#44; the relationship between hypoxemia and serum TG should be independent of obesity&#46; Furthermore&#44; both hypoxemia and plasma TG levels in pneumonia were clearly factors associated with inflammation&#44; it was possible that inflammation could be a potential mechanism linking these two factors mentioned above&#44; but future studies were needed to verify this assumption&#46;</p><p id="para0030" class="elsevierStylePara elsevierViewall">In the study&#44; pneumonia was diagnosed primarily based on the WHO criteria&#46; However&#44; cough and difficulty breathing were neither specific nor sensitive symptoms of the disease&#46; So&#44; the pneumonia children included in the study must be supported by the results of chest auscultation or chest x-ray&#44; which increased the accuracy of the diagnosis&#46;</p><p id="para0031" class="elsevierStylePara elsevierViewall">There were two advantages in the present study&#46; First&#44; the inclusion of 3000 children provided a sufficiently large sample size and test power&#46; Second&#44; the data in the study were analyzed at multiple levels&#46; For example&#44; the included children were grouped according to the severity of pneumonia&#44; and a series of lipid metabolic markers were also analyzed separately&#46; This helped the researchers discover more valuable information&#46;</p><p id="para0032" class="elsevierStylePara elsevierViewall">The most significant limitation of this study came from its cross-sectional design&#46; The correlation between obesity and lipid profile was clear&#46; In the present study&#44; the authors did not find any significant differences in obesity levels between the three groups&#44; so pneumonia &#40;especially severe pneumonia&#41; was the most likely factor associated with altered lipid profiles in children&#46; However&#44; due to the lack of reliable longitudinal data&#44; the authors were unable to determine whether altered lipid profiles preceded the onset of pneumonia&#46; After all&#44; pneumonia or other acute inflammatory states can also alter an individual&#39;s lipid profile&#46;<a class="elsevierStyleCrossRef" href="#bib0020"><span class="elsevierStyleSup">20</span></a> Therefore&#44; the available evidence did not yet support a direct independent pathogenic effect of lipid metabolism on disease severity&#46; Cohort studies as well as Mendelian randomization studies can continue to explore these questions at both phenotypic and genotypic levels&#44; in the expectation that they may provide more definitive conclusions&#44; and the present study could be an important basis for these future studies&#46;</p><p id="para0033" class="elsevierStylePara elsevierViewall">In conclusion&#44; there was a significant relationship between lipid metabolism and severe pneumonia &#40;but not common pneumonia&#41; in under-five children&#46; Briefly&#44; the elevated peripheral concentrations of TG&#44; TC&#44; LDL-C&#44; VLDL-C and ApoB might be related to the increased risk of severe pneumonia&#44; and the elevated peripheral concentrations of HDL-C and ApoA1 might be related to the decreased risk of the disease&#46; Furthermore&#44; the peripheral concentration of TG was associated with the development of hypoxemia both in common and severe pneumonia in these children&#46; In addition&#44; these relationships might be partly explained by inflammation&#46; More studies should be conducted to further validate this conclusion&#46;</p></span><span id="sec0016" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0022">Data availability statements</span><p id="para0035" class="elsevierStylePara elsevierViewall">Data can not be shared at present due to this is an ongoing study&#46; When the study was completed&#44; the data will be shared immediately&#46;</p></span></span>"
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        2 => array:2 [
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          "titulo" => "Introduction"
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          "titulo" => "Materials and methods"
          "secciones" => array:6 [
            0 => array:2 [
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              "titulo" => "Ethics statement"
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              "titulo" => "Characteristics of the subjects in the study"
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            1 => array:2 [
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              "titulo" => "Association of the lipid metabolic markers with the risk of pneumonia"
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              "identificador" => "sec0012"
              "titulo" => "Association of the lipid metabolic markers with the risk of hypoxemia"
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              "titulo" => "Linear association of the lipid metabolic markers with serum C-reactive protein"
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          "titulo" => "Discussion"
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    "pdfFichero" => "main.pdf"
    "tienePdf" => true
    "fechaRecibido" => "2022-12-01"
    "fechaAceptado" => "2023-03-30"
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          "clase" => "keyword"
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          "palabras" => array:5 [
            0 => "Apolipoprotein"
            1 => "Hypoxemia"
            2 => "Lipid metabolism"
            3 => "Pneumonia"
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    "resumen" => array:1 [
      "en" => array:3 [
        "titulo" => "Abstract"
        "resumen" => "<span id="abss0001" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0002">Objective</span><p id="spara005" class="elsevierStyleSimplePara elsevierViewall">The relationship between lipid metabolism and pneumonia in under-five children remains unclear&#46; The aim of the study was to explore the association of several lipids&#44; lipoproteins and apolipoproteins with the risk of childhood pneumonia&#44; and to initially reveal the mechanisms involved&#46;</p></span> <span id="abss0002" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0003">Methods</span><p id="spara006" class="elsevierStyleSimplePara elsevierViewall">There were 1000 children with confirmed severe pneumonia and 1000 healthy controls &#40;18&#8211;59 months old&#41; in the study&#46; Serum levels of several lipids&#44; lipoproteins and apolipoproteins were measured&#46; The occurrence of hypoxaemia and serum level of C-reactive protein were recorded&#46; Multivariate logistic regression and spearman correlation analysis were adopted to assess the correlation between these variables to achieve the research objective&#46;</p></span> <span id="abss0003" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0004">Results</span><p id="spara007" class="elsevierStyleSimplePara elsevierViewall">First&#44; higher triglycerides&#44; total cholesterol&#44; LDL cholesterol&#44; VLDL cholesterol and apolipoprotein B levels were associated with the elevated risk of severe pneumonia &#40;OR&#58; 1&#46;407&#44; 95&#37;CI&#58; 1&#46;336&#8764;1&#46;480&#59; OR&#58; 1&#46;947&#44; 95&#37;CI&#58; 1&#46;741&#8764;2&#46;175&#59; OR&#58; 1&#46;153&#44; 95&#37;CI&#58; 1&#46;116&#8764;1&#46;189&#59; OR&#58; 1&#46;310&#44; 95&#37;CI&#58; 1&#46;222&#8764;1&#46;404&#59; OR&#58; 1&#46;075&#44; 95&#37;CI&#58; 1&#46;003&#8764;1&#46;151&#41;&#46; Higher HDL cholesterol and apolipoprotein A1 levels were associated with a decreased risk of the disease &#40;OR&#58; 0&#46;903&#44; 95&#37;CI&#58; 0&#46;873&#8764;0&#46;933&#59; OR&#58; 0&#46;921&#44; 95&#37;CI&#58; 0&#46;891&#8764;0&#46;952&#41;&#46; Second&#44; higher triglycerides level was associated with an increased risk of hypoxemia in these children &#40;OR&#58; 1&#46;142&#44; 95&#37;CI&#58; 1&#46;072&#8764;1&#46;215&#41;&#46; Third&#44; serum HDL cholesterol level was linearly associated with C-reactive protein level in these children &#40;<span class="elsevierStyleItalic">&#961;</span>&#160;&#61;&#160;-0&#46;343&#44; <span class="elsevierStyleItalic">P</span> &#60; 0&#46;001&#41;&#46;</p></span> <span id="abss0004" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="cesectitle0005">Conclusion</span><p id="spara008" class="elsevierStyleSimplePara elsevierViewall">Abnormal levels of several lipids&#44; lipoproteins and apolipoproteins were related to severe childhood pneumonia&#46; The findings that triglycerides and HDL cholesterol were respectively implicated in hypoxaemia and inflammation might partly explain the mechanisms linking lipid metabolism to severe pneumonia&#46;</p></span>"
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                  \t\t\t\t</td><a name="en0022"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">49 &#40;42&#44; 55&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0023"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">0&#46;383&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0024"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">0&#46;826&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0025"></a><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="" valign="top"><span class="elsevierStyleHsp" style=""></span>Male &#40;n&#44;&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0026"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">699&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0027"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">685&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0028"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">676&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0029"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">1&#46;231&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0030"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">0&#46;267&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0031"></a><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="" valign="top"><span class="elsevierStyleHsp" style=""></span>Han nationality &#40;n&#44;&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0032"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">939&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0033"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">925&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0034"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">934&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0035"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">1&#46;546&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0036"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">0&#46;214&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0037"></a><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="" valign="top"><span class="elsevierStyleHsp" style=""></span>BMI Z-score&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0038"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">1&#46;00 &#40;&#8722;0&#46;58&#44; 2&#46;46&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0039"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">0&#46;91 &#40;&#8722;0&#46;58&#44; 2&#46;67&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0040"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">1&#46;17 &#40;&#8722;0&#46;35&#44; 2&#46;84&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0041"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">5&#46;054&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0042"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">0&#46;080&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0043"></a><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="" valign="top"><span class="elsevierStyleHsp" style=""></span>Household income &#40;yuan&#41;<a class="elsevierStyleCrossRef" href="#tb1fn2"><span class="elsevierStyleSup">b</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0044"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">2900 &#40;2000&#44; 3900&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0045"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">2900 &#40;1900&#44; 3900&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0046"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">3000 &#40;1800&#44; 3800&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0047"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">3&#46;225&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0048"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">0&#46;199&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0049"></a><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="" valign="top">Clinical manifestations&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0050"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0051"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0052"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0053"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0054"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0055"></a><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="" valign="top"><span class="elsevierStyleHsp" style=""></span>Hyperpyrexia &#40;n&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0056"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">&#8212;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0057"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">195&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0058"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">340&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0059"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">53&#46;651&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0060"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0061"></a><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="" valign="top"><span class="elsevierStyleHsp" style=""></span>Dehydration &#40;n&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0062"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">&#8212;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0063"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">155&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0064"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">275&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0065"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">42&#46;660&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0066"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0067"></a><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="" valign="top"><span class="elsevierStyleHsp" style=""></span>Diarrhea &#40;n&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0068"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">&#8212;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0069"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">225&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0070"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">295&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0071"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">12&#46;734&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0072"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0073"></a><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="" valign="top"><span class="elsevierStyleHsp" style=""></span>Hypoxemia &#40;n&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0074"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">&#8212;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0075"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">78&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0076"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">231&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0077"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">89&#46;601&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0078"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0079"></a><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="" valign="top">Serological data&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0080"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0081"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0082"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0083"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0084"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0085"></a><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="" valign="top"><span class="elsevierStyleHsp" style=""></span>WBC count &#40;&#215; 10<span class="elsevierStyleSup">9</span>&#47;l&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0086"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">&#8212;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0087"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">12&#46;89 &#40;9&#46;69&#44; 16&#46;06&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0088"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">12&#46;31 &#40;9&#46;41&#44; 15&#46;93&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0089"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">2&#46;609&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0090"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">0&#46;106&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0091"></a><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="" valign="top"><span class="elsevierStyleHsp" style=""></span>High creatinine &#40;n&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0092"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">&#8212;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0093"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">75&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0094"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">235&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0095"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">97&#46;729&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0096"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0097"></a><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="" valign="top"><span class="elsevierStyleHsp" style=""></span>C-reactive protein &#40;mg&#47;l&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0098"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">&#8212;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0099"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">103&#46;19 &#40;54&#46;18&#44; 161&#46;84&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0100"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">137&#46;10 &#40;63&#46;03&#44; 198&#46;04&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0101"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">45&#46;871&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0102"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0103"></a><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="" valign="top">Antibiotics&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0104"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0105"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0106"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0107"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0108"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0109"></a><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="" valign="top"><span class="elsevierStyleHsp" style=""></span>Cephalosporins&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0110"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">&#8212;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0111"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">865&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0112"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">935&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0113"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">27&#46;222&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0114"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0115"></a><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="" valign="top"><span class="elsevierStyleHsp" style=""></span>Macrolides&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0116"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">&#8212;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0117"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">625&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0118"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">490&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0119"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">36&#46;939&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0120"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0121"></a><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="" valign="top"><span class="elsevierStyleHsp" style=""></span>Other antibiotics&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0122"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">&#8212;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0123"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">240&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0124"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">475&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0125"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">120&#46;214&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0126"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0127"></a><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="" valign="top"><span class="elsevierStyleHsp" style=""></span>Required to change antibiotics&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0128"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">&#8212;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0129"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">310&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0130"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">575&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0131"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">142&#46;332&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0132"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr></tbody></table>
                  """
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            0 => array:2 [
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                0 => """
                  <table border="0" frame="\n
                  \t\t\t\t\tvoid\n
                  \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><a name="en0133"></a><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="" valign="top" scope="col" style="border-bottom: 2px solid black">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><a name="en0134"></a><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="" valign="top" scope="col" style="border-bottom: 2px solid black">Control&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><a name="en0135"></a><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="" valign="top" scope="col" style="border-bottom: 2px solid black">Common case&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><a name="en0136"></a><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="" valign="top" scope="col" style="border-bottom: 2px solid black">Severe case&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><a name="en0137"></a><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="" valign="top" scope="col" style="border-bottom: 2px solid black">H value&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><a name="en0138"></a><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="" valign="top" scope="col" style="border-bottom: 2px solid black">P value&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><a name="en0139"></a><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="" valign="top">Total &#40;n&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0140"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">1000&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0141"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">1000&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0142"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">1000&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0143"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0144"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0145"></a><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="" valign="top">TG &#40;mmol&#47;l&#41; <a class="elsevierStyleCrossRef" href="#tb2fn2"><span class="elsevierStyleSup">b</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0146"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">0&#46;83 &#40;0&#46;66&#44; 0&#46;96&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0147"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">0&#46;83 &#40;0&#46;67&#44; 0&#46;99&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0148"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">0&#46;98 &#40;0&#46;76&#44; 1&#46;19&#41; &#8225;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0149"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">298&#46;258&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0150"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0151"></a><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="" valign="top">TC &#40;mmol&#47;l&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0152"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">3&#46;49 &#40;2&#46;73&#44; 4&#46;25&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0153"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">3&#46;63 &#40;2&#46;83&#44; 4&#46;38&#41; &#8224;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0154"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">4&#46;09 &#40;3&#46;26&#44; 4&#46;87&#41; &#8225;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0155"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">193&#46;845&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0156"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0157"></a><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="" valign="top">LDL-C &#40;mmol&#47;l&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0158"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">2&#46;01 &#40;1&#46;77&#44; 2&#46;26&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0159"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">2&#46;03 &#40;1&#46;76&#44; 2&#46;30&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0160"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">2&#46;19 &#40;1&#46;85&#44; 2&#46;49&#41; &#8225;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0161"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">110&#46;759&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0162"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0163"></a><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="" valign="top">VLDL-C &#40;mmol&#47;l&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0164"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">0&#46;33 &#40;0&#46;20&#44; 0&#46;45&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0165"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">0&#46;33 &#40;0&#46;24&#44; 0&#46;46&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0166"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">0&#46;39 &#40;0&#46;26&#44; 0&#46;53&#41; &#8225;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0167"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">85&#46;380&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0168"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0169"></a><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="" valign="top">HDL-C &#40;mmol&#47;l&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0170"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">1&#46;36 &#40;1&#46;06&#44; 1&#46;67&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0171"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">1&#46;34 &#40;1&#46;08&#44; 1&#46;60&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0172"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">1&#46;25 &#40;1&#46;00&#44; 1&#46;49&#41; &#8225;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0173"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">66&#46;823&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0174"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0175"></a><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="" valign="top">Lp-a &#40;mmol&#47;l&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0176"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">57&#46;23 &#40;32&#46;77&#44; 84&#46;77&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0177"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">58&#46;26 &#40;31&#46;32&#44; 87&#46;33&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0178"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">59&#46;42 &#40;29&#46;99&#44; 88&#46;18&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0179"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">1&#46;675&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0180"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">0&#46;433&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0181"></a><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="" valign="top">ApoA1 &#40;g&#47;l&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0182"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">1&#46;17 &#40;0&#46;87&#44; 1&#46;48&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0183"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">1&#46;16 &#40;0&#46;88&#44; 1&#46;42&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0184"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">1&#46;07 &#40;0&#46;84&#44; 1&#46;34&#41; &#8225;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0185"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">39&#46;981&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0186"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0187"></a><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="" valign="top">ApoB &#40;g&#47;l&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0188"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">0&#46;47 &#40;0&#46;36&#44; 0&#46;59&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0189"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">0&#46;48 &#40;0&#46;35&#44; 0&#46;62&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0190"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">0&#46;48 &#40;0&#46;36&#44; 0&#46;63&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0191"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">8&#46;524&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0192"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">0&#46;014&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr></tbody></table>
                  """
              ]
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                0 => "xTab3256810.png"
              ]
            ]
          ]
          "notaPie" => array:2 [
            0 => array:3 [
              "identificador" => "tb2fn1"
              "etiqueta" => "a"
              "nota" => "<p class="elsevierStyleNotepara" id="notep0003">The serum levels of lipids&#44; lipoproteins and apolipoproteins were expressed using medians &#40;25th quartiles&#44; 75th quartiles&#41;&#46; The difference of these markers was measured using Kruskal-Wallis H test&#46; &#8220;&#8224;&#8221; indicated &#8220;compared with control group&#44; P&#60;0&#46;05&#8243;&#59; &#8220;&#8225;&#8221; indicated &#8220;compared with common case group&#44; P&#60;0&#46;05&#8243;&#46;</p>"
            ]
            1 => array:3 [
              "identificador" => "tb2fn2"
              "etiqueta" => "b"
              "nota" => "<p class="elsevierStyleNotepara" id="notep0004">TG&#160;&#61;&#160;Triglycerides&#59; TC&#160;&#61;&#160;Total cholesterol&#59; LDL-C&#160;&#61;&#160;Low-density lipoprotein cholesterol&#59; VLDL-C&#160;&#61;&#160;Very low-density lipoprotein cholesterol&#59; HDL-C&#160;&#61;&#160;High-density lipoprotein cholesterol&#59; ApoA1&#160;&#61;&#160;Apolipoprotein A1&#59; ApoB&#160;&#61;&#160;Apolipoprotein B&#59; Lp-<span class="elsevierStyleItalic">a</span>&#160;&#61;&#160;Lipoprotein A&#46;</p>"
            ]
          ]
        ]
        "descripcion" => array:1 [
          "en" => "<p id="spara002" class="elsevierStyleSimplePara elsevierViewall">Serum levels of lipids&#44; lipoproteins and apolipoproteins in the study&#46;<a class="elsevierStyleCrossRef" href="#tb2fn1"><span class="elsevierStyleSup">a</span></a></p>"
        ]
      ]
      2 => array:8 [
        "identificador" => "tbl0003"
        "etiqueta" => "Table 3"
        "tipo" => "MULTIMEDIATABLA"
        "mostrarFloat" => true
        "mostrarDisplay" => false
        "detalles" => array:1 [
          0 => array:3 [
            "identificador" => "alt0003"
            "detalle" => "Table "
            "rol" => "short"
          ]
        ]
        "tabla" => array:2 [
          "tablatextoimagen" => array:2 [
            0 => array:2 [
              "tabla" => array:1 [
                0 => """
                  <table border="0" frame="\n
                  \t\t\t\t\tvoid\n
                  \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><a name="en0193"></a><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="" valign="top" scope="col">Risk of common case&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><a name="en0194"></a><th class="td-with-role" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t ; entry_with_role_colgroup " colspan="2" align="center" valign="top" scope="col" style="border-bottom: 2px solid black">Univariate logistic regression</th><a name="en0195"></a><th class="td-with-role" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t ; entry_with_role_colgroup " colspan="2" align="center" valign="top" scope="col" style="border-bottom: 2px solid black">Multivariate logistic regression</th></tr><tr title="table-row"><a name="en0193a"></a><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="" valign="top" scope="col" style="border-bottom: 2px solid black">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><a name="en0197"></a><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="" valign="top" scope="col" style="border-bottom: 2px solid black">OR&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><a name="en0198"></a><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="" valign="top" scope="col" style="border-bottom: 2px solid black">95&#37;CI&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><a name="en0199"></a><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="" valign="top" scope="col" style="border-bottom: 2px solid black">OR&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><a name="en0200"></a><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="" valign="top" scope="col" style="border-bottom: 2px solid black">95&#37;CI&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><a name="en0201"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">TG<a class="elsevierStyleCrossRef" href="#tb3fn2"><span class="elsevierStyleSup">b</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0202"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">1&#46;045&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0203"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">0&#46;995 &#8764; 1&#46;097&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0204"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">1&#46;046&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0205"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">0&#46;995 &#8764; 1&#46;098&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0206"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">TC&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0207"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">1&#46;109&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0208"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">1&#46;013 &#8764; 1&#46;214&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0209"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">1&#46;110&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0210"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">1&#46;014 &#8764; 1&#46;214&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0211"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">LDL-C&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0212"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">1&#46;028&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0213"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">0&#46;999 &#8764; 1&#46;059&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0214"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">1&#46;028&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0215"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">0&#46;999 &#8764; 1&#46;059&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0216"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">VLDL-C&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0217"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">1&#46;063&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0218"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">0&#46;996 &#8764; 1&#46;134&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0219"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">1&#46;064&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0220"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">0&#46;996 &#8764; 1&#46;135&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0221"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">HDL-C&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0222"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">0&#46;990&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0223"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">0&#46;963 &#8764; 1&#46;017&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0224"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">0&#46;992&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0225"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">0&#46;963 &#8764; 1&#46;018&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0226"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">Lp-a&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0227"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">1&#46;011&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0228"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">0&#46;983 &#8764; 1&#46;040&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0229"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">1&#46;011&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0230"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">0&#46;984 &#8764; 1&#46;040&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0231"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">ApoA1&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0232"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">0&#46;979&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0233"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">0&#46;953 &#8764; 1&#46;007&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0234"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">0&#46;980&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0235"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">0&#46;953 &#8764; 1&#46;008&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0236"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">ApoB&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0237"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">1&#46;039&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0238"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">0&#46;979 &#8764; 1&#46;102&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0239"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">1&#46;039&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0240"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">0&#46;979 &#8764; 1&#46;103&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr></tbody></table>
                  """
              ]
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                0 => "xTab3256811.png"
              ]
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            1 => array:2 [
              "tabla" => array:1 [
                0 => """
                  <table border="0" frame="\n
                  \t\t\t\t\tvoid\n
                  \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><a name="en0241"></a><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="" valign="top" scope="col">Risk of severe case&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><a name="en0242"></a><th class="td-with-role" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t ; entry_with_role_colgroup " colspan="2" align="center" valign="top" scope="col" style="border-bottom: 2px solid black">Univariate logistic regression</th><a name="en0243"></a><th class="td-with-role" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t ; entry_with_role_colgroup " colspan="2" align="center" valign="top" scope="col" style="border-bottom: 2px solid black">Multivariate logistic regression</th></tr><tr title="table-row"><a name="en0241a"></a><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="" valign="top" scope="col" style="border-bottom: 2px solid black">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><a name="en0245"></a><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="" valign="top" scope="col" style="border-bottom: 2px solid black">OR&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><a name="en0246"></a><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="" valign="top" scope="col" style="border-bottom: 2px solid black">95&#37;CI&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><a name="en0247"></a><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="" valign="top" scope="col" style="border-bottom: 2px solid black">OR&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><a name="en0248"></a><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="" valign="top" scope="col" style="border-bottom: 2px solid black">95&#37;CI&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><a name="en0249"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">TG&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0250"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">1&#46;406&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0251"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">1&#46;336 &#8764; 1&#46;479&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0252"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">1&#46;407&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0253"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">1&#46;336 &#8764; 1&#46;480&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0254"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">TC&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0255"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">1&#46;946&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0256"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">1&#46;740 &#8764; 2&#46;175&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0257"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">1&#46;947&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0258"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">1&#46;741 &#8764; 2&#46;175&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0259"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">LDL-C&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0260"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">1&#46;152&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0261"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">1&#46;116 &#8764; 1&#46;188&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0262"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">1&#46;153&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0263"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">1&#46;116 &#8764; 1&#46;189&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0264"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">VLDL-C&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0265"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">1&#46;309&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0266"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">1&#46;221 &#8764; 1&#46;403&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0267"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">1&#46;310&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0268"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">1&#46;222 &#8764; 1&#46;404&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0269"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">HDL-C&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0270"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">0&#46;902&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0271"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">0&#46;873 &#8764; 0&#46;932&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0272"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">0&#46;903&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0273"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">0&#46;873 &#8764; 0&#46;933&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0274"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">Lp-a&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0275"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">1&#46;011&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0276"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">0&#46;979 &#8764; 1&#46;045&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0277"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">1&#46;012&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0278"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">0&#46;979 &#8764; 1&#46;046&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0279"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">ApoA1&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0280"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">0&#46;921&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0281"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">0&#46;891 &#8764; 0&#46;951&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0282"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">0&#46;921&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0283"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">0&#46;891 &#8764; 0&#46;952&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0284"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">ApoB&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0285"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">1&#46;074&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0286"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">1&#46;003 &#8764; 1&#46;150&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0287"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">1&#46;075&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0288"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">1&#46;003 &#8764; 1&#46;151&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr></tbody></table>
                  """
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            0 => array:3 [
              "identificador" => "tb3fn1"
              "etiqueta" => "a"
              "nota" => "<p class="elsevierStyleNotepara" id="notep0005">The association of serum lipids&#44; lipoproteins and apolipoproteins with the risk of common and severe pneumonia was performed by univariate and multivariate logistic regression&#44; and their ORs and 95&#37;CIs were reported&#46; In the multivariate analyses&#44; demography data&#44; clinical manifestations&#44; serological data and antibiotics were adjusted&#46;</p>"
            ]
            1 => array:3 [
              "identificador" => "tb3fn2"
              "etiqueta" => "b"
              "nota" => "<p class="elsevierStyleNotepara" id="notep0006">TG&#160;&#61;&#160;Triglycerides&#59; TC&#160;&#61;&#160;Total cholesterol&#59; LDL-C&#160;&#61;&#160;Low-density lipoprotein cholesterol&#59; VLDL-C&#160;&#61;&#160;Very low-density lipoprotein cholesterol&#59; HDL-C&#160;&#61;&#160;High-density lipoprotein cholesterol&#59; ApoA1&#160;&#61;&#160;Apolipoprotein A1&#59; ApoB&#160;&#61;&#160;Apolipoprotein B&#59; Lp-<span class="elsevierStyleItalic">a</span>&#160;&#61;&#160;Lipoprotein A&#46;</p>"
            ]
          ]
        ]
        "descripcion" => array:1 [
          "en" => "<p id="spara003" class="elsevierStyleSimplePara elsevierViewall">Association of serum lipids&#44; lipoproteins and apolipoproteins with the risk of common and severe pneumonia&#46;<a class="elsevierStyleCrossRef" href="#tb3fn1"><span class="elsevierStyleSup">a</span></a></p>"
        ]
      ]
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        "etiqueta" => "Table 4"
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            "detalle" => "Table "
            "rol" => "short"
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                0 => """
                  <table border="0" frame="\n
                  \t\t\t\t\tvoid\n
                  \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><a name="en0289"></a><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="" valign="top" scope="col">Risk of hypoxemia in common case&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><a name="en0290"></a><th class="td-with-role" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t ; entry_with_role_colgroup " colspan="2" align="center" valign="top" scope="col" style="border-bottom: 2px solid black">Univariate logistic regression</th><a name="en0291"></a><th class="td-with-role" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t ; entry_with_role_colgroup " colspan="2" align="center" valign="top" scope="col" style="border-bottom: 2px solid black">Multivariate logistic regression</th></tr><tr title="table-row"><a name="en0289a"></a><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="" valign="top" scope="col" style="border-bottom: 2px solid black">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><a name="en0293"></a><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="" valign="top" scope="col" style="border-bottom: 2px solid black">OR&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><a name="en0294"></a><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="" valign="top" scope="col" style="border-bottom: 2px solid black">95&#37;CI&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><a name="en0295"></a><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="" valign="top" scope="col" style="border-bottom: 2px solid black">OR&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><a name="en0296"></a><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="" valign="top" scope="col" style="border-bottom: 2px solid black">95&#37;CI&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><a name="en0297"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">TG<a class="elsevierStyleCrossRef" href="#tb4fn2"><span class="elsevierStyleSup">b</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0298"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">1&#46;171&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0299"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">1&#46;028 &#8764; 1&#46;335&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0300"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">1&#46;172&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0301"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">1&#46;028 &#8764; 1&#46;336&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0302"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">TC&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0303"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">0&#46;982&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0304"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">0&#46;773 &#8764; 1&#46;249&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0305"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">0&#46;983&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0306"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">0&#46;774 &#8764; 1&#46;249&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0307"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">LDL-C&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0308"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">1&#46;050&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0309"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">0&#46;976 &#8764; 1&#46;130&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0310"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">1&#46;051&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0311"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">0&#46;976 &#8764; 1&#46;131&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0312"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">VLDL-C&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0313"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">1&#46;031&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0314"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">0&#46;859 &#8764; 1&#46;237&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0315"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">1&#46;032&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0316"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">0&#46;859 &#8764; 1&#46;237&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0317"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">HDL-C&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0318"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">1&#46;060&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0319"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">0&#46;981 &#8764; 1&#46;145&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0320"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">1&#46;060&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0321"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">0&#46;981 &#8764; 1&#46;146&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0322"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">Lp-a&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0323"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">0&#46;992&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0324"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">0&#46;923 &#8764; 1&#46;066&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0325"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">0&#46;993&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0326"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">0&#46;923 &#8764; 1&#46;066&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><a name="en0327"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">ApoA1&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0328"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">1&#46;021&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0329"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">0&#46;946 &#8764; 1&#46;103&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0330"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">1&#46;021&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><a name="en0331"></a><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="top">0&#46;947 &#8764; 1&#46;103&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t  " align="" valign="top">0&#46;969 &#8764; 1&#46;324&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t  " align="" valign="top">0&#46;917 &#8764; 1&#46;004&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t  " align="" valign="top">0&#46;961&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t  " align="" valign="top">0&#46;917 &#8764; 1&#46;005&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t  " align="" valign="top">ApoA1&nbsp;\t\t\t\t\t\t\n
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                            0 => "T&#46;K&#46; Nguyen"
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                            3 => "C&#46;G&#46; Grijalva"
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                      "titulo" => "Global climate change and mental health"
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                          "autores" => array:2 [
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                      "doi" => "10.1016/j.copsyc.2019.06.023"
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                        "tituloSerie" => "Curr Opin Psychol"
                        "fecha" => "2020"
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Vol. 99. Issue 5.
Pages 500-506 (September - October 2023)
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Vol. 99. Issue 5.
Pages 500-506 (September - October 2023)
Original article
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Association of lipid metabolism with pneumonia risk in under-five children in China
Visits
1701
Qianhan Wang
Corresponding author
qianhan789324@126.com

Corresponding author.
, Yonghong Miao, Qiongdan Zhao
Department of Pediatrics, Henan Provincial People's Hospital, Zhengzhou, Henan Province, China
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Tables (4)
Table 1. Characteristics of the subjects in the study.a
Table 2. Serum levels of lipids, lipoproteins and apolipoproteins in the study.a
Table 3. Association of serum lipids, lipoproteins and apolipoproteins with the risk of common and severe pneumonia.a
Table 4. Association of serum lipids, lipoproteins and apolipoproteins with the risk of hypoxemia in common and severe case group.a
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Additional material (1)
Abstract
Objective

The relationship between lipid metabolism and pneumonia in under-five children remains unclear. The aim of the study was to explore the association of several lipids, lipoproteins and apolipoproteins with the risk of childhood pneumonia, and to initially reveal the mechanisms involved.

Methods

There were 1000 children with confirmed severe pneumonia and 1000 healthy controls (18–59 months old) in the study. Serum levels of several lipids, lipoproteins and apolipoproteins were measured. The occurrence of hypoxaemia and serum level of C-reactive protein were recorded. Multivariate logistic regression and spearman correlation analysis were adopted to assess the correlation between these variables to achieve the research objective.

Results

First, higher triglycerides, total cholesterol, LDL cholesterol, VLDL cholesterol and apolipoprotein B levels were associated with the elevated risk of severe pneumonia (OR: 1.407, 95%CI: 1.336∼1.480; OR: 1.947, 95%CI: 1.741∼2.175; OR: 1.153, 95%CI: 1.116∼1.189; OR: 1.310, 95%CI: 1.222∼1.404; OR: 1.075, 95%CI: 1.003∼1.151). Higher HDL cholesterol and apolipoprotein A1 levels were associated with a decreased risk of the disease (OR: 0.903, 95%CI: 0.873∼0.933; OR: 0.921, 95%CI: 0.891∼0.952). Second, higher triglycerides level was associated with an increased risk of hypoxemia in these children (OR: 1.142, 95%CI: 1.072∼1.215). Third, serum HDL cholesterol level was linearly associated with C-reactive protein level in these children (ρ = -0.343, P < 0.001).

Conclusion

Abnormal levels of several lipids, lipoproteins and apolipoproteins were related to severe childhood pneumonia. The findings that triglycerides and HDL cholesterol were respectively implicated in hypoxaemia and inflammation might partly explain the mechanisms linking lipid metabolism to severe pneumonia.

Keywords:
Apolipoprotein
Hypoxemia
Lipid metabolism
Pneumonia
Inflammation
Full Text
Introduction

Pneumonia is one of the leading causes of death in children under the age of five all around the world.1,2 According to statistics, pneumonia caused more than 800,000 childhood deaths in 2017, which accounts for 15% of all deaths of under-five children that year.2 In China, the prevalence of childhood pneumonia is also very high.3 The disease not only seriously affects the children's health, but also significantly increases the financial burden on their families and the psychological burden on their guardians.4 Although doctors have made great efforts to treat pneumonia and reduce mortality, the results have not been satisfactory.5 One very important reason for this is that a great number of factors may influence the susceptibility and prognosis of pneumonia, such as socioeconomic status, malnutrition, and so on.2

Currently, obesity has gradually become a new global health problem in children under the age of five.6 One published study reported a prognostic significance of obesity and overweight on pneumonia in this group of children.7 Then, whether lipid metabolism was also related to childhood pneumonia attracted the attention of researchers. But a series of related studies failed to provide consistent results. Some studies believed that the increased levels of some lipid metabolic markers such as triglycerides may worsen the prognosis of childhood pneumonia.8 Others suggested that cholesterol metabolism and the elevated levels of several apolipoproteins may have a protective effect on the disease.9,10 So, a firmed conclusion has not been drawn until then.

Therefore, the present study enrolled 3000 children under the age of five in China to reveal the association of several lipids, lipoproteins, and apolipoproteins with the risk of childhood pneumonia, and to further explore the association of these lipid metabolic markers with the risk of hypoxemia induced by pneumonia and the levels of C-reactive protein (CRP) in serums. The results obtained from the study may help people to determine whether lipid metabolism may be a potential effective factor in childhood pneumonia.

Materials and methodsEthics statement

The study was approved by the ethics committee of Henan provincial people's hospital and was performed in accordance with the Declaration of Helsinki (Supplemental Fig. 1). The guardians of the included children agreed to participate in the study and signed the written consents.

Data source

The data of the study were collected from the medical records of Henan provincial people's hospital. Briefly, all patients admitted to the hospital were told that their medical records might be used anonymously for scientific research. If the patients or their families agreed, the written informed consent forms would be signed. After the patients were discharged from the hospital, their medical records would be included in the scientific research database.

Subjects

A total of 1000 children with common pneumonia, and 1000 children with severe pneumonia were randomly included from the database, and all of them were admitted to the hospital between January 2010 and December 2020 due to pneumonia. Their age was limited to 18 to 60 months.

Pneumonia was diagnosed and classified using the criteria of the World Health Organization (WHO), which included: a history of cough or difficulty breathing, and if present, respiratory rate > 50 breaths/minute (age < 12 months) or > 40 breaths/minute (age ≥ 12 months).11 Severe pneumonia indicated that the disease met the above diagnostic criteria and was accompanied by at least one of the danger signs, which included (1) nasal flaring, (2) subcostal retractions, (3) convulsions, (4) Blantyre coma scale < 5, (5) “alert, voice, pain, unresponsive” scale less than “alert” and (6) inability to drink or feed. Common pneumonia was defined as meeting the above diagnostic criteria without the danger signs. Children with tuberculosis infection, congenital lung diseases, dysplasia disorders and other serious diseases were excluded. All the children with pneumonia were treated according to the protocolized guidelines for the diagnosis and treatment of pneumonia in China and the world.11

Other 1000 healthy children were randomly included from the database, and all of them came to the hospital for consultation at the same period, but no obvious disease was detected. They served as controls. Their ages ranged from 18 to 60 months.

Data collection and definition

Research data were obtained from the database using predefined questionnaires. For the children with pneumonia, age, gender, ethnic group, height, weight, household income, clinical manifestations (i.e., hyperpyrexia, dehydration, diarrhea and hypoxemia), serological data (i.e., serum white blood cell (WBC) count, creatinine level and CRP) and use of antibiotics were collected. For the controls, age, gender, ethnic group, height, weight and household income were collected.

Hyperpyrexia was a body temperature greater than 39°C. Hypoxaemia was defined as SpO2 < 90%. High creatinine referred to plasma creatinine levels greater than 35 mmol/l in infants and greater than 62 mmol/l in children.

Generally, obesity is assessed using the body mass index (BMI), which is calculated based on weight and height. However, children under 60 months of age are in a rapid growth and development phase. To increase the comparability, BMI Z-scores were calculated in the study to standardize the data, and its formula was (BMI - mean of BMI) / (standard deviation of BMI).12 The mean and standard deviation of BMI for the local population were obtained from the local Center for Disease Control and Prevention. A BMIZ score greater than 2.00 was considered overweight, a score greater than 3.00 was diagnosed as obesity, and the score between −2.00 and 2.00 was defined as normal.12

Lipid metabolism

The serum levels of several lipids, lipoproteins and apolipoproteins were adopted to reflect lipid metabolism. The lipid metabolic markers included triglycerides (TG), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), very low-density lipoprotein cholesterol (VLDL-C), high-density lipoprotein cholesterol (HDL-C), apolipoprotein A1 (ApoA1), apolipoprotein B (ApoB) and lipoprotein A (Lp-a).

These data were also collected from the database, and the blood specimen collection and testing process was briefly described below. When each child presented to the hospital, his or her fasting venous blood was routinely collected to measure a range of serological markers (such as blood lipids) in order to guide the diagnosis and treatment. The blood sample was immediately sent to the laboratory center of the hospital. After centrifugation and extraction, the serum sample was used to measure the levels of these lipid metabolic markers mentioned above. Serum levels of TG, TC, LDL-C, VLDL-C and HDL-C were detected using an ADVIA-1650 Chemistry System (Bayer Co., USA). Serum levels of ApoA1, ApoB and Lp-a were determined by several latex-particle-enhanced immunonephelometric assays on a BN ProSpec nephelometer (Dade Behring Co., Germany). Each serological marker was measured twice, and their average value was recorded in the database.

Statistical analysis

According to the Shapiro-Wilk test, all continuous variables in this study did not follow a normal distribution. Therefore, these variables were expressed by medians (25th quartiles, 75th quartiles), while the differences between groups were compared by Kruskal-Wallis H test. Categorical variables were expressed by frequencies, and the difference of the two categorical variables was measured using the Chi-square test. If there were three categorical variables to be compared at the same time, the maximum and minimum values were compared. The linear association of two continuous variables was determined using spearman correlation analysis. A P-value less than 0.05 was considered statistically significant. The Association of the lipids, lipoproteins and apolipoproteins with the risk of childhood pneumonia and hypoxemia was determined using univariate and multivariate logistic regression. The odds ratios (ORs) and 95% confidence intervals (CIs) were reported. In the multivariate analyses, demography data, clinical manifestations, serological data and use of antibiotics were adjusted. If a 95%CI did not include value one, it was considered statistically significant. All analyses were conducted using SPSS 23.0 (USA).

ResultsCharacteristics of the subjects in the study

As shown in Table 1, compared with the common case group, the children in the severe case group had more opportunities to suffer from hyperpyrexia, dehydration, diarrhea, hypoxemia, high creatinine, high CRP (P < 0.001, P < 0.001, P < 0.001, P < 0.001, P < 0.001, P < 0.001), to receive the cephalosporins treatment (P < 0.001) and to change the antibiotics (P < 0.001). Compared with the severe case group, the children in the common case group had more possibilities to receive the macrolides treatment (P <  0.001). In addition, there was no difference in WBC count between the common case and severe case groups (P = 0.106). There was no difference in age, gender, and nationality, BMI Z-score, and household income among all the three groups (P = 0.826, P = 0.267, P = 0.214, P = 0.080, P = 0.199). Among them, household income indicated average monthly income per capita.

Table 1.

Characteristics of the subjects in the study.a

  Control  Common case  Severe case  F/H value  P value 
Total (n)  1000  1000  1000  —  — 
Demography data           
Age (months)  48 (42, 54)  49 (43, 54)  49 (42, 55)  0.383  0.826 
Male (n,%)  699  685  676  1.231  0.267 
Han nationality (n,%)  939  925  934  1.546  0.214 
BMI Z-score  1.00 (−0.58, 2.46)  0.91 (−0.58, 2.67)  1.17 (−0.35, 2.84)  5.054  0.080 
Household income (yuan)b  2900 (2000, 3900)  2900 (1900, 3900)  3000 (1800, 3800)  3.225  0.199 
Clinical manifestations           
Hyperpyrexia (n)  —  195  340  53.651  <0.001 
Dehydration (n)  —  155  275  42.660  <0.001 
Diarrhea (n)  —  225  295  12.734  <0.001 
Hypoxemia (n)  —  78  231  89.601  <0.001 
Serological data           
WBC count (× 109/l)  —  12.89 (9.69, 16.06)  12.31 (9.41, 15.93)  2.609  0.106 
High creatinine (n)  —  75  235  97.729  <0.001 
C-reactive protein (mg/l)  —  103.19 (54.18, 161.84)  137.10 (63.03, 198.04)  45.871  <0.001 
Antibiotics           
Cephalosporins  —  865  935  27.222  <0.001 
Macrolides  —  625  490  36.939  <0.001 
Other antibiotics  —  240  475  120.214  <0.001 
Required to change antibiotics  —  310  575  142.332  <0.001 
a

Continuous variables were expressed by medians (25th quartiles, 75th quartiles). The difference of the continuous variables was measured using Kruskal-Wallis H test. Categorical variables were expressed by frequencies. The difference of two categorical variables was measured using Chi-square test, and the difference of three categorical variables was measured by comparing the maximum and minimum values using Chi-square test.

b

Household income indicated average monthly income per capita.

As shown in Table 2, with the exception of Lp-a (P = 0.433), the serum levels of the other lipid metabolic markers differed significantly in the control, common case, and severe case groups (P < 0.001, P <  0.001, P < 0.001, P < 0.001, P < 0.001, P < 0.001, P = 0.014). Briefly, compared with the common case group, the serum levels of TG, TC, LDL-C, and VLDL-C were significantly higher and the serum levels of HDL-C and ApoA1 were significantly lower in the severe case group (P < 0.05). Compared with the control group, the serum level of TC was significantly higher in the common case group (P < 0.05).

Table 2.

Serum levels of lipids, lipoproteins and apolipoproteins in the study.a

  Control  Common case  Severe case  H value  P value 
Total (n)  1000  1000  1000     
TG (mmol/l) b  0.83 (0.66, 0.96)  0.83 (0.67, 0.99)  0.98 (0.76, 1.19) ‡  298.258  <0.001 
TC (mmol/l)  3.49 (2.73, 4.25)  3.63 (2.83, 4.38) †  4.09 (3.26, 4.87) ‡  193.845  <0.001 
LDL-C (mmol/l)  2.01 (1.77, 2.26)  2.03 (1.76, 2.30)  2.19 (1.85, 2.49) ‡  110.759  <0.001 
VLDL-C (mmol/l)  0.33 (0.20, 0.45)  0.33 (0.24, 0.46)  0.39 (0.26, 0.53) ‡  85.380  <0.001 
HDL-C (mmol/l)  1.36 (1.06, 1.67)  1.34 (1.08, 1.60)  1.25 (1.00, 1.49) ‡  66.823  <0.001 
Lp-a (mmol/l)  57.23 (32.77, 84.77)  58.26 (31.32, 87.33)  59.42 (29.99, 88.18)  1.675  0.433 
ApoA1 (g/l)  1.17 (0.87, 1.48)  1.16 (0.88, 1.42)  1.07 (0.84, 1.34) ‡  39.981  <0.001 
ApoB (g/l)  0.47 (0.36, 0.59)  0.48 (0.35, 0.62)  0.48 (0.36, 0.63)  8.524  0.014 
a

The serum levels of lipids, lipoproteins and apolipoproteins were expressed using medians (25th quartiles, 75th quartiles). The difference of these markers was measured using Kruskal-Wallis H test. “†” indicated “compared with control group, P<0.05″; “‡” indicated “compared with common case group, P<0.05″.

b

TG = Triglycerides; TC = Total cholesterol; LDL-C = Low-density lipoprotein cholesterol; VLDL-C = Very low-density lipoprotein cholesterol; HDL-C = High-density lipoprotein cholesterol; ApoA1 = Apolipoprotein A1; ApoB = Apolipoprotein B; Lp-a = Lipoprotein A.

Association of the lipid metabolic markers with the risk of pneumonia

As shown in Table 3, the higher level of TC in serum was associated with the increased risk of common pneumonia (OR = 1.110, 95%CI = 1.014 ∼ 1.214). In addition, the other lipid metabolic markers were not related to the risk of the disease (Table 3).

Table 3.

Association of serum lipids, lipoproteins and apolipoproteins with the risk of common and severe pneumonia.a

Risk of common case  Univariate logistic regressionMultivariate logistic regression
  OR  95%CI  OR  95%CI 
TGb  1.045  0.995 ∼ 1.097  1.046  0.995 ∼ 1.098 
TC  1.109  1.013 ∼ 1.214  1.110  1.014 ∼ 1.214 
LDL-C  1.028  0.999 ∼ 1.059  1.028  0.999 ∼ 1.059 
VLDL-C  1.063  0.996 ∼ 1.134  1.064  0.996 ∼ 1.135 
HDL-C  0.990  0.963 ∼ 1.017  0.992  0.963 ∼ 1.018 
Lp-a  1.011  0.983 ∼ 1.040  1.011  0.984 ∼ 1.040 
ApoA1  0.979  0.953 ∼ 1.007  0.980  0.953 ∼ 1.008 
ApoB  1.039  0.979 ∼ 1.102  1.039  0.979 ∼ 1.103 
Risk of severe case  Univariate logistic regressionMultivariate logistic regression
  OR  95%CI  OR  95%CI 
TG  1.406  1.336 ∼ 1.479  1.407  1.336 ∼ 1.480 
TC  1.946  1.740 ∼ 2.175  1.947  1.741 ∼ 2.175 
LDL-C  1.152  1.116 ∼ 1.188  1.153  1.116 ∼ 1.189 
VLDL-C  1.309  1.221 ∼ 1.403  1.310  1.222 ∼ 1.404 
HDL-C  0.902  0.873 ∼ 0.932  0.903  0.873 ∼ 0.933 
Lp-a  1.011  0.979 ∼ 1.045  1.012  0.979 ∼ 1.046 
ApoA1  0.921  0.891 ∼ 0.951  0.921  0.891 ∼ 0.952 
ApoB  1.074  1.003 ∼ 1.150  1.075  1.003 ∼ 1.151 
a

The association of serum lipids, lipoproteins and apolipoproteins with the risk of common and severe pneumonia was performed by univariate and multivariate logistic regression, and their ORs and 95%CIs were reported. In the multivariate analyses, demography data, clinical manifestations, serological data and antibiotics were adjusted.

b

TG = Triglycerides; TC = Total cholesterol; LDL-C = Low-density lipoprotein cholesterol; VLDL-C = Very low-density lipoprotein cholesterol; HDL-C = High-density lipoprotein cholesterol; ApoA1 = Apolipoprotein A1; ApoB = Apolipoprotein B; Lp-a = Lipoprotein A.

Besides, the higher levels of TG, TC, LDL-C, VLDL-C and ApoB were associated with the elevated risk of severe pneumonia (OR = 1.407, 95%CI = 1.336 ∼ 1.480; OR = 1.947, 95%CI = 1.741 ∼ 2.175; OR = 1.153, 95%CI = 1.116 ∼ 1.189; OR = 1.310, 95%CI = 1.222 ∼ 1.404; OR = 1.075, 95%CI = 1.003 ∼ 1.151). On the contrary, the lower levels of HDL-C and ApoA1 were related to the increased risk of severe pneumonia (OR = 0.903, 95%CI = 0.873 ∼ 0.933; OR = 0.921, 95%CI = 0.891 ∼ 0.952). In addition, the serum of Lp-a was not associated with the risk of the disease (OR = 1.012, 95%CI = 0.979 ∼ 1.046).

Association of the lipid metabolic markers with the risk of hypoxemia

As shown in Table 4, the higher level of TG in serum was associated with the risk of hypoxemia in this group (OR = 1.172, 95%CI = 1.028 ∼ 1.336). However, the serum levels of the other lipid metabolic markers were not related to the risk of hypoxemia in the common case group (Table 4).

Table 4.

Association of serum lipids, lipoproteins and apolipoproteins with the risk of hypoxemia in common and severe case group.a

Risk of hypoxemia in common case  Univariate logistic regressionMultivariate logistic regression
  OR  95%CI  OR  95%CI 
TGb  1.171  1.028 ∼ 1.335  1.172  1.028 ∼ 1.336 
TC  0.982  0.773 ∼ 1.249  0.983  0.774 ∼ 1.249 
LDL-C  1.050  0.976 ∼ 1.130  1.051  0.976 ∼ 1.131 
VLDL-C  1.031  0.859 ∼ 1.237  1.032  0.859 ∼ 1.237 
HDL-C  1.060  0.981 ∼ 1.145  1.060  0.981 ∼ 1.146 
Lp-a  0.992  0.923 ∼ 1.066  0.993  0.923 ∼ 1.066 
ApoA1  1.021  0.946 ∼ 1.103  1.021  0.947 ∼ 1.103 
ApoB  0.971  0.831 ∼ 1.135  0.972  0.831 ∼ 1.136 
Risk of hypoxemia in severe case  Univariate logistic regressionMultivariate logistic regression
  OR  95%CI  OR  95%CI 
TG  1.141  1.072 ∼ 1.214  1.142  1.072 ∼ 1.215 
TC  1.133  0.969 ∼ 1.324  1.134  0.969 ∼ 1.325 
LDL-C  1.004  0.964 ∼ 1.045  1.005  0.965 ∼ 1.046 
VLDL-C  1.033  0.940 ∼ 1.135  1.034  0.940 ∼ 1.135 
HDL-C  1.032  0.979 ∼ 1.087  1.033  0.979 ∼ 1.088 
Lp-a  0.960  0.917 ∼ 1.004  0.961  0.917 ∼ 1.005 
ApoA1  1.013  0.962 ∼ 1.066  1.013  0.963 ∼ 1.066 
ApoB  0.983  0.894 ∼ 1.081  0.984  0.894 ∼ 1.082 
a

The association of serum lipids, lipoproteins and apolipoproteins with the risk of hypoxemia in common and severe case group was performed by univariate and multivariate logistic regression, and their ORs and 95%CIs were reported. In the multivariate analyses, demography data, clinical manifestations, serological data and antibiotics were adjusted.

b

TG = Triglycerides; TC = Total cholesterol; LDL-C = Low-density lipoprotein cholesterol; VLDL-C = Very low-density lipoprotein cholesterol; HDL-C = High-density lipoprotein cholesterol; ApoA1 = Apolipoprotein A1; ApoB = Apolipoprotein B; Lp-a = Lipoprotein A.

Similar to the common case group, only the higher level of TG in serum was relate to the increased risk of hypoxemia in the severe case group (OR = 1.142, 95%CI = 1.072 ∼ 1.215). And the serum levels of the other lipid metabolic markers were not related to the risk of hypoxemia in this group (Table 4).

Linear association of the lipid metabolic markers with serum C-reactive protein

As shown in supplemental Table 1, in the common case group, the serum level of HDL-C was inversely associated with the serum level of C-reactive protein (ρ = −0.097, P = 0.002). In the severe case group, the serum level of HDL-C was also inversely associated with the serum level of C-reactive protein (ρ = −0.343, P < 0.001), and the serum level of TC was positively correlated with the serum level of the inflammatory marker (ρ = 0.064, P = 0.042).

Discussion

As mentioned above, pneumonia is one of the major health challenges in children under 5 years of age, and obesity is another emerging health issue for these children that have become increasingly important in recent years.13,14 And the Han Chinese are the dominant ethnic group in China and are also widely distributed in Southeast Asia, North America and Western Europe, with a population of over 1.2 billion. These two diseases mentioned above also severely affect Han Chinese children.13-15 Therefore, it is of great scientific and practical importance to explore the correlation between lipid metabolism and pneumonia in Han Chinese children of this age group.

Based on the results of this study, the authors found that lipid metabolism was more closely related to severe pneumonia than common pneumonia. For severe pneumonia, the elevated levels of TG, TC, LDL-C, VLDL-C and ApoB were implicated in the increased risk of severe pneumonia by about 7% to 90%, while the elevated levels of HDL-C and ApoA1 were associated with the decreased risk of the disease by about 8% to 10%. For common pneumonia, only one lipid metabolic marker TC was related to the risk of common pneumonia, and the elevated levels of it in serum was related to the increased risk of the disease by 10%. The study did not find any relationship between the other lipid metabolic markers and the risk of common pneumonia. Thus, the present study was partially consistent with the previous study, although it did not cover so many lipid metabolic markers and did not distinguish pneumonia into common and severe groups.8

It is well known that lipid metabolism disorders are often implicated in low-intensity metabolic inflammation in the body.16 In childhood pneumonia, inflammation is also a pathophysiological process that is inextricably linked to the disease progression and prognosis, accompanied by altered levels of numerous inflammatory factors (including CRP). More importantly, the present study confirmed that there was a certain inversely linear relationship between serum HDL and CRP both in the common and severe cases, while serum TC had a positive linear association with serum CRP in the severe cases. Therefore, both the previous knowledge as well as the authors’ findings implied that the correlation between lipid metabolism and childhood pneumonia might be explained by inflammation. However, the exact mechanisms remained unclear and need to be explored in further research.

Hypoxaemia should be a serious clinical manifestation in childhood pneumonia, which is often associated with a fatal prognosis.17 The present study found a correlation between serum TG and hypoxemia both in the common case and severe case groups. Briefly, the higher TG level in serum may suggest an increased risk of hypoxemia by more than 10% in these two groups. In fact, an association between obesity and hypoxemia had long been established in sleep apnea syndrome, and its mechanism was that obesity led to stricture of the respiratory tracts, promoting apnea and hypoxemia.18,19 However, because the present study failed to find any significant difference in obesity (BMI Z-score) levels among all three groups, the relationship between hypoxemia and serum TG should be independent of obesity. Furthermore, both hypoxemia and plasma TG levels in pneumonia were clearly factors associated with inflammation, it was possible that inflammation could be a potential mechanism linking these two factors mentioned above, but future studies were needed to verify this assumption.

In the study, pneumonia was diagnosed primarily based on the WHO criteria. However, cough and difficulty breathing were neither specific nor sensitive symptoms of the disease. So, the pneumonia children included in the study must be supported by the results of chest auscultation or chest x-ray, which increased the accuracy of the diagnosis.

There were two advantages in the present study. First, the inclusion of 3000 children provided a sufficiently large sample size and test power. Second, the data in the study were analyzed at multiple levels. For example, the included children were grouped according to the severity of pneumonia, and a series of lipid metabolic markers were also analyzed separately. This helped the researchers discover more valuable information.

The most significant limitation of this study came from its cross-sectional design. The correlation between obesity and lipid profile was clear. In the present study, the authors did not find any significant differences in obesity levels between the three groups, so pneumonia (especially severe pneumonia) was the most likely factor associated with altered lipid profiles in children. However, due to the lack of reliable longitudinal data, the authors were unable to determine whether altered lipid profiles preceded the onset of pneumonia. After all, pneumonia or other acute inflammatory states can also alter an individual's lipid profile.20 Therefore, the available evidence did not yet support a direct independent pathogenic effect of lipid metabolism on disease severity. Cohort studies as well as Mendelian randomization studies can continue to explore these questions at both phenotypic and genotypic levels, in the expectation that they may provide more definitive conclusions, and the present study could be an important basis for these future studies.

In conclusion, there was a significant relationship between lipid metabolism and severe pneumonia (but not common pneumonia) in under-five children. Briefly, the elevated peripheral concentrations of TG, TC, LDL-C, VLDL-C and ApoB might be related to the increased risk of severe pneumonia, and the elevated peripheral concentrations of HDL-C and ApoA1 might be related to the decreased risk of the disease. Furthermore, the peripheral concentration of TG was associated with the development of hypoxemia both in common and severe pneumonia in these children. In addition, these relationships might be partly explained by inflammation. More studies should be conducted to further validate this conclusion.

Data availability statements

Data can not be shared at present due to this is an ongoing study. When the study was completed, the data will be shared immediately.

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