key: cord-1015833-8789ibcp authors: Pigoga, Jennifer L; Friedman, Alexandra; Broccoli, Morgan; Hirner, Sarah; Naidoo, Antoinette Vanessa; Singh, Swasthi; Werner, Kalin; Wallis, Lee A title: Clinical and historical features associated with severe COVID-19 infection: a systematic review date: 2020-04-27 journal: nan DOI: 10.1101/2020.04.23.20076653 sha: 037ecc89d99be71ea27ea32779354efe1c2796e2 doc_id: 1015833 cord_uid: 8789ibcp Background: There is an urgent need for rapid assessment methods to guide pathways of care for COVID-19 patients, as frontline providers need to make challenging decisions surrounding rationing of resources. This study aimed to evaluate existing literature for factors associated with COVID-19 illness severity. Methods: A systematic review identified all studies published between 1/12/19 and 19/4/20 that used primary data and inferential statistics to assess associations between the outcome of interest - disease severity - and historical or clinical variables. PubMed, Scopus, Web of Science, and the WHO Database of Publications on Coronavirus Disease were searched. Data were independently extracted and cross-checked independently by two reviewers using PRISMA guidelines, after which they were descriptively analysed. Quality and risk of bias in available evidence were assessed using the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) framework. This review was registered with PROSPERO, registration number CRD42020178098. Results: Of the 6202 relevant articles found, 63 were eligible for inclusion; these studies analysed data from 17648 COVID-19 patients. The majority (n=57, 90.5%) were from China and nearly all (n=51, 90.5%) focussed on admitted adult patients. Patients had a median age of 52.5 years and 52.8% were male. The predictors most frequently associated with COVID-19 disease severity were age, absolute lymphocyte count, hypertension, lactate dehydrogenase (LDH), C-reactive protein (CRP), and history of any pre-existing medical condition. Conclusion: This study identified multiple variables likely to be predictive of severe COVID-19 illness. Due to the novelty of SARS-CoV-2 infection, there is currently no severity prediction tool designed to, or validated for, COVID-19 illness severity. Findings may inform such a tool that can offer guidance on clinical treatment and disposition, and ultimately reduce morbidity and mortality due to the pandemic. Despite containment efforts, COVID-19 has reached pandemic status. As of 21 April 2020, there are 2.5 million confirmed cases worldwide, with over 170,000 deaths; 1 2 these numbers are only expected to grow in the coming weeks and months. Although data surrounding the novel coronavirus are rapidly evolving, initial estimates depict a dire situation: between 15% and 20% of infections lead to severe or critical disease. 2 3 Highly vulnerable populations, compromised by factors such as malnutrition and comorbid diseases, are believed to be at greater risk of developing severe and critical disease. 4 Mortality has varied across settings, but early data suggest a case fatality rate ranging from 0.5% to 4.5%. [5] [6] [7] [8] As COVID-19 spreads, healthcare systems worldwide are being strained. 9 10 Early recognition, resuscitation and referral have proven key to effective responses, yielding lower mortality. 11 High volumes of patients in need of critical care limit systems' abilities to provide such care; this is already occurring even in the most highly-resourced settings. 9 10 It is increasingly likely that the countries with the most limited capacity to respond will soon be affected on a large scale. 12 Many low-resource settings (LRS) have scarce critical care resources, with limitations in the availability of oxygen and other basic resources as well as healthcare provider shortages. 13 14 While ongoing acute and emergency care system strengthening efforts are underway and showing impact in many of these settings, these systems will not be able to keep pace with the emerging demand. 12 Immediate targeted efforts are needed to assist stressed healthcare systems around the globe in managing and treating large numbers of acutely ill COVID-19 patients. 12 Frontline providers in emergency units (EUs) need to make challenging decisions surrounding rationing of resources, including oxygen and ventilators, upon initial assessment of COVID-19 patients. Clinical guidance for evaluating patients' respiratory needs and subsequent dispositions is essential, particularly in LRS. A range of scoring systems are available to guide care for severely ill patients. While these tools may have some utility in predicting COVID-19 patient severity, they are likely limited in this unique context. Some scores are designed for specific care settings, such as intensive care units (ICUs), a very scarce resource in LRS. 15 While selected COVID-19 patients can be treated in ICUs, most patients are less critical, requiring interventions more appropriate for general ward and EU settings. Thus, a tool predicting outcomes based solely on those already admitted to ICU may have reduced utility across the range of illness severity seen in this disease. Other scoring systems were purposedesigned for patients presenting with specific conditions, such as pneumonia and sepsis. 15 16 Conditionspecific tools may be of some use in assessing COVID-19 patients but are likely limited in that these patients initially present with a range of symptoms, only some of which involve respiratory disease or septic shock. 17 High burdens of data entry seen in many tools can lead to increased time-to-decision making and frequent missing data points. [18] [19] [20] Some also involve additional investigations, including blood tests and imaging, 15 21-23 that have very limited availability in LRS. In the context of the COVID-19 crisis, a low-input severity scoring tool could be a cornerstone of ensuring timely access to appropriate care and justified use of critically limited resources. In order to identify or develop a severity assessment tool appropriate for COVID-19 patients, factors contributing to, and predictive of, patient severity must first be understood. This study aimed to systematically evaluate existing COVID-19 literature for relationships between historical characteristics and clinical presentations and investigations, and illness severity. A systematic review was conducted to identify papers that studied potential associations between demographics, comorbidities, clinical presentations and investigational studies, and COVID-19 illness severity. The Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines were adhered to throughout this process. 24 Search strategy and selection criteria Three online databases (PubMed, Scopus, and Web of Science) were searched using a combination of free-text phrases and medical subject headings. Results were restricted to those in the English, Spanish, and Mandarin languages, published between 01 December 2019 and 19 April 2020. Search terms related to COVID-19 infection ("NCoV", "Coronavirus", "severe acute respiratory syndrome coronavirus 2", "COVID", "COVID-19", "Coronavirus infections") and illness severity ("Severity of Illness Index", "severity", "critical", "critical illness", "critical care", "patient admission", "length of stay", "outcome", "morbidity", "mortality", "death", "respiratory insufficiency", "respiratory distress syndrome, adult", and "respiration, artificial") were used in combination with those for demographics ("demographic", "demographic", "age", "sex", and "gender"), historical features ("comorbidity", "comorbidity"), "pre-existing", and "condition"), clinical presentation ("signs and symptoms", "symptom", "characteristic", "clinical" and, "presentation"), and diagnostic investigations ("investigation", "laboratory", "blood test", "imaging", "X-ray" and, "CT"). Refer to appendix 1 for full search strategy. All publications in the World Health Organization's (WHO) Database of Publications on Coronavirus Disease (COVID-19) were also included. 25 Reference lists of all texts eligible full texts were reviewed to identify additional relevant literature. Duplicates were manually removed. All articles were screened for inclusion by two independent reviewers (JLP, KW, SS, AVN), after which a third reviewer (AF, JLP, MB, SS, AVN) retrieved each eligible full-text and considered for inclusion. Two discrepancies in agreement were resolved through discussion. This study included all full-text manuscripts, both pre-print and published, that provided data on associations between the outcome of interest -disease severity -and demographics, comorbidities, symptoms, vital signs, and/or investigational studies of confirmed COVID-19 patients admitted to hospitals. Research-based correspondence pieces were also included, as this is an additional format of rapid research dissemination in the COVID-19 era. Those not directly evaluating primary data, including literature reviews and meta-analyses, were excluded, as were opinion and editorial pieces, case reports, and clinical management guidelines. A range of definitions and parameters of illness severity were considered acceptable as comparator outcomes, including disease severity itself (as defined by the article's authors), as well as proxy measures for disease severity, such as inpatient mortality and ICU admission 26 . Manuscripts that did not include statistical analyses evaluating significance were excluded. There were no restrictions to study design. Studies evaluating exclusively children or pregnant populations were excluded. symptom most frequently associated with severe disease was dyspnoea or difficulty in breathing ( Table 4 ). All other symptoms, including fever or chills, cough, sputum production, myalgias, and diarrhoea among others, were more frequently not associated with severe disease. Six of ten (60%) studies evaluating respiratory rate for initial vitals found it to be a predictor of severity, and four of five (80%) for SpO2. The most commonly associated laboratory values were absolute lymphocyte count, LDH, CRP, Ddimer, and procalcitonin (Table 5 ). Among associated laboratory values, PaO2/FiO2,N-terminal btype natriuretic peptide (NT-proBNP) and blood glucose were each consistently reported as significant across multiple studies. Abnormal CT was significant in ten of 16 (62·5%) studies, and abnormal chest X-ray in two of four (50%) ( Table 5 ). The novelty of SARS-CoV-2 infection has led to many hypotheses regarding potentially significant predictors of patient illness. This study aimed to provide clarity around potential predictors by presenting a systematic review of the features most frequently and consistently associated with COVID-19 illness severity. The available literature evaluates a broad range of clinical characteristics and investigations, highlighting variables likely to be significantly associated with illness severity, including age, history of pre-existing medical conditions, dyspnoea on presentation, and a range of blood tests. In line with several publications, [28] [29] [30] age was identified as a predictor of illness severity in nearly all studies. However, not all studies addressed confounding in their methodology. It is not clear whether age is an independent predictor for severity due to decreased physiological reserve or if increased rates of comorbidities amongst elderly populations influence its significance. Results suggest that any preexisting condition may put COVID-19 patients at higher risk of poor outcomes. But, when looking at specific conditions, few comorbidities were found to be consistently significant across the literature. Hypertension, cardiovascular disease, and body mass index (BMI) were found to be significant predictors in the majority of instances where they were evaluated; these should be assessed further in future investigations In clinical practice, clinical discriminators and vital signs play important roles in determining acuity. Shortness of breath or dyspnoea was the only presenting symptom reported as a significant predictor of severity across these studies. An earlier meta-analysis of COVID-19 data also supports this conclusion. 31 Dyspnoea is easy to assess and already being used in many settings for COVID-19 screening, 31-33 making it a candidate for potential inclusion in a COVID-19 severity scoring tool. Data on initial vital signs were inconclusive. Although a large portion of potentially predictive variables depend on blood investigations, these predictors may have limited utility in the initial management of COVID-19 disease, especially in LRS: Faced with scarce time and resources, and overwhelming patient numbers, clinicians around the world are in need of near-immediate indicators of illness severity. Potentially relevant severity calculators such as the Pneumonia Severity Index and CURB-65, require blood investigations and imaging to predict mortality, and are based on non-COVID-19 pneumonia, 23 34 limiting their utility in the pandemic. Due to the novelty of SARS-CoV-2 infection, there are currently no scoring systems validated for COVID-19 illness severity assessment either at the initial point of entry to the healthcare system or during admission. Such a tool could enable rapid classification of patients' illness severity to determine disposition and resource allocation, aiding overwhelmed healthcare systems facing limited resources. It could assist frontline providers in decision-making surrounding resource allocation, including both the physical -e.g. oxygen and mechanical ventilation -and human resources necessary to oversee such interventions in a timely, appropriate manner for the rapidly increasing volume of COVID-19 patients. Most LRS already suffered from scarcities of oxygen, mechanical ventilation and ICU beds pre-COVID-19, 35 and the current resource constraints seen in highly-resourced settings will likely be even more extreme in LRS. 36 37 Ethical allocation of resources is expected to become a necessity in all settings, as providers will have to divide resources across both COVID-19 and non-COVID-19 patients, many of whom will have similar prognoses. 38 Though a severity scoring tool may identify a patient's need for oxygen or mechanical ventilation, broader resource allocation for all patient populations requires ethical frameworks beyond such a tool's scope. This review's findings may have utility as components of a COVID-19-specific severity scoring tool that could offer guidance on clinical treatment and disposition, and ultimately reduce morbidity and mortality due to the COVID-19 pandemic. Some discrepancies exist between our findings and calculators currently being used to evaluate COVID-19 patients, namely on the significance of initial vitals, presenting symptoms, laboratory values and imaging findings. Though our findings were inconclusive in regard to initial vitals, one study reported that qSOFA was predictive of COVID-19 illness severity, 39 indicating that altered mental status, tachypnoea and systolic blood pressure ≤100mmHg could be predictive in a severity scoring tool. Most pneumonia clinical calculators to predict illness severity rely on laboratory and imaging investigations that were insignificant in our systematic review-aside from glucose, absolute lymphocyte count and PaO2/FiO2-and are not immediately available in most LRS. Various calculators also emphasise sex and pulmonary co-morbidities, which were found to be independently insignificant in our review. The discrepancies between our systematic review and the clinical calculators of illness severity being used in this pandemic warrant a COVID-19 specific-calculator based on the emerging evidence rather than single-institution experience to facilitate illness severity stratification. Due to the emergent COVID-19 pandemic and need for data to inform responses, rapid efforts are being made to publish any available information. Our review included research-based correspondence and pre-print articles alongside peer-reviewed publications, all of which were in the form of observational cohort studies. However, all studies performed well against GRADE criteria, scoring at least as well as is expected for cohort studies (low quality or above). An overwhelming majority of studies originated in China; this suggests that there may be increased homogeneity in the data and that results might not be translatable to other settings. It could not be confirmed that none of the publications used populations from the same patient database. Findings of this study may also be limited in that they are solely descriptive, lacking any testing of statistical significance. Numerous definitions for, and proxy measures of, illness severity were presented in the primary literature included in this review. While this variance may have influenced results, it could not be avoided given the urgency of the COVID-19 pandemic and lack of existing evidence. This systematic review presents the features most associated with COVID-19 illness severity based on frequency and consistency of reporting publications. These findings could aid frontline providers in determining how to allocate scarce resources, namely oxygen and mechanical ventilation, in a timely and appropriate manner for the rapidly increasing volume of COVID-19 patients around the world, but especially in LRS. It is our hope that by using significant variables such as age, history of comorbidity, and dyspnoea as a presenting symptom, providers in LRS can quickly predict illness severity to guide clinical treatment and disposition of patients with COVID-19 disease. Given the urgency of the pandemic and the almost universally low-quality of data, future research collaborations with larger samples and prospective designs are critical to improving COVID-19 illness severity prediction and subsequent management. Contributors: LAW, JLP, and MB designed the study. JLP performed the database searches. JLP, KW, SS, and AVN screened articles titles and abstracts for inclusion. AF, JLP, MB, SS and AVN screened eligible full texts for inclusion. AF, JLP, MB, SH, SS, and AVN extracted data. JLP and AF crosschecked all data extractions, assessed quality of included studies, performed data analysis, and drafted the manuscript. All authors contributed to revising the manuscript and have approved of the final version. LAW is the guarantor. No funding was received for this study. Data availability statement: Additional extracted data not provided in-text or as supplementary information are available upon request. . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted April 27, 2020. . . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted April 27, 2020. . Full-text articles excluded: Did not evaluate primary data (literature review/case report/correspondence/metaanalysis) (n = 55) Significance testing not conducted for relevant variables (n = 289) Records excluded on screening (n = 5361) . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted April 27, 2020. . . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted April 27, 2020. . Other respiratory disease 2 (29) 7 Current smoker 1 (9) 11 Tuberculosis 0 (0) 3 Hepatitis/cirrhosis 0 (0) 14 Immunocompromised 0 (0) 2 *Significance denoted by p<0.05 as related to illness severity by definition specified in paper. . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted April 27, 2020. . *Significance denoted by p<0.05 as related to illness severity by definition specified in paper. **No data were available on the predictive value of abnormal auscultation. . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted April 27, 2020. 2 TITLE-ABS-KEY("severity of illness index" OR sever* OR critical* OR "patient admission" OR "length of stay" OR "critical illness" OR "critical care" OR outcome* OR mortality OR death OR morbidity OR respiratory AND insufficiency OR "respiratory distress syndrome" OR respiration OR ventilation) . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted April 27, 2020. . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. 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