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This underscores the critical need for epidemiological investigations to elucidate its prevalence&#44; risk factors&#44; and impact on patient outcomes&#46; Previous studies assessing the impact of silent hypoxemia in COVID-19 were based on relatively small sample sizes and may have been underpowered to detect significant risk factors associated with unfavorable clinical outcomes&#46;<a class="elsevierStyleCrossRefs" href="#bib0030"><span class="elsevierStyleSup">6&#8211;11</span></a></p><p id="par0020" class="elsevierStylePara elsevierViewall">In this context&#44; we aimed to describe the clinical characteristics and predictors of mortality in a cohort of patients who were hospitalized for severe acute respiratory syndrome &#40;SARS&#41; due to COVID-19 presenting with silent hypoxemia&#46;</p></span><span id="sec0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0070">Material and methods</span><span id="sec0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0075">Study design&#44; data sources&#44; participants&#44; and measurements</span><p id="par0025" class="elsevierStylePara elsevierViewall">This is an observational retrospective cohort study&#46; We extracted data from the Influenza Epidemiological Surveillance Information System &#40;<span class="elsevierStyleItalic">Sistema de Informa&#231;&#227;o da Vigil&#226;ncia Epidemiol&#243;gica da Gripe</span>&#44; <span class="elsevierStyleItalic">SIVEP-Gripe</span>&#44; in Portuguese&#41;&#44; an information system of the Brazilian Ministry of Health that captures all notifications of hospitalizations due to SARS in Brazil in both public and private&#44; from the Department of Information and Computing of the Brazilian Unified Health System &#40;<span class="elsevierStyleItalic">Departamento de Informa&#231;&#227;o e Inform&#225;tica do Sistema &#218;nico de Sa&#250;de</span>&#44; <span class="elsevierStyleItalic">DATASUS</span>&#44; in Portuguese&#41;&#44; from January 1 to June 18&#44; 2021&#46; Notifications were submitted to the system within 24&#8239;h of initial clinical suspicion or positive laboratory results&#46; SARS was defined as dyspnea&#44; central cyanosis&#44; persistent chest pain or pressure&#44; or peripheral arterial oxygen saturation &#40;SpO<span class="elsevierStyleInf">2</span>&#41; measured by pulse oximetry of &#60;95&#37; in room air&#46;<a class="elsevierStyleCrossRef" href="#bib0060"><span class="elsevierStyleSup">12</span></a></p><p id="par0030" class="elsevierStylePara elsevierViewall">We considered only records of patients with confirmed COVID-19 diagnosis as per the Brazilian Ministry of Health guidelines<a class="elsevierStyleCrossRef" href="#bib0060"><span class="elsevierStyleSup">12</span></a> and silent hypoxemia at presentation&#44; defined as SpO<span class="elsevierStyleInf">2</span> measured by pulse oximetry of &#60;95&#37; without dyspnea&#46; We excluded pregnant patients or patients with unknown pregnancy status and patients with missing data regarding SpO<span class="elsevierStyleInf">2</span>&#46;</p><p id="par0035" class="elsevierStylePara elsevierViewall">Baseline characteristics&#44; such as symptoms&#44; signs&#44; and radiological&#47;computed tomography &#40;CT&#41; findings&#44; were assessed and recorded by the healthcare professionals responsible for patient care at hospital admission&#46; Requirement for respiratory support&#44; admission to the intensive care unit &#40;ICU&#41;&#44; and mortality were evaluated throughout the hospital stay&#46;</p><p id="par0040" class="elsevierStylePara elsevierViewall">This study adheres to the Helsinki Declaration&#8217;s ethical guidelines for research involving human subjects&#46; The Ethics Committee of the Public Health School of Cear&#225; approved this study &#40;reference number 49905921&#46;4&#46;0000&#46;5037&#41;&#46; Patient consent for publication was not required&#44; as data was extracted from a publicly accessible&#44; deidentified repository&#46;</p></span><span id="sec0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0080">Follow-up and outcomes</span><p id="par0045" class="elsevierStylePara elsevierViewall">Patients were followed up during hospitalization&#46; The primary outcome of interest was the occurrence of death&#46;</p></span><span id="sec0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0085">Statistical analyses</span><p id="par0050" class="elsevierStylePara elsevierViewall">Categorical data were expressed as absolute counts and percentages&#46; All &#8203;&#8203;quantitative data were tested for normal distribution using the Kolmogorov&#8211;Smirnov test&#46; Normally distributed data were expressed as mean and standard deviation &#40;SD&#41;&#46;</p><p id="par0055" class="elsevierStylePara elsevierViewall">Proportions for categorical variables were compared using the chi-squared and Fisher&#8217;s exact tests&#44; as appropriate&#46; Means for continuous variables were compared using the Student&#8217;s t-test according to normal distribution&#46;</p><p id="par0060" class="elsevierStylePara elsevierViewall">We then performed a multivariable logistic regression analysis including statistically significant variables in bivariate analysis to identify independent predictors of mortality&#46; The most significant level of the variables for the outcome of interest was investigated using the forward stepwise method&#46; The presence of collinearity between the &#8203;&#8203;independent variables was explored by estimating the tolerance and variance inflation factor before the inclusion of multivariable models&#46;</p><p id="par0065" class="elsevierStylePara elsevierViewall">All analyses were performed with IBM SPSS Statistics for Mac OS&#44; version 23&#46;0 &#40;IBM Corp&#46;&#44; Armonk&#44; N&#46;Y&#46;&#44; USA&#41;&#46; We regarded a <span class="elsevierStyleItalic">P</span> value of &#60;0&#46;05 as statistically significant&#46;</p></span></span><span id="sec0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0090">Results</span><span id="sec0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0095">Clinical characteristics of patient population</span><p id="par0070" class="elsevierStylePara elsevierViewall">A total of 747&#44;926 patients were screened between January and June 2021&#44; and 46&#44;102 patients were included &#40;<a class="elsevierStyleCrossRef" href="#fig0005">Fig&#46; 1</a>&#41;&#46; The mean age was 59&#8239;&#177;&#8239;16 years&#44; 19&#44;204 &#40;41&#46;6&#37;&#41; were female&#44; and 23&#44;428 &#40;50&#46;9&#37;&#41; were White individuals&#46; The predominant comorbidities were chronic cardiovascular disease &#40;14&#44;890 &#91;32&#46;3&#37;&#93;&#41;&#44; diabetes &#40;5717 &#91;12&#46;4&#37;&#93;&#41;&#44; and obesity &#40;1780 &#91;3&#46;9&#37;&#93;&#41;&#46; The most common signs and symptoms during hospitalization were cough &#40;30&#44;951 &#91;67&#46;2&#37;&#93;&#41;&#44; respiratory distress &#40;22&#44;496 &#91;48&#46;8&#37;&#93;&#41;&#44; and fatigue &#40;11&#44;176 &#91;24&#46;2&#37;&#93;&#41;&#46; The main chest imaging findings were interstitial infiltrates &#40;6467 &#91;14&#37;&#93;&#41; and typical COVID-19 pneumonia &#40;22&#44;390 &#91;48&#46;6&#37;&#93;&#41; on radiographs and CT scans&#44; respectively&#46; Most patients needed ventilatory support&#44; with 30&#44;413 &#40;66&#37;&#41; non-invasive support and 7762 &#40;16&#46;8&#37;&#41; requiring invasive support&#46; Additionally&#44; 13&#44;428 &#40;29&#46;1&#37;&#41; of patients were admitted to the ICU&#46;</p><elsevierMultimedia ident="fig0005"></elsevierMultimedia></span><span id="sec0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0100">Primary outcome</span><p id="par0075" class="elsevierStylePara elsevierViewall">The main outcome occurred in 13&#44;149 &#40;28&#46;5&#37;&#41; patients by the end of the follow-up period&#46;</p></span><span id="sec0045" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0105">Univariable analyses</span><p id="par0080" class="elsevierStylePara elsevierViewall"><a class="elsevierStyleCrossRefs" href="#tbl0005">Tables 1 and 2</a> show epidemiological&#44; demographic&#44; clinical&#44; radiological&#44; and treatment data stratified by the presence of the primary outcome&#46;</p><elsevierMultimedia ident="tbl0005"></elsevierMultimedia><elsevierMultimedia ident="tbl0010"></elsevierMultimedia><p id="par0085" class="elsevierStylePara elsevierViewall">Compared with patients who survived&#44; patients who died were characterized by advanced age &#40;mean age&#44; 66 &#91;SD&#44; 15&#93; <span class="elsevierStyleItalic">vs&#46;</span> 56 years &#91;SD&#44; 16&#93;&#59; <span class="elsevierStyleItalic">P</span>&#8239;&#60;&#8239;0&#46;001&#41;&#44; less frequently female sex &#40;43&#46;6&#37; female <span class="elsevierStyleItalic">vs&#46;</span> 56&#46;4&#37; male&#59; <span class="elsevierStyleItalic">P</span>&#8239;&#60;&#8239;0&#46;001&#41;&#44; and predominantly black &#40;6&#46;1&#37; <span class="elsevierStyleItalic">vs&#46;</span> 4&#46;8&#37;&#59; <span class="elsevierStyleItalic">P</span>&#8239;&#60;&#8239;0&#46;001&#41; ethnic-racial group&#46; Proportionately&#44; black and brown individuals had higher mortality rates &#40;53&#46;3&#37; and 41&#46;4&#37;&#44; respectively&#41;&#46;</p><p id="par0090" class="elsevierStylePara elsevierViewall">Patients who died were significantly more likely to have one or more coexisting medical conditions compared to those who survived &#40;74&#46;3&#37; <span class="elsevierStyleItalic">vs&#46;</span> 56&#46;8&#37;&#59; <span class="elsevierStyleItalic">P</span>&#8239;&#60;&#8239;0&#46;001&#41;&#46; Of those comorbidities&#44; chronic cardiovascular disease &#40;40&#46;8&#37; <span class="elsevierStyleItalic">vs&#46;</span> 28&#46;9&#37;&#59; <span class="elsevierStyleItalic">P</span>&#8239;&#60;&#8239;0&#46;001&#41;&#44; chronic hematologic disease &#40;0&#46;4&#37; <span class="elsevierStyleItalic">vs&#46;</span> 0&#46;2&#37;&#59; <span class="elsevierStyleItalic">P</span>&#8239;&#60;&#8239;0&#46;001&#41;&#44; chronic neurological disease &#40;6&#37; <span class="elsevierStyleItalic">vs&#46;</span> 2&#46;7&#37;&#59; <span class="elsevierStyleItalic">P</span>&#8239;&#60;&#8239;0&#46;001&#41;&#44; chronic hepatic disease &#40;0&#46;5&#37; <span class="elsevierStyleItalic">vs&#46;</span> 0&#46;2&#37;&#59; <span class="elsevierStyleItalic">P</span>&#8239;&#60;&#8239;0&#46;001&#41;&#44; chronic lung disease &#40;2&#46;3&#37; <span class="elsevierStyleItalic">vs&#46;</span> 0&#46;9&#37;&#59; <span class="elsevierStyleItalic">P</span>&#8239;&#60;&#8239;0&#46;001&#41;&#44; chronic kidney disease &#40;5&#46;4&#37; <span class="elsevierStyleItalic">vs&#46;</span> 2&#37;&#59; <span class="elsevierStyleItalic">P</span>&#8239;&#60;&#8239;0&#46;001&#41;&#44; diabetes &#40;17&#46;4&#37; <span class="elsevierStyleItalic">vs&#46;</span> 10&#46;4&#37;&#59; <span class="elsevierStyleItalic">P</span>&#8239;&#60;&#8239;0&#46;001&#41;&#44; immunodeficiency &#40;1&#46;2&#37; <span class="elsevierStyleItalic">vs&#46;</span> 0&#46;5&#37;&#59; <span class="elsevierStyleItalic">P</span>&#8239;&#60;&#8239;0&#46;001&#41;&#44; and obesity &#40;5&#46;4&#37; <span class="elsevierStyleItalic">vs&#46;</span> 3&#46;3&#37;&#59; <span class="elsevierStyleItalic">P</span>&#8239;&#60;&#8239;0&#46;001&#41; were significantly associated with mortality&#46;</p><p id="par0095" class="elsevierStylePara elsevierViewall">Regarding the influenza vaccination status&#44; deceased patients had significantly higher rates of up-to-date vaccination &#40;23&#46;2&#37; <span class="elsevierStyleItalic">vs&#46;</span> 21&#46;4&#37;&#59; <span class="elsevierStyleItalic">P</span>&#8239;&#61;&#8239;0&#46;002&#41; compared to survivors&#46;</p><p id="par0100" class="elsevierStylePara elsevierViewall">During hospitalization&#44; patients who died presented significantly higher rates of respiratory distress &#40;52&#46;8&#37; <span class="elsevierStyleItalic">vs&#46;</span> 47&#46;6&#37;&#59; <span class="elsevierStyleItalic">P</span>&#8239;&#60;&#8239;0&#46;001&#41; compared to those who survived&#46; However&#44; anosmia &#40;7&#46;7&#37; <span class="elsevierStyleItalic">vs&#46;</span> 12&#46;2&#37;&#59; <span class="elsevierStyleItalic">P</span>&#8239;&#60;&#8239;0&#46;001&#41;&#44; cough &#40;60&#46;9&#37; <span class="elsevierStyleItalic">vs&#46;</span> 70&#37;&#59; <span class="elsevierStyleItalic">P</span>&#8239;&#60;&#8239;0&#46;001&#41;&#44; diarrhea &#40;14&#46;9&#37; <span class="elsevierStyleItalic">vs&#46;</span> 17&#46;7&#37;&#59; <span class="elsevierStyleItalic">P</span>&#8239;&#60;&#8239;0&#46;001&#41;&#44; dysgeusia &#40;8&#46;7&#37; <span class="elsevierStyleItalic">vs&#46;</span> 13&#37;&#59; <span class="elsevierStyleItalic">P</span>&#8239;&#60;&#8239;0&#46;001&#41;&#44; fatigue &#40;21&#46;9&#37; <span class="elsevierStyleItalic">vs&#46;</span> 25&#46;9&#37;&#59; <span class="elsevierStyleItalic">P</span>&#8239;&#60;&#8239;0&#46;001&#41;&#44; and sore throat &#40;13&#46;2&#37; <span class="elsevierStyleItalic">vs&#46;</span> 16&#46;6&#37;&#59; <span class="elsevierStyleItalic">P</span>&#8239;&#60;&#8239;0&#46;001&#41; were significantly less frequent&#46;</p><p id="par0105" class="elsevierStylePara elsevierViewall">In comparison to survivors&#44; non-survivors were significantly less likely to exhibit changes in chest imaging studies&#44; except for the typical COVID-19 pattern &#40;61&#37; <span class="elsevierStyleItalic">vs&#46;</span> 67&#46;1&#37;&#59; P&#8239;&#60;&#8239;0&#46;001&#41;&#46; However&#44; a substantial proportion of patients did not undergo chest imaging &#40;39&#46;7&#37; for radiographs and 18&#46;6&#37; for chest CT scans&#41;&#46;</p><p id="par0110" class="elsevierStylePara elsevierViewall">Concerning respiratory support&#44; non-survivors had a significantly higher need for invasive mechanical ventilation &#40;42&#46;4&#37; <span class="elsevierStyleItalic">vs&#46;</span> 6&#46;6&#37;&#59; <span class="elsevierStyleItalic">P</span>&#8239;&#60;&#8239;0&#46;001&#41; compared to survivors&#46; In contrast&#44; no respiratory support &#40;8&#46;7&#37; <span class="elsevierStyleItalic">vs&#46;</span> 20&#46;6&#37;&#59; <span class="elsevierStyleItalic">P</span>&#8239;&#60;&#8239;0&#46;001&#41; and the need for non-invasive respiratory support &#40;48&#46;9&#37; <span class="elsevierStyleItalic">vs&#46;</span> 72&#46;8&#37;&#59; <span class="elsevierStyleItalic">P</span>&#8239;&#60;&#8239;0&#46;001&#41; were significantly less likely among non-survivors&#46;</p><p id="par0115" class="elsevierStylePara elsevierViewall">Finally&#44; ICU admission was significantly associated with mortality &#40;56&#46;9&#37; <span class="elsevierStyleItalic">vs&#46;</span> 20&#37;&#59; <span class="elsevierStyleItalic">P</span>&#8239;&#60;&#8239;0&#46;001&#41;&#46;</p></span><span id="sec0050" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0110">Multivariable analyses</span><p id="par0120" class="elsevierStylePara elsevierViewall">In the multivariable analysis &#40;<a class="elsevierStyleCrossRef" href="#tbl0015">Table 3</a>&#41;&#44; advanced age &#40;odd ratio &#91;OR&#93; 1&#46;04&#59; 95&#37; confidence interval &#91;CI&#93; 1&#46;037&#8211;1&#46;04&#59; <span class="elsevierStyleItalic">P</span>&#8239;&#60;&#8239;0&#46;001&#41;&#44; presence of comorbidities &#40;OR 1&#46;54&#59; 95&#37;CI 1&#46;47&#8211;1&#46;62&#59; <span class="elsevierStyleItalic">P</span>&#8239;&#60;&#8239;0&#46;001&#41;&#44; cough &#40;OR 0&#46;74&#59; 95&#37;CI 0&#46;71&#8211;0&#46;79&#59; <span class="elsevierStyleItalic">P</span>&#8239;&#60;&#8239;0&#46;001&#41;&#44; respiratory distress &#40;OR 1&#46;32&#59; 95&#37;CI 1&#46;26&#8211;1&#46;38&#59; <span class="elsevierStyleItalic">P</span>&#8239;&#60;&#8239;0&#46;001&#41;&#44; and need for non-invasive respiratory support &#40;OR 0&#46;37&#59; 95&#37;CI 0&#46;35&#8211;0&#46;40&#59; <span class="elsevierStyleItalic">P</span>&#8239;&#60;&#8239;0&#46;001&#41; remained independently associated with death&#46;</p><elsevierMultimedia ident="tbl0015"></elsevierMultimedia></span></span><span id="sec0055" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0115">Discussion</span><p id="par0125" class="elsevierStylePara elsevierViewall">This retrospective cohort study evaluated the clinical characteristics and predictors of death in hospitalized patients due to SARS from COVID-19 who presented with silent hypoxemia at admission&#46; Our main findings were that &#40;I&#41; advanced age&#44; presence of comorbidities&#44; and development of respiratory distress were independent risk factors for mortality&#44; while &#40;II&#41; development of cough and need for non-invasive respiratory support were independent protective factors against mortality&#46;</p><p id="par0130" class="elsevierStylePara elsevierViewall">Several mechanisms have been proposed to explain silent hypoxemia in COVID-19&#46; Gattinoni et al&#46; proposed two primary &#8220;phenotypes&#8221;&#58; types L and H&#46; Type L&#44; characterized by low elastance and reduced ventilation-to-perfusion &#40;V&#47;Q&#41; ratio&#44; results from viral-induced local interstitial edema and vasoplegia&#46;<a class="elsevierStyleCrossRefs" href="#bib0065"><span class="elsevierStyleSup">13&#8211;15</span></a> Patients with the type L lack dyspnea due to near-normal compliance&#46;<a class="elsevierStyleCrossRefs" href="#bib0080"><span class="elsevierStyleSup">16&#8211;19</span></a> Transition to the type H&#44; driven by heightened COVID-19 severity and inflammation&#44; may induce dyspnea through patient self-inflicted lung injury &#40;P-SILI&#41;&#46;<a class="elsevierStyleCrossRefs" href="#bib0065"><span class="elsevierStyleSup">13&#44;20</span></a> This mirrors the conditions observed in acute respiratory distress syndrome&#46;<a class="elsevierStyleCrossRefs" href="#bib0080"><span class="elsevierStyleSup">16&#44;21&#44;22</span></a></p><p id="par0135" class="elsevierStylePara elsevierViewall">In COVID-19&#44; the absence of dyspnea may be attributed to direct viral damage to the carotid bodies and solitary tract&#44; as the glomus cells of the carotid body exhibit high expression levels of the SARS-CoV-2 receptor&#44; angiotensin-converting enzyme-2&#46;<a class="elsevierStyleCrossRefs" href="#bib0035"><span class="elsevierStyleSup">7&#44;18&#44;19&#44;23&#8211;26</span></a> Acute vascular distress syndrome &#40;AVDS&#41;&#44; resulting from endothelial dysfunction&#44; microthrombi formation in the pulmonary vasculature&#44; and vascular proliferation in the lungs&#44; causes an elevated pulmonary vascular flow&#44; leading to a significant intrapulmonary right-to-left shunt&#46;<a class="elsevierStyleCrossRefs" href="#bib0135"><span class="elsevierStyleSup">27&#44;28</span></a> Additionally&#44; variability of the hypoxic ventilatory response across different populations not only explains the high prevalence of silent hypoxemia but also suggests that this phenomenon could be present in other causes of hypoxia&#44; such as influenza pneumonia&#44; among others &#40;<a class="elsevierStyleCrossRef" href="#fig0010">Fig&#46; 2</a>&#41;&#46;<a class="elsevierStyleCrossRef" href="#bib0080"><span class="elsevierStyleSup">16</span></a></p><elsevierMultimedia ident="fig0010"></elsevierMultimedia><p id="par0140" class="elsevierStylePara elsevierViewall">To our knowledge&#44; this study is the largest cohort of silent hypoxemia in COVID-19 to date&#46; Advanced age and the presence of comorbidities emerged as significant independent predictors of adverse outcomes&#44; aligning with prior research&#46; Remarkably&#44; a comprehensive meta-analysis assessing the isolated effect of age on the risk of severe outcomes among COVID-19 patients&#44; the risks of hospitalization&#44; in-hospital mortality&#44; and overall mortality increased by 3&#46;4&#37;&#44; 5&#46;7&#37;&#44; and 7&#46;4&#37; per age year&#44; respectively&#46; These outcomes underscore the continuous age-related increase in susceptibility to adverse events associated with SARS-CoV-2 infection&#46;<a class="elsevierStyleCrossRefs" href="#bib0005"><span class="elsevierStyleSup">1&#44;3&#44;29&#8211;32</span></a> Moreover&#44; the association of comorbid conditions&#44; such as cardiovascular disease&#44; diabetes&#44; and obesity&#44; with severe COVID-19 emphasizes the importance of considering the underlying health status in risk stratification and clinical management strategies for patients with silent hypoxemia&#46;<a class="elsevierStyleCrossRefs" href="#bib0165"><span class="elsevierStyleSup">33&#8211;35</span></a></p><p id="par0145" class="elsevierStylePara elsevierViewall">In our cohort&#44; survivors were generally more symptomatic&#44; experiencing a range of symptoms including anosmia&#44; cough&#44; diarrhea&#44; dysgeusia&#44; fatigue&#44; and sore throat&#46; These symptoms may have prompted patients to seek medical care earlier in the disease course&#59; thereby&#44; increasing the likelihood of receiving timely respiratory support&#46; This prompt intervention could have contributed to diminishing P-SILI&#44; attenuating the severity of respiratory compromise and ultimately improving patient outcomes&#46;</p><p id="par0150" class="elsevierStylePara elsevierViewall">Notably&#44; the development of cough and the need for non-invasive respiratory support emerge as protective factors against mortality&#46; These results underscore the significance of early identification of hypoxemic patients&#46; Timely recognition of symptoms like cough and prompt initiation of appropriate respiratory support measures could significantly improve patient outcomes and reduce mortality rates in COVID-19&#46;</p><p id="par0155" class="elsevierStylePara elsevierViewall">In a meta-analysis investigating the prevalence and outcomes of COVID-19 patients with silent hypoxia&#44; Bepouka et al&#46; demonstrated a mortality rate ranging from 1&#37; to 45&#46;4&#37;&#44; with a pooled mortality of 2&#37;&#46;<a class="elsevierStyleCrossRef" href="#bib0180"><span class="elsevierStyleSup">36</span></a> In our cohort&#44; the mortality was notably higher at 28&#46;5&#37;&#46; This disparity may stem from variations in patient demographics&#44; disease severity&#44; healthcare systems&#44; and definitions of silent hypoxemia across studies&#46;</p><p id="par0160" class="elsevierStylePara elsevierViewall">Among non-dyspneic COVID-19 patients&#44; approximately one-third may manifest hypoxemia upon admission&#44; marking them as a subset of severe cases requiring early identification&#46;<a class="elsevierStyleCrossRefs" href="#bib0185"><span class="elsevierStyleSup">37&#44;38</span></a> Pulse oximetry emerges as a pivotal tool in this context&#44; offering a simple&#44; non-invasive&#44; and widely accessible means of assessing arterial oxygen saturation&#46;<a class="elsevierStyleCrossRefs" href="#bib0195"><span class="elsevierStyleSup">39&#44;40</span></a> Despite potential confounding factors&#44; such as racial bias&#44; vasoconstriction&#44; hypoxemia&#44; and COVID-19 itself&#44; which may impact the accuracy of SpO<span class="elsevierStyleInf">2</span> measurement and the correlation between SpO<span class="elsevierStyleInf">2</span> and arterial oxygenation&#44; the integration of pulse oximeters is crucial for screening COVID-19 patients&#46;<a class="elsevierStyleCrossRefs" href="#bib0205"><span class="elsevierStyleSup">41&#44;42</span></a> In this specific group of non-dyspneic patients&#44; the initial assessment of SpO<span class="elsevierStyleInf">2</span> through pulse oximetry holds particular significance&#44; enabling the early detection of asymptomatic hypoxia&#44; facilitating timely intervention&#44; and ultimately enhancing outcomes&#46;<a class="elsevierStyleCrossRefs" href="#bib0185"><span class="elsevierStyleSup">37&#44;43&#44;44</span></a> Additionally&#44; clinical evaluations should emphasize monitoring the progression of signs and symptoms&#44; especially the respiratory rate&#44; to promptly identify any deterioration&#46;<a class="elsevierStyleCrossRefs" href="#bib0080"><span class="elsevierStyleSup">16&#44;45</span></a> This comprehensive approach ensures a proactive and effective management strategy for this specific cohort&#44; contributing to enhanced patient care and better overall prognosis&#46;</p><p id="par0165" class="elsevierStylePara elsevierViewall">Regarding screening for the severity of disease in the outpatient setting&#44; it is clear that the sole utilization of patient-reported symptoms would not be an accurate and thorough strategy due to the existence of non-dyspneic hypoxemic presentations&#46; This should warrant the utilization of more objective criteria&#44; including arterial blood gas and pulse oximetry&#46; Based on these findings&#44; we suggest that when feasible patients with COVID-19 should undergo timely screening of hypoxemia&#44; regardless of symptomology&#44; with pulse oximetry to assess for silent hypoxemia and consequent need for respiratory support and pharmacological treatments available&#46;</p><p id="par0170" class="elsevierStylePara elsevierViewall">When providing respiratory support to patients with silent hypoxemia &#8211; believed to be associated with the type L phenotype &#8211;&#44; the primary focus should be on preventing P-SILI and increasing the fraction of inspired oxygen&#46; Implementing an early strategy of providing respiratory support for these patients could have the potential to reduce the risk of P-SILI&#44; and&#44; consequently&#44; mitigate disease progression&#46;</p></span><span id="sec0060" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0120">Limitations</span><p id="par0175" class="elsevierStylePara elsevierViewall">This study has limitations&#46; First&#44; we used administrative records from structured surveillance forms&#44; which may carry inherent limitations due to their reliance on predefined categories and standardized data entry&#46; Second&#44; not all cases of COVID-19 are notified in Brazil&#46; The underreporting could impact the generalizability of the study results&#46; Third&#44; patients with missing data regarding SpO<span class="elsevierStyleInf">2</span> and the presence of dyspnea or respiratory distress at hospital admission were excluded from the analysis&#46; Fourth&#44; since our study was conducted in early 2021&#44; patients with the Omicron variant and its sublineages were unlikely to be included&#46; Thus&#44; further research specifically including patients infected with these variants is essential&#46; Fifth&#44; the absence of available data on laboratory results&#44; including arterial blood gas&#44; which could be used to analyze better blood gas alterations that could potentially interfere with clinical courses such as hypo and hypercapnia&#44; limited our considerations&#46; Sixth&#44; the limited data on time from the symptom onset to the initial presentation and duration of follow-up hinders precise assessment of patient clinical evolution and the impact of delayed medical intervention&#46; Thus&#44; more studies with comprehensive time-related data are warranted to further elucidate the clinical course of silent hypoxemia in COVID-19&#46;</p></span><span id="sec0065" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0125">Conclusions</span><p id="par0180" class="elsevierStylePara elsevierViewall">In this multicenter cohort study of 46&#44;102 hospitalized patients due to SARS due to COVID-19 with silent hypoxemia at presentation in Brazil&#44; advanced age&#44; presence of comorbidities&#44; and development of respiratory distress were independent risk factors for mortality&#46; Conversely&#44; the emergence of cough and the requirement for non-invasive respiratory support were independent protective factors against mortality&#46;</p></span><span id="sec0070" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0130">Funding</span><p id="par0185" class="elsevierStylePara elsevierViewall">This study was sponsored by the Brazilian Council for Scientific and Technological Development &#40;<span class="elsevierStyleItalic">Conselho Nacional de Desenvolvimento Cient&#237;fico e Tecnol&#243;gico&#44;</span><span class="elsevierStyleGrantSponsor" id="gs0005"><span class="elsevierStyleItalic">CNPq</span></span>&#44; in Portuguese&#41; and by the Coordination of Improvement of Higher Education Personnel &#40;<span class="elsevierStyleItalic">Coordena&#231;&#227;o de Aperfei&#231;oamento de Pessoal de N&#237;vel</span> Superior&#44; <span class="elsevierStyleGrantSponsor" id="gs0010">CAPES</span>&#44; in Portuguese&#41;&#46; The funding sources did not participate in study design&#59; collection&#44; management&#44; analysis&#44; and interpretation of data&#59; and preparation&#44; review&#44; and approval of this manuscript&#46;</p></span><span id="sec0075" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0135">Conflicts of interest</span><p id="par0190" class="elsevierStylePara elsevierViewall">The authors have declared no conflicts of interest&#46;</p></span><span id="sec0080" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0140">Data availability statement</span><p id="par0195" class="elsevierStylePara elsevierViewall">All data relevant to the study are included in the article or uploaded as supplementary information&#46;</p></span></span>"
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    "fechaRecibido" => "2024-01-19"
    "fechaAceptado" => "2024-06-02"
    "PalabrasClave" => array:2 [
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        0 => array:4 [
          "clase" => "keyword"
          "titulo" => "Keywords"
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          "palabras" => array:6 [
            0 => "COVID-19"
            1 => "Hypoxia"
            2 => "Mortality"
            3 => "Predictor"
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            0 => "COVID-19"
            1 => "Hipoxia"
            2 => "Mortalidad"
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      "en" => array:3 [
        "titulo" => "Abstract"
        "resumen" => "<span id="abst0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0010">Objective</span><p id="spar0080" class="elsevierStyleSimplePara elsevierViewall">To describe the predictors of mortality in hospitalized patients with severe acute respiratory syndrome &#40;SARS&#41; due to COVID-19 presenting with silent hypoxemia&#46;</p></span> <span id="abst0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0015">Material and methods</span><p id="spar0085" class="elsevierStyleSimplePara elsevierViewall">Retrospective cohort study of hospitalized patients with SARS due to COVID-19 and silent hypoxemia at admission&#44; in Brazil&#44; from January to June 2021&#46; The primary outcome of interest was in-hospital death&#46; Multivariable logistic regression analysis was performed&#46;</p></span> <span id="abst0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0020">Results</span><p id="spar0090" class="elsevierStyleSimplePara elsevierViewall">Of 46&#44;102 patients&#44; the mean age was 59&#8239;&#177;&#8239;16 years&#44; and 41&#46;6&#37; were female&#46; During hospitalization&#44; 13&#44;149 patients died&#46; Compared to survivors&#44; non-survivors were older &#40;mean age&#44; 66 <span class="elsevierStyleItalic">vs&#46;</span> 56 years&#59; <span class="elsevierStyleItalic">P</span>&#8239;&#60;&#8239;0&#46;001&#41;&#44; less frequently female &#40;43&#46;6&#37; <span class="elsevierStyleItalic">vs&#46;</span> 40&#46;9&#37;&#59; <span class="elsevierStyleItalic">P</span>&#8239;&#60;&#8239;0&#46;001&#41;&#44; and more likely to have comorbidities &#40;74&#46;3&#37; <span class="elsevierStyleItalic">vs&#46;</span> 56&#46;8&#37;&#59; <span class="elsevierStyleItalic">P</span>&#8239;&#60;&#8239;0&#46;001&#41;&#46; Non-survivors had higher needs for invasive mechanical ventilation &#40;42&#46;4&#37; <span class="elsevierStyleItalic">vs&#46;</span> 6&#46;6&#37;&#59; <span class="elsevierStyleItalic">P</span>&#8239;&#60;&#8239;0&#46;001&#41; and intensive care unit admission &#40;56&#46;9&#37; <span class="elsevierStyleItalic">vs&#46;</span> 20&#37;&#59; <span class="elsevierStyleItalic">P</span>&#8239;&#60;&#8239;0&#46;001&#41; compared to survivors&#46; In the multivariable regression analysis&#44; advanced age &#40;OR 1&#46;04&#59; 95&#37;CI 1&#46;037&#8211;1&#46;04&#41;&#44; presence of comorbidities &#40;OR 1&#46;54&#59; 95&#37;CI 1&#46;47&#8211;1&#46;62&#41;&#44; cough &#40;OR 0&#46;74&#59; 95&#37;CI 0&#46;71&#8211;0&#46;79&#41;&#44; respiratory distress &#40;OR 1&#46;32&#59; 95&#37;CI 1&#46;26&#8211;1&#46;38&#41;&#44; and need for non-invasive respiratory support &#40;OR 0&#46;37&#59; 95&#37;CI 0&#46;35&#8211;0&#46;40&#41; remained independently associated with death&#46;</p></span> <span id="abst0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0025">Conclusions</span><p id="spar0095" class="elsevierStyleSimplePara elsevierViewall">Advanced age&#44; presence of comorbidities&#44; and respiratory distress were independent risk factors for mortality&#44; while cough and requirement for non-invasive respiratory support were independent protective factors against mortality in hospitalized patients due to SARS due to COVID-19 with silent hypoxemia at presentation&#46;</p></span>"
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            "titulo" => "Material and methods"
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        "resumen" => "<span id="abst0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0035">Objetivo</span><p id="spar0100" class="elsevierStyleSimplePara elsevierViewall">Describir los predictores de mortalidad en pacientes hospitalizados con s&#237;ndrome respiratorio agudo severo &#40;SARS&#41; debido a COVID-19 que presentan hipoxemia silente&#46;</p></span> <span id="abst0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0040">Material y m&#233;todos</span><p id="spar0105" class="elsevierStyleSimplePara elsevierViewall">Estudio de cohorte retrospectivo de pacientes hospitalizados con SARS debido a COVID-19 y hipoxemia silente al ingreso&#44; en Brasil&#44; de enero a junio de 2021&#46; El resultado principal de inter&#233;s fue la muerte intrahospitalaria&#46; Se realiz&#243; un an&#225;lisis de regresi&#243;n log&#237;stica multivariable&#46;</p></span> <span id="abst0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0045">Resultados</span><p id="spar0110" class="elsevierStyleSimplePara elsevierViewall">De 46&#44;102 pacientes&#44; la edad media fue de 59&#8239;&#177;&#8239;16 a&#241;os y el 41&#46;6&#37; eran mujeres&#46; Durante la hospitalizaci&#243;n&#44; fallecieron 13&#44;149 pacientes&#46; En comparaci&#243;n con los sobrevivientes&#44; los no sobrevivientes eran de mayor edad &#40;edad media&#44; 66 vs&#46; 56 a&#241;os&#59; P&#8239;&#60;&#8239;0&#46;001&#41;&#44; menos frecuentemente mujeres &#40;43&#46;6&#37; hombres vs&#46; 40&#46;9&#37;&#59; P&#8239;&#60;&#8239;0&#46;001&#41; y m&#225;s propensos a tener comorbilidades &#40;74&#46;3&#37; vs&#46; 56&#46;8&#37;&#59; P&#8239;&#60;&#8239;0&#46;001&#41;&#46; Los no sobrevivientes tuvieron mayores necesidades de ventilaci&#243;n mec&#225;nica invasiva &#40;42&#46;4&#37; vs&#46; 6&#46;6&#37;&#59; P&#8239;&#60;&#8239;0&#46;001&#41; y admisi&#243;n a la unidad de cuidados intensivos &#40;56&#46;9&#37; vs&#46; 20&#37;&#59; P&#8239;&#60;&#8239;0&#46;001&#41; en comparaci&#243;n con los sobrevivientes&#46; En el an&#225;lisis de regresi&#243;n multivariable&#44; la edad avanzada &#40;OR 1&#46;04&#59; IC del 95&#37; 1&#46;037&#8211;1&#46;04&#41;&#44; la presencia de comorbilidades &#40;OR 1&#46;54&#59; IC del 95&#37; 1&#46;47&#8211;1&#46;62&#41;&#44; la tos &#40;OR 0&#46;74&#59; IC del 95&#37; 0&#46;71&#8211;0&#46;79&#41;&#44; la dificultad respiratoria &#40;OR 1&#46;32&#59; IC del 95&#37; 1&#46;26&#8211;1&#46;38&#41; y la necesidad de soporte respiratorio no invasivo &#40;OR 0&#46;37&#59; IC del 95&#37; 0&#46;35&#8211;0&#46;40&#41; permanecieron independientemente asociadas con la muerte&#46;</p></span> <span id="abst0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0050">Conclusiones</span><p id="spar0115" class="elsevierStyleSimplePara elsevierViewall">La edad avanzada&#44; la presencia de comorbilidades y la dificultad respiratoria fueron factores de riesgo independientes para la mortalidad&#44; mientras que la tos y la necesidad de soporte respiratorio no invasivo fueron factores protectores independientes contra la mortalidad en pacientes hospitalizados debido a SARS debido a COVID-19 con hipoxemia silente en la presentaci&#243;n&#46;</p></span>"
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          "en" => "<p id="spar0015" class="elsevierStyleSimplePara elsevierViewall">Proposed mechanisms of silent hypoxia in COVID-19&#46;</p> <p id="spar1010" class="elsevierStyleSimplePara elsevierViewall">&#40;A&#41; Direct viral infection of the carotid bodies and central nervous system may reduce the perception of dyspnea mediated by chemoreceptors&#46; &#40;B&#41; Endothelial cell dysfunction can precipitate acute vascular distress syndrome&#46; This fosters the formation of microthrombi within the pulmonary vasculature &#40;C&#41; and induces vascular proliferation in the lungs&#46; Consequently&#44; this cascade can culminate in the development of intrapulmonary right-to-left shunt &#40;D&#41;&#46; &#40;E&#41; Loss of lung perfusion regulation and hypoxic vasoconstriction might also contribute to right-to-left shunt &#40;D&#41;&#46; &#40;F&#41; Respiratory alkalosis and hypocapnia blunt both ventilatory stimuli and sensation of dyspnea&#46;</p> <p id="spar0020" class="elsevierStyleSimplePara elsevierViewall"><span class="elsevierStyleItalic">Abbreviation</span>&#58; P-SILI&#44; patient self-inflicted lung injury&#46;</p>"
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          "leyenda" => "<p id="spar0030" class="elsevierStyleSimplePara elsevierViewall">Categorical data are expressed as absolute count &#40;percentages&#41;&#46; Quantitative data are expressed as mean&#8239;&#177;&#8239;standard deviation&#46;</p><p id="spar0035" class="elsevierStyleSimplePara elsevierViewall"><span class="elsevierStyleItalic">Abbreviation</span>&#58; SD&#44; standard deviation&#46;</p>"
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">706 &#40;6&#46;1&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">1325 &#40;4&#46;8&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Brown&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">13&#44;541 &#40;29&#46;4&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">3965 &#40;34&#46;1&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">9576 &#40;34&#46;4&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Indigenous&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">56 &#40;0&#46;1&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">16 &#40;0&#46;1&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">40 &#40;0&#46;1&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>White&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">23&#44;468 &#40;50&#46;9&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">6829 &#40;58&#46;8&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">16&#44;639 &#40;59&#46;7&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleBold">Comorbidity&#44; <span class="elsevierStyleItalic">n</span> &#40;&#37;&#41;</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">28&#44;492 &#40;61&#46;8&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">9770 &#40;74&#46;3&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">18&#44;722 &#40;56&#46;8&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Asthma&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">341 &#40;0&#46;07&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">123 &#40;0&#46;9&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">218 &#40;0&#46;7&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#46;002&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Chronic cardiovascular disease&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">14&#44;890 &#40;32&#46;3&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">5369 &#40;40&#46;8&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">9521 &#40;28&#46;9&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Chronic hematologic disease&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">128 &#40;0&#46;3&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">57 &#40;0&#46;4&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">71 &#40;0&#46;2&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Chronic hepatic disease&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">134 &#40;0&#46;3&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">68 &#40;0&#46;5&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">66 &#40;0&#46;2&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Chronic lung disease&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">612 &#40;1&#46;3&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">301 &#40;2&#46;3&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">311 &#40;0&#46;9&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Chronic neurological disease&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">1686 &#40;3&#46;6&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">784 &#40;6&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">902 &#40;2&#46;7&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Chronic renal disease&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">1371 &#40;3&#46;0&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">711 &#40;5&#44;4&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">660 &#40;2&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Diabetes&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">5717 &#40;12&#46;4&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">2284 &#40;17&#46;4&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">3433 &#40;10&#46;4&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Down syndrome&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">55 &#40;0&#46;1&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">19 &#40;0&#46;1&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">36 &#40;0&#46;1&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#46;322&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Vomiting&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">4623 &#40;10&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">1181 &#40;9&#46;1&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">3442 &#40;10&#46;6&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " colspan="5" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleBold">Chest radiograph findings&#44; <span class="elsevierStyleItalic">n</span> &#40;&#37;&#41;</span></td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Consolidation&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">626 &#40;1&#46;3&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">274 &#40;3&#46;3&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">352 &#40;1&#46;7&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Interstitial infiltrates&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">6467 &#40;14&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">1985 &#40;23&#46;6&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">4482 &#40;21&#46;5&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Mixed pattern&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">725 &#40;1&#46;6&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">249 &#40;3&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">476 &#40;2&#46;3&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Normal&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">907 &#40;2&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">266 &#40;3&#46;2&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">641 &#40;3&#46;1&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Other&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">2250 &#40;4&#46;9&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">712 &#40;8&#46;5&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">1538 &#40;7&#46;4&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Not performed&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">18&#44;312 &#40;39&#46;7&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">4930 &#40;58&#46;6&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">13&#44;382 &#40;64&#46;1&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " colspan="5" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleBold">Chest CT scan findings&#44; <span class="elsevierStyleItalic">n</span> &#40;&#37;&#41;</span></td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Atypical COVID-19 pattern&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">421 &#40;0&#46;9&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">124 &#40;1&#46;3&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">297 &#40;1&#46;2&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Typical COVID-19 pattern&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">22&#44;390 &#40;48&#46;6&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">5799 &#40;61&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">16&#44;591 &#40;67&#46;1&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Undetermined COVID-19 pattern&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">948 &#40;2&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">325 &#40;3&#46;4&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">623 &#40;2&#46;5&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Normal&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">85 &#40;0&#46;2&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">19 &#40;0&#46;2&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">66 &#40;0&#46;3&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Other&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">1790 &#40;3&#46;9&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">381 &#40;4&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">1409 &#40;5&#46;7&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Not performed&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">8590 &#40;18&#46;6&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">2864 &#40;30&#46;1&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">5726 &#40;23&#46;2&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#60;0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " colspan="5" align="left" valign="\n
                  \t\t\t\t\ttop\n
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                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>None&nbsp;\t\t\t\t\t\t\n
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          "leyenda" => "<p id="spar0065" class="elsevierStyleSimplePara elsevierViewall">In total&#44; 15 variables were inputted into the multivariate model&#46; The 15 variables were&#58; age&#44; sex&#44; presence of comorbidities&#44; need for non-invasive respiratory support&#44; chronic hepatic disease&#44; chronic neurological disease&#44; chronic pulmonary disease&#44; diabetes&#44; obesity&#44; cough&#44; respiratory distress&#44; fatigue&#44; anosmia&#44; diarrhea&#44; and fever&#46; The initial five variables&#44; considered of utmost importance&#44; are displayed&#46;</p><p id="spar0075" class="elsevierStyleSimplePara elsevierViewall"><span class="elsevierStyleItalic">Abbreviations</span>&#58; CI&#44; confidence interval&#59; OR&#44; odds ratio&#46;</p>"
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                  \t\t\t\t">Cough&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
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                  \t\t\t\t">Non-invasive respiratory support&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">Presence of comorbidities&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">1&#46;54&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">Respiratory distress&nbsp;\t\t\t\t\t\t\n
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          "en" => "<p id="spar0060" class="elsevierStyleSimplePara elsevierViewall">Multivariable analysis for the primary outcome&#46;</p>"
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    ]
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      "titulo" => "References"
      "seccion" => array:1 [
        0 => array:2 [
          "identificador" => "bibs0005"
          "bibliografiaReferencia" => array:45 [
            0 => array:3 [
              "identificador" => "bib0005"
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              "referencia" => array:1 [
                0 => array:2 [
                  "contribucion" => array:1 [
                    0 => array:2 [
                      "titulo" => "Clinical features of patients infected with 2019 novel coronavirus in Wuhan&#44; China"
                      "autores" => array:1 [
                        0 => array:2 [
                          "etal" => true
                          "autores" => array:6 [
                            0 => "C&#46; Huang"
                            1 => "Y&#46; Wang"
                            2 => "X&#46; Li"
                            3 => "L&#46; Ren"
                            4 => "J&#46; Zhao"
                            5 => "Y&#46; Hu"
                          ]
                        ]
                      ]
                    ]
                  ]
                  "host" => array:1 [
                    0 => array:2 [
                      "doi" => "10.1016/S0140-6736(20)30183-5"
                      "Revista" => array:7 [
                        "tituloSerie" => "Lancet"
                        "fecha" => "2020"
                        "volumen" => "395"
                        "numero" => "10223"
                        "paginaInicial" => "497"
                        "paginaFinal" => "506"
                        "link" => array:1 [
                          0 => array:2 [
                            "url" => "https://www.ncbi.nlm.nih.gov/pubmed/31986264"
                            "web" => "Medline"
                          ]
                        ]
                      ]
                    ]
                  ]
                ]
              ]
            ]
            1 => array:3 [
              "identificador" => "bib0010"
              "etiqueta" => "2"
              "referencia" => array:1 [
                0 => array:2 [
                  "contribucion" => array:1 [
                    0 => array:2 [
                      "titulo" => "Clinical characteristics of coronavirus disease 2019 in China"
                      "autores" => array:1 [
                        0 => array:2 [
                          "etal" => true
                          "autores" => array:6 [
                            0 => "W&#46;-J&#46; Guan"
                            1 => "Z&#46;-Y&#46; Ni"
                            2 => "Y&#46; Hu"
                            3 => "W&#46;-H&#46; Liang"
                            4 => "C&#46;-Q&#46; Ou"
                            5 => "J&#46;-X&#46; He"
                          ]
                        ]
                      ]
                    ]
                  ]
                  "host" => array:1 [
                    0 => array:2 [
                      "doi" => "10.1056/NEJMoa2002032"
                      "Revista" => array:7 [
                        "tituloSerie" => "N Engl J Med"
                        "fecha" => "2020"
                        "volumen" => "382"
                        "numero" => "18"
                        "paginaInicial" => "1708"
                        "paginaFinal" => "1720"
                        "link" => array:1 [
                          0 => array:2 [
                            "url" => "https://www.ncbi.nlm.nih.gov/pubmed/32109013"
                            "web" => "Medline"
                          ]
                        ]
                      ]
                    ]
                  ]
                ]
              ]
            ]
            2 => array:3 [
              "identificador" => "bib0015"
              "etiqueta" => "3"
              "referencia" => array:1 [
                0 => array:2 [
                  "contribucion" => array:1 [
                    0 => array:2 [
                      "titulo" => "Mechanisms of hypoxemia"
                      "autores" => array:1 [
                        0 => array:2 [
                          "etal" => false
                          "autores" => array:3 [
                            0 => "M&#46; Sarkar"
                            1 => "N&#46; Niranjan"
                            2 => "P&#46;K&#46; Banyal"
                          ]
                        ]
                      ]
                    ]
                  ]
                  "host" => array:1 [
                    0 => array:2 [
                      "doi" => "10.4103/0970-2113.197116"
                      "Revista" => array:6 [
                        "tituloSerie" => "Lung India"
                        "fecha" => "2017"
                        "volumen" => "34"
                        "numero" => "1"
                        "paginaInicial" => "47"
                        "link" => array:1 [
                          0 => array:2 [
                            "url" => "https://www.ncbi.nlm.nih.gov/pubmed/28144061"
                            "web" => "Medline"
                          ]
                        ]
                      ]
                    ]
                  ]
                ]
              ]
            ]
            3 => array:3 [
              "identificador" => "bib0020"
              "etiqueta" => "4"
              "referencia" => array:1 [
                0 => array:1 [
                  "referenciaCompleta" => "Centers for Disease Control and Prevention &#40;CDC&#41;&#46; National Institutes of Health&#46; Coronavirus disease 2019 &#40;COVID-19&#41; treatment guidelines&#46; Published 2023&#46; &#91;Accessed 20 April 2023&#93;&#46; <a target="_blank" href="https://www.covid19treatmentguidelines.nih.gov/">https&#58;&#47;&#47;www&#46;covid19treatmentguidelines&#46;nih&#46;gov&#47;</a>&#46;"
                ]
              ]
            ]
            4 => array:3 [
              "identificador" => "bib0025"
              "etiqueta" => "5"
              "referencia" => array:1 [
                0 => array:2 [
                  "contribucion" => array:1 [
                    0 => array:2 [
                      "titulo" => "Silent hypoxia&#58; a frequently overlooked clinical entity in patients with COVID-19"
                      "autores" => array:1 [
                        0 => array:2 [
                          "etal" => false
                          "autores" => array:4 [
                            0 => "A&#46; Chandra"
                            1 => "U&#46; Chakraborty"
                            2 => "J&#46; Pal"
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Journal Information
Vol. 224. Issue 8.
Pages 485-493 (October 2024)
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328
Vol. 224. Issue 8.
Pages 485-493 (October 2024)
Original article
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Risk factors for mortality in coronavirus disease 2019 patients with silent hypoxemia
Factores de riesgo de mortalidad en pacientes con enfermedad del coronavirus 2019 con hipoxemia silente
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328
Beatriz Ximenes Braza,b, Gdayllon Cavalcante Menesesa,c, Geraldo Bezerra da Silva Juniorc,d, Alice Maria Costa Martinsc, Andressa Fernandes de Souza Mourão Feitosaa, Gabriel Cavalcante Lima Chagasa,
Corresponding author
gabrielchagas.gc@gmail.com

Corresponding author at: Rua NS 03, 92, Fortaleza, CE 60824-090, Brazil.
, Elizabeth De Francesco Dahera
a Post-Graduation Program in Medical Sciences, Department of Internal Medicine, Faculty of Medicine, Federal University of Ceará, Fortaleza, CE, Brazil
b Internal Medicine Department, University of Miami, Miami, FL, United States
c Clinical and Toxicological Analysis Department, School of Pharmacy, Federal University of Ceará, Fortaleza, CE, Brazil
d Post-Graduation Program in Collective Health, Health Sciences Center, University of Fortaleza – UNIFOR, Fortaleza, CE, Brazil
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Tables (3)
Table 1. Baseline characteristics stratified by the primary outcome.
Table 2. Signs/symptoms, chest imaging, and treatments stratified by the primary outcome.
Table 3. Multivariable analysis for the primary outcome.
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Abstract
Objective

To describe the predictors of mortality in hospitalized patients with severe acute respiratory syndrome (SARS) due to COVID-19 presenting with silent hypoxemia.

Material and methods

Retrospective cohort study of hospitalized patients with SARS due to COVID-19 and silent hypoxemia at admission, in Brazil, from January to June 2021. The primary outcome of interest was in-hospital death. Multivariable logistic regression analysis was performed.

Results

Of 46,102 patients, the mean age was 59 ± 16 years, and 41.6% were female. During hospitalization, 13,149 patients died. Compared to survivors, non-survivors were older (mean age, 66 vs. 56 years; P < 0.001), less frequently female (43.6% vs. 40.9%; P < 0.001), and more likely to have comorbidities (74.3% vs. 56.8%; P < 0.001). Non-survivors had higher needs for invasive mechanical ventilation (42.4% vs. 6.6%; P < 0.001) and intensive care unit admission (56.9% vs. 20%; P < 0.001) compared to survivors. In the multivariable regression analysis, advanced age (OR 1.04; 95%CI 1.037–1.04), presence of comorbidities (OR 1.54; 95%CI 1.47–1.62), cough (OR 0.74; 95%CI 0.71–0.79), respiratory distress (OR 1.32; 95%CI 1.26–1.38), and need for non-invasive respiratory support (OR 0.37; 95%CI 0.35–0.40) remained independently associated with death.

Conclusions

Advanced age, presence of comorbidities, and respiratory distress were independent risk factors for mortality, while cough and requirement for non-invasive respiratory support were independent protective factors against mortality in hospitalized patients due to SARS due to COVID-19 with silent hypoxemia at presentation.

Keywords:
COVID-19
Hypoxia
Mortality
Predictor
Risk factor
Severe acute respiratory syndrome
Resumen
Objetivo

Describir los predictores de mortalidad en pacientes hospitalizados con síndrome respiratorio agudo severo (SARS) debido a COVID-19 que presentan hipoxemia silente.

Material y métodos

Estudio de cohorte retrospectivo de pacientes hospitalizados con SARS debido a COVID-19 y hipoxemia silente al ingreso, en Brasil, de enero a junio de 2021. El resultado principal de interés fue la muerte intrahospitalaria. Se realizó un análisis de regresión logística multivariable.

Resultados

De 46,102 pacientes, la edad media fue de 59 ± 16 años y el 41.6% eran mujeres. Durante la hospitalización, fallecieron 13,149 pacientes. En comparación con los sobrevivientes, los no sobrevivientes eran de mayor edad (edad media, 66 vs. 56 años; P < 0.001), menos frecuentemente mujeres (43.6% hombres vs. 40.9%; P < 0.001) y más propensos a tener comorbilidades (74.3% vs. 56.8%; P < 0.001). Los no sobrevivientes tuvieron mayores necesidades de ventilación mecánica invasiva (42.4% vs. 6.6%; P < 0.001) y admisión a la unidad de cuidados intensivos (56.9% vs. 20%; P < 0.001) en comparación con los sobrevivientes. En el análisis de regresión multivariable, la edad avanzada (OR 1.04; IC del 95% 1.037–1.04), la presencia de comorbilidades (OR 1.54; IC del 95% 1.47–1.62), la tos (OR 0.74; IC del 95% 0.71–0.79), la dificultad respiratoria (OR 1.32; IC del 95% 1.26–1.38) y la necesidad de soporte respiratorio no invasivo (OR 0.37; IC del 95% 0.35–0.40) permanecieron independientemente asociadas con la muerte.

Conclusiones

La edad avanzada, la presencia de comorbilidades y la dificultad respiratoria fueron factores de riesgo independientes para la mortalidad, mientras que la tos y la necesidad de soporte respiratorio no invasivo fueron factores protectores independientes contra la mortalidad en pacientes hospitalizados debido a SARS debido a COVID-19 con hipoxemia silente en la presentación.

Palabras clave:
COVID-19
Hipoxia
Mortalidad
Predictor
Factor de riesgo
Síndrome respiratorio agudo severo
Full Text
Introduction

Coronavirus disease 2019 (COVID-19), an infection caused by the severe acute respiratory syndrome Coronavirus 2 (SARS-CoV-2), has a wide range of clinical presentations, from asymptomatic infection to critical and fatal disease.1 Most symptomatic infections are mild and present with fever, cough, and fatigue.2

Changes in blood gas concentrations can cause dyspnea and respiratory distress, which are crucial indicators of severe disease.3 According to the Centers for Disease Control and Prevention guidelines, patients with hypoxemia are classified as having severe disease, with the requirement for more advanced medical care.4 Patients may have hypoxemia without dyspnea, also known as silent, non-dyspneic, or “happy” hypoxemia.5 In patients presenting to the hospital with COVID-19 and hypoxemia, the prevalence of this unusual clinical presentation ranges from 4.9% to 31.9%. Given the definition of silent hypoxemia, the prevalence of this severe manifestation of COVID-19 may be underestimated.6,7

Despite its prevalence and potential for rapid clinical deterioration, the pathological mechanisms and prognostic implications of silent hypoxemia remain poorly understood. This underscores the critical need for epidemiological investigations to elucidate its prevalence, risk factors, and impact on patient outcomes. Previous studies assessing the impact of silent hypoxemia in COVID-19 were based on relatively small sample sizes and may have been underpowered to detect significant risk factors associated with unfavorable clinical outcomes.6–11

In this context, we aimed to describe the clinical characteristics and predictors of mortality in a cohort of patients who were hospitalized for severe acute respiratory syndrome (SARS) due to COVID-19 presenting with silent hypoxemia.

Material and methodsStudy design, data sources, participants, and measurements

This is an observational retrospective cohort study. We extracted data from the Influenza Epidemiological Surveillance Information System (Sistema de Informação da Vigilância Epidemiológica da Gripe, SIVEP-Gripe, in Portuguese), an information system of the Brazilian Ministry of Health that captures all notifications of hospitalizations due to SARS in Brazil in both public and private, from the Department of Information and Computing of the Brazilian Unified Health System (Departamento de Informação e Informática do Sistema Único de Saúde, DATASUS, in Portuguese), from January 1 to June 18, 2021. Notifications were submitted to the system within 24 h of initial clinical suspicion or positive laboratory results. SARS was defined as dyspnea, central cyanosis, persistent chest pain or pressure, or peripheral arterial oxygen saturation (SpO2) measured by pulse oximetry of <95% in room air.12

We considered only records of patients with confirmed COVID-19 diagnosis as per the Brazilian Ministry of Health guidelines12 and silent hypoxemia at presentation, defined as SpO2 measured by pulse oximetry of <95% without dyspnea. We excluded pregnant patients or patients with unknown pregnancy status and patients with missing data regarding SpO2.

Baseline characteristics, such as symptoms, signs, and radiological/computed tomography (CT) findings, were assessed and recorded by the healthcare professionals responsible for patient care at hospital admission. Requirement for respiratory support, admission to the intensive care unit (ICU), and mortality were evaluated throughout the hospital stay.

This study adheres to the Helsinki Declaration’s ethical guidelines for research involving human subjects. The Ethics Committee of the Public Health School of Ceará approved this study (reference number 49905921.4.0000.5037). Patient consent for publication was not required, as data was extracted from a publicly accessible, deidentified repository.

Follow-up and outcomes

Patients were followed up during hospitalization. The primary outcome of interest was the occurrence of death.

Statistical analyses

Categorical data were expressed as absolute counts and percentages. All ​​quantitative data were tested for normal distribution using the Kolmogorov–Smirnov test. Normally distributed data were expressed as mean and standard deviation (SD).

Proportions for categorical variables were compared using the chi-squared and Fisher’s exact tests, as appropriate. Means for continuous variables were compared using the Student’s t-test according to normal distribution.

We then performed a multivariable logistic regression analysis including statistically significant variables in bivariate analysis to identify independent predictors of mortality. The most significant level of the variables for the outcome of interest was investigated using the forward stepwise method. The presence of collinearity between the ​​independent variables was explored by estimating the tolerance and variance inflation factor before the inclusion of multivariable models.

All analyses were performed with IBM SPSS Statistics for Mac OS, version 23.0 (IBM Corp., Armonk, N.Y., USA). We regarded a P value of <0.05 as statistically significant.

ResultsClinical characteristics of patient population

A total of 747,926 patients were screened between January and June 2021, and 46,102 patients were included (Fig. 1). The mean age was 59 ± 16 years, 19,204 (41.6%) were female, and 23,428 (50.9%) were White individuals. The predominant comorbidities were chronic cardiovascular disease (14,890 [32.3%]), diabetes (5717 [12.4%]), and obesity (1780 [3.9%]). The most common signs and symptoms during hospitalization were cough (30,951 [67.2%]), respiratory distress (22,496 [48.8%]), and fatigue (11,176 [24.2%]). The main chest imaging findings were interstitial infiltrates (6467 [14%]) and typical COVID-19 pneumonia (22,390 [48.6%]) on radiographs and CT scans, respectively. Most patients needed ventilatory support, with 30,413 (66%) non-invasive support and 7762 (16.8%) requiring invasive support. Additionally, 13,428 (29.1%) of patients were admitted to the ICU.

Figure 1.

Flow diagram illustrating the inclusions and exclusions of study participants.

Abbreviation: SpO2, peripheral arterial oxygen saturation.

(0.13MB).
Primary outcome

The main outcome occurred in 13,149 (28.5%) patients by the end of the follow-up period.

Univariable analyses

Tables 1 and 2 show epidemiological, demographic, clinical, radiological, and treatment data stratified by the presence of the primary outcome.

Table 1.

Baseline characteristics stratified by the primary outcome.

Variable  All (n = 46,102)  Died (n = 13,149)  Alive (n = 32,953)  P value 
Age, mean (SD), years  59 (16)  66 (15)  56 (16)  <0.001 
Gender, n (%)
Female  19,204 (41.6)  5727 (43.6)  13,477 (40.9)  <0.001 
Ethno-racial group, n (%)
Asian  375 (0.08)  106 (0.9)  269 (1)  <0.001 
Black  2031 (4.4)  706 (6.1)  1325 (4.8)  <0.001 
Brown  13,541 (29.4)  3965 (34.1)  9576 (34.4)  <0.001 
Indigenous  56 (0.1)  16 (0.1)  40 (0.1)  <0.001 
White  23,468 (50.9)  6829 (58.8)  16,639 (59.7)  <0.001 
Comorbidity, n (%)  28,492 (61.8)  9770 (74.3)  18,722 (56.8)  <0.001 
Asthma  341 (0.07)  123 (0.9)  218 (0.7)  0.002 
Chronic cardiovascular disease  14,890 (32.3)  5369 (40.8)  9521 (28.9)  <0.001 
Chronic hematologic disease  128 (0.3)  57 (0.4)  71 (0.2)  <0.001 
Chronic hepatic disease  134 (0.3)  68 (0.5)  66 (0.2)  <0.001 
Chronic lung disease  612 (1.3)  301 (2.3)  311 (0.9)  <0.001 
Chronic neurological disease  1686 (3.6)  784 (6)  902 (2.7)  <0.001 
Chronic renal disease  1371 (3.0)  711 (5,4)  660 (2)  <0.001 
Diabetes  5717 (12.4)  2284 (17.4)  3433 (10.4)  <0.001 
Down syndrome  55 (0.1)  19 (0.1)  36 (0.1)  0.322 
Immunodeficiency  332 (0.7)  158 (1.2)  174 (0.5)  <0.001 
Obesity  1780 (3.8)  706 (5.4)  1074 (3.3)  <0.001 
Up-to-date influenza vaccination, n (%)  5359 (11.6)  1543 (23.2)  3816 (21.4)  0.002 

Categorical data are expressed as absolute count (percentages). Quantitative data are expressed as mean ± standard deviation.

Abbreviation: SD, standard deviation.

Table 2.

Signs/symptoms, chest imaging, and treatments stratified by the primary outcome.

Variable  All (n = 46,102)  Died (n = 13,149)  Alive (n = 32,953)  P value 
Signs and symptoms, n (%)
Abdominal pain  3002 (6.5)  768 (6)  2234 (6.9)  <0.001 
Anosmia  4935 (10.7)  992 (7.7)  3943 (12.2)  <0.001 
Cough  30,951 (67.1)  7966 (60.9)  22,985 (70)  <0.001 
Diarrhea  7710 (16.7)  1927 (14.9)  5783 (17.7)  <0.001 
Dysgeusia  5307 (11.5)  1113 (8.7)  4194 (13)  <0.001 
Fatigue  11,176 (24.2)  2819 (21.9)  8357 (25.9)  <0.001 
Respiratory distress*  22,496 (48.8)  6901 (52.8)  15,595 (47.6)  <0.001 
Sore throat  7126 (15.4)  1714 (13.2)  5412 (16.6)  <0.001 
Vomiting  4623 (10)  1181 (9.1)  3442 (10.6)  <0.001 
Chest radiograph findings, n (%)
Consolidation  626 (1.3)  274 (3.3)  352 (1.7)  <0.001 
Interstitial infiltrates  6467 (14)  1985 (23.6)  4482 (21.5)  <0.001 
Mixed pattern  725 (1.6)  249 (3)  476 (2.3)  <0.001 
Normal  907 (2)  266 (3.2)  641 (3.1)  <0.001 
Other  2250 (4.9)  712 (8.5)  1538 (7.4)  <0.001 
Not performed  18,312 (39.7)  4930 (58.6)  13,382 (64.1)  <0.001 
Chest CT scan findings, n (%)
Atypical COVID-19 pattern  421 (0.9)  124 (1.3)  297 (1.2)  <0.001 
Typical COVID-19 pattern  22,390 (48.6)  5799 (61)  16,591 (67.1)  <0.001 
Undetermined COVID-19 pattern  948 (2)  325 (3.4)  623 (2.5)  <0.001 
Normal  85 (0.2)  19 (0.2)  66 (0.3)  <0.001 
Other  1790 (3.9)  381 (4)  1409 (5.7)  <0.001 
Not performed  8590 (18.6)  2864 (30.1)  5726 (23.2)  <0.001 
Need for respiratory support, n (%)
None  7927 (17.2)  1146 (8.7)  6781 (20.6)  <0.001 
Non-invasive  30,413 (66)  6429 (48.9)  23,984 (72.8)  <0.001 
Invasive  7762 (16.3)  5574 (42.4)  2188 (6.6)  <0.001 
Need for ICU admission, n (%)  13,428 (29.1)  7128 (56.9)  6300 (20)  <0.001 

Categorical data are expressed as absolute count (percentages).

Abbreviations: CT, computed tomography; ICU, intensive care unit.

*

Absent at hospital admission.

Compared with patients who survived, patients who died were characterized by advanced age (mean age, 66 [SD, 15] vs. 56 years [SD, 16]; P < 0.001), less frequently female sex (43.6% female vs. 56.4% male; P < 0.001), and predominantly black (6.1% vs. 4.8%; P < 0.001) ethnic-racial group. Proportionately, black and brown individuals had higher mortality rates (53.3% and 41.4%, respectively).

Patients who died were significantly more likely to have one or more coexisting medical conditions compared to those who survived (74.3% vs. 56.8%; P < 0.001). Of those comorbidities, chronic cardiovascular disease (40.8% vs. 28.9%; P < 0.001), chronic hematologic disease (0.4% vs. 0.2%; P < 0.001), chronic neurological disease (6% vs. 2.7%; P < 0.001), chronic hepatic disease (0.5% vs. 0.2%; P < 0.001), chronic lung disease (2.3% vs. 0.9%; P < 0.001), chronic kidney disease (5.4% vs. 2%; P < 0.001), diabetes (17.4% vs. 10.4%; P < 0.001), immunodeficiency (1.2% vs. 0.5%; P < 0.001), and obesity (5.4% vs. 3.3%; P < 0.001) were significantly associated with mortality.

Regarding the influenza vaccination status, deceased patients had significantly higher rates of up-to-date vaccination (23.2% vs. 21.4%; P = 0.002) compared to survivors.

During hospitalization, patients who died presented significantly higher rates of respiratory distress (52.8% vs. 47.6%; P < 0.001) compared to those who survived. However, anosmia (7.7% vs. 12.2%; P < 0.001), cough (60.9% vs. 70%; P < 0.001), diarrhea (14.9% vs. 17.7%; P < 0.001), dysgeusia (8.7% vs. 13%; P < 0.001), fatigue (21.9% vs. 25.9%; P < 0.001), and sore throat (13.2% vs. 16.6%; P < 0.001) were significantly less frequent.

In comparison to survivors, non-survivors were significantly less likely to exhibit changes in chest imaging studies, except for the typical COVID-19 pattern (61% vs. 67.1%; P < 0.001). However, a substantial proportion of patients did not undergo chest imaging (39.7% for radiographs and 18.6% for chest CT scans).

Concerning respiratory support, non-survivors had a significantly higher need for invasive mechanical ventilation (42.4% vs. 6.6%; P < 0.001) compared to survivors. In contrast, no respiratory support (8.7% vs. 20.6%; P < 0.001) and the need for non-invasive respiratory support (48.9% vs. 72.8%; P < 0.001) were significantly less likely among non-survivors.

Finally, ICU admission was significantly associated with mortality (56.9% vs. 20%; P < 0.001).

Multivariable analyses

In the multivariable analysis (Table 3), advanced age (odd ratio [OR] 1.04; 95% confidence interval [CI] 1.037–1.04; P < 0.001), presence of comorbidities (OR 1.54; 95%CI 1.47–1.62; P < 0.001), cough (OR 0.74; 95%CI 0.71–0.79; P < 0.001), respiratory distress (OR 1.32; 95%CI 1.26–1.38; P < 0.001), and need for non-invasive respiratory support (OR 0.37; 95%CI 0.35–0.40; P < 0.001) remained independently associated with death.

Table 3.

Multivariable analysis for the primary outcome.

Variable  OR  95%CI  P value 
Age*  1.039  1.037–1.04  <0.001 
Cough  0.74  0.71–0.78  <0.001 
Non-invasive respiratory support  0.37  0.35–0.40  <0.001 
Presence of comorbidities  1.54  1.47–1.62  <0.001 
Respiratory distress  1.32  1.26–1.38  <0.001 

In total, 15 variables were inputted into the multivariate model. The 15 variables were: age, sex, presence of comorbidities, need for non-invasive respiratory support, chronic hepatic disease, chronic neurological disease, chronic pulmonary disease, diabetes, obesity, cough, respiratory distress, fatigue, anosmia, diarrhea, and fever. The initial five variables, considered of utmost importance, are displayed.

Abbreviations: CI, confidence interval; OR, odds ratio.

*

Risk for every additional year of age.

Discussion

This retrospective cohort study evaluated the clinical characteristics and predictors of death in hospitalized patients due to SARS from COVID-19 who presented with silent hypoxemia at admission. Our main findings were that (I) advanced age, presence of comorbidities, and development of respiratory distress were independent risk factors for mortality, while (II) development of cough and need for non-invasive respiratory support were independent protective factors against mortality.

Several mechanisms have been proposed to explain silent hypoxemia in COVID-19. Gattinoni et al. proposed two primary “phenotypes”: types L and H. Type L, characterized by low elastance and reduced ventilation-to-perfusion (V/Q) ratio, results from viral-induced local interstitial edema and vasoplegia.13–15 Patients with the type L lack dyspnea due to near-normal compliance.16–19 Transition to the type H, driven by heightened COVID-19 severity and inflammation, may induce dyspnea through patient self-inflicted lung injury (P-SILI).13,20 This mirrors the conditions observed in acute respiratory distress syndrome.16,21,22

In COVID-19, the absence of dyspnea may be attributed to direct viral damage to the carotid bodies and solitary tract, as the glomus cells of the carotid body exhibit high expression levels of the SARS-CoV-2 receptor, angiotensin-converting enzyme-2.7,18,19,23–26 Acute vascular distress syndrome (AVDS), resulting from endothelial dysfunction, microthrombi formation in the pulmonary vasculature, and vascular proliferation in the lungs, causes an elevated pulmonary vascular flow, leading to a significant intrapulmonary right-to-left shunt.27,28 Additionally, variability of the hypoxic ventilatory response across different populations not only explains the high prevalence of silent hypoxemia but also suggests that this phenomenon could be present in other causes of hypoxia, such as influenza pneumonia, among others (Fig. 2).16

Figure 2.

Proposed mechanisms of silent hypoxia in COVID-19.

(A) Direct viral infection of the carotid bodies and central nervous system may reduce the perception of dyspnea mediated by chemoreceptors. (B) Endothelial cell dysfunction can precipitate acute vascular distress syndrome. This fosters the formation of microthrombi within the pulmonary vasculature (C) and induces vascular proliferation in the lungs. Consequently, this cascade can culminate in the development of intrapulmonary right-to-left shunt (D). (E) Loss of lung perfusion regulation and hypoxic vasoconstriction might also contribute to right-to-left shunt (D). (F) Respiratory alkalosis and hypocapnia blunt both ventilatory stimuli and sensation of dyspnea.

Abbreviation: P-SILI, patient self-inflicted lung injury.

(0.39MB).

To our knowledge, this study is the largest cohort of silent hypoxemia in COVID-19 to date. Advanced age and the presence of comorbidities emerged as significant independent predictors of adverse outcomes, aligning with prior research. Remarkably, a comprehensive meta-analysis assessing the isolated effect of age on the risk of severe outcomes among COVID-19 patients, the risks of hospitalization, in-hospital mortality, and overall mortality increased by 3.4%, 5.7%, and 7.4% per age year, respectively. These outcomes underscore the continuous age-related increase in susceptibility to adverse events associated with SARS-CoV-2 infection.1,3,29–32 Moreover, the association of comorbid conditions, such as cardiovascular disease, diabetes, and obesity, with severe COVID-19 emphasizes the importance of considering the underlying health status in risk stratification and clinical management strategies for patients with silent hypoxemia.33–35

In our cohort, survivors were generally more symptomatic, experiencing a range of symptoms including anosmia, cough, diarrhea, dysgeusia, fatigue, and sore throat. These symptoms may have prompted patients to seek medical care earlier in the disease course; thereby, increasing the likelihood of receiving timely respiratory support. This prompt intervention could have contributed to diminishing P-SILI, attenuating the severity of respiratory compromise and ultimately improving patient outcomes.

Notably, the development of cough and the need for non-invasive respiratory support emerge as protective factors against mortality. These results underscore the significance of early identification of hypoxemic patients. Timely recognition of symptoms like cough and prompt initiation of appropriate respiratory support measures could significantly improve patient outcomes and reduce mortality rates in COVID-19.

In a meta-analysis investigating the prevalence and outcomes of COVID-19 patients with silent hypoxia, Bepouka et al. demonstrated a mortality rate ranging from 1% to 45.4%, with a pooled mortality of 2%.36 In our cohort, the mortality was notably higher at 28.5%. This disparity may stem from variations in patient demographics, disease severity, healthcare systems, and definitions of silent hypoxemia across studies.

Among non-dyspneic COVID-19 patients, approximately one-third may manifest hypoxemia upon admission, marking them as a subset of severe cases requiring early identification.37,38 Pulse oximetry emerges as a pivotal tool in this context, offering a simple, non-invasive, and widely accessible means of assessing arterial oxygen saturation.39,40 Despite potential confounding factors, such as racial bias, vasoconstriction, hypoxemia, and COVID-19 itself, which may impact the accuracy of SpO2 measurement and the correlation between SpO2 and arterial oxygenation, the integration of pulse oximeters is crucial for screening COVID-19 patients.41,42 In this specific group of non-dyspneic patients, the initial assessment of SpO2 through pulse oximetry holds particular significance, enabling the early detection of asymptomatic hypoxia, facilitating timely intervention, and ultimately enhancing outcomes.37,43,44 Additionally, clinical evaluations should emphasize monitoring the progression of signs and symptoms, especially the respiratory rate, to promptly identify any deterioration.16,45 This comprehensive approach ensures a proactive and effective management strategy for this specific cohort, contributing to enhanced patient care and better overall prognosis.

Regarding screening for the severity of disease in the outpatient setting, it is clear that the sole utilization of patient-reported symptoms would not be an accurate and thorough strategy due to the existence of non-dyspneic hypoxemic presentations. This should warrant the utilization of more objective criteria, including arterial blood gas and pulse oximetry. Based on these findings, we suggest that when feasible patients with COVID-19 should undergo timely screening of hypoxemia, regardless of symptomology, with pulse oximetry to assess for silent hypoxemia and consequent need for respiratory support and pharmacological treatments available.

When providing respiratory support to patients with silent hypoxemia – believed to be associated with the type L phenotype –, the primary focus should be on preventing P-SILI and increasing the fraction of inspired oxygen. Implementing an early strategy of providing respiratory support for these patients could have the potential to reduce the risk of P-SILI, and, consequently, mitigate disease progression.

Limitations

This study has limitations. First, we used administrative records from structured surveillance forms, which may carry inherent limitations due to their reliance on predefined categories and standardized data entry. Second, not all cases of COVID-19 are notified in Brazil. The underreporting could impact the generalizability of the study results. Third, patients with missing data regarding SpO2 and the presence of dyspnea or respiratory distress at hospital admission were excluded from the analysis. Fourth, since our study was conducted in early 2021, patients with the Omicron variant and its sublineages were unlikely to be included. Thus, further research specifically including patients infected with these variants is essential. Fifth, the absence of available data on laboratory results, including arterial blood gas, which could be used to analyze better blood gas alterations that could potentially interfere with clinical courses such as hypo and hypercapnia, limited our considerations. Sixth, the limited data on time from the symptom onset to the initial presentation and duration of follow-up hinders precise assessment of patient clinical evolution and the impact of delayed medical intervention. Thus, more studies with comprehensive time-related data are warranted to further elucidate the clinical course of silent hypoxemia in COVID-19.

Conclusions

In this multicenter cohort study of 46,102 hospitalized patients due to SARS due to COVID-19 with silent hypoxemia at presentation in Brazil, advanced age, presence of comorbidities, and development of respiratory distress were independent risk factors for mortality. Conversely, the emergence of cough and the requirement for non-invasive respiratory support were independent protective factors against mortality.

Funding

This study was sponsored by the Brazilian Council for Scientific and Technological Development (Conselho Nacional de Desenvolvimento Científico e Tecnológico,CNPq, in Portuguese) and by the Coordination of Improvement of Higher Education Personnel (Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, CAPES, in Portuguese). The funding sources did not participate in study design; collection, management, analysis, and interpretation of data; and preparation, review, and approval of this manuscript.

Conflicts of interest

The authors have declared no conflicts of interest.

Data availability statement

All data relevant to the study are included in the article or uploaded as supplementary information.

Acknowledgment

This work should be credited to the Federal University of Ceará, Fortaleza, CE, Brazil.

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