key: cord-0275154-v8tzpr84 authors: Davis, P.; Rosychuk, R. J.; Hau, J. P.; Cheng, I.; McRae, A. D.; Daoust, R.; Lang, E.; Turner, J.; Khangura, J.; Fok, P. T.; Stachura, M.; Brar, B.; Hohl, C. M. title: Diagnostic Yield of Screening for SARS-CoV-2 among Patients Admitted for Alternate Diagnoses date: 2021-09-27 journal: nan DOI: 10.1101/2021.09.23.21264036 sha: 8e727b649adcb5b342733dd13236590132cc7602 doc_id: 275154 cord_uid: v8tzpr84 Objectives: To determine the diagnostic yield of screening patients for SARS-CoV-2 who were admitted with a diagnosis unrelated to COVID-19, and identify risk factors for positive tests. Design: Cohort from the Canadian COVID-19 Emergency Department Rapid Response Network (CCEDRRN) registry Setting: 30 acute care hospitals across Canada Participants: Patients hospitalized for non-COVID-19 related diagnoses who were tested for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) between March 1, and December 29, 2020 Main outcome: Positive nucleic acid amplification test (NAAT) for SARS-CoV-2 Outcome measure: Diagnostic yield Results: We enrolled 15,690 consecutive eligible adults who were admitted to hospital without clinically suspected COVID-19. Among these patients, 122 tested positive for COVID-19, resulting in a diagnostic yield of 0.8% (95% CI 0.64% - 0.92%). Factors associated with a positive test included presence of a fever, being a healthcare worker, having a positive household contact or institutional exposure, and living in an area with higher 7-day average incident COVID-19 cases. Conclusions: Universal screening of hospitalized patients for COVID-19 across two pandemic waves had a low diagnostic yield and should be informed by individual-level risk assessment in addition to regional COVID-19 prevalence. Section 1: Universal screening of admitted patients for SARS-CoV-2 was implemented in many hospitals at the beginning of the pandemic. The Infections Diseases Society of America (IDSA) recommended avoiding universal screening of asymptomatic hospitalized patients in areas and times of low-COVID prevalence (defined as <2% prevalence) with very low certainty of evidence, based on studies of COVID-19 prevalence among asymptomatic individuals in the community. This study supports IDSA recommendations to avoid universal screening for COVID-19 in times and areas of low COVID prevalence and identifies patient-level risk factors strongly associated with positive testing that should be considered for screening. Healthcare institutions initiated widespread testing of admitted patients for coronavirus disease 2019 in the spring of 2020 (1) . Patients without any reported symptoms of COVID-19 were routinely tested even in jurisdictions where COVID-19 rates were low in order to identify asymptomatic carriers and prevent hospital outbreaks (2) . Some jurisdictions have continued this practice without robust evidence to support this practice. An Alberta study of 3,375 patients admitted to hospital for alternate diagnoses during the first wave of the pandemic when COVID-19 prevalence was very low found that CCEDRRN has an active patient engagement committee with patient partners who have lived experience with COVID-19 from geographically representative areas of Canada. Patient partners provided input into the development of this research question and study protocol and the final manuscript. Participating sites needed to demonstrate >99% compliance in enrolling consecutive eligible patients for their data to be included in this study. Data from sites and periods that did not meet this quality threshold were excluded. We included consecutive eligible patients who were admitted to hospital and swabbed for SARS-CoV-2 using a nucleic acid amplification test (NAAT) within 24 hours of ED arrival. We enrolled patients between March 1, 2020 and December 29, 2020. To identify a population of admitted patients in whom COVID-19 disease was not suspected, we excluded patients with ED diagnoses that would have been clinically suspicious for COVID-19. These included all patients with ED diagnoses of suspected or confirmed COVID-19, influenza-like-illness (ILI), upper respiratory infections, and pneumonia or viral pneumonia for which testing would have been indicated based on clinical suspicion. We excluded patients who were discharged directly from the ED, diagnosed with COVID-19 before ED arrival (based on a NAAT done in the community), those whose first swab occurred more than 24 hours after their arrival, and repeat admissions. We also excluded patients in whom initial SARS-CoV-2 testing was negative and repeat testing became positive more than 5 days after arrival, as these patients could have contracted nosocomial COVID. Trained research assistants collected data retrospectively from electronic and/or paper-based medical records into a central, web-based REDCap database (Vanderbilt University; Nashville, TN, USA). Research assistants captured demographics, infection risk, ED vital signs, presenting symptoms, comorbid conditions and the results of COVID-19 tests. The coordinating centre implemented regular data quality checks, including logic checks in REDCap as well as site-level record verifications for nonsensical or outlying values. In addition to these clinical variables, we calculated the seven-day moving average incident COVID-19 case count for the health region of each participating site using publicly available epidemiological data (14) . For each calendar day within each health region represented in the study, we calculated the average daily incident rate of new infections per 100,000 population over the preceding seven days. This sevenday moving average incidence was assigned to each patient based on the date of their index emergency department encounter and the health region of their postal code of residence. We allocated patients with no fixed address to the health region of the hospital in which they were tested. We imputed values for the first five weeks of the pandemic by modeling the reported COVID-19 cases that had accumulated in every health region over time using linear interpolation (0.1% missing), COVID-19 case data were not publicly available for the early pandemic. The seven-day moving average incident COVID-19 case count was categorized as 0 -1.99 per 100,000 population, 2 -7.99 per 100,000 population, and ≥ 8 per 100,000 population based on the relationship between incidence and COVID-19 positive results in a previous analysis (15). The primary outcome was a positive NAAT for SARS-CoV-2 in patients admitted with non-COVIDrelated diagnoses. We divided the cohort into two groups, those without symptoms of COVID-19 and those with symptoms compatible with COVID-19 that were attributed to an alternate diagnosis (i.e., CHF, COPD, Asthma, etc.). We considered cough, dyspnea, fever, general weakness, chest pain, diarrhea, nausea and vomiting, headache, chills, myalgia, sore throat, altered level of consciousness, and dysgeusia/anosmia to be COVID-19-compatible symptoms. We used descriptive statistics to describe the population. We calculated the diagnostic yield by dividing the number of positive NAATs over the total number of NAATs performed. We calculated the exact binomial proportion 95% confidence intervals (95% CI) for all proportions and used the modified Clopper-Pearson interval for small samples. We completed a planned subgroup analyses for patients presenting with and without COVID compatible symptoms to determine associated factors for a positive test. The initial multivariable logistic regression model to identify factors associated with a positive NAAT considered candidate variables with a p-value cut-off point of 0.20 based on the Wald test from univariable analyses. From the full model, a step-down procedure reduced the model to key predictors based on Akaike's information criterion (AIC) scores (e.g., chose the model with the smallest AIC score). Candidate variables included seven-day moving average incident COVID-19 case count category, patient age, gender, infection risk, and presenting symptoms. We limited the number of predictor variables in the model to one variable for every 10 outcomes in our data to avoid overfitting. Statistical analysis was preformed using Stata (Version 16.1, StataCorp, College Station, Texas). We identified 19,791 patients admitted to hospital who presented to a participating ED between March 1, 2020, and December 29, 2020 ( Figure 1 ). We excluded 4,101 patients, of which 2,769 had ED diagnoses that were clinically suspicious for COVID-19 and warranted SARS-CoV-2 testing on clinical grounds. The final cohort contained 15,690 patients. During the study period Canada experienced two pandemic waves with the local 7-day average incident case count ranging from between 0 and 42.6 cases per 100,000 population across sites. We divided the cohort into two groups, those without any COVID-19 compatible symptoms, and those with COVID-19 compatible symptoms that were attributed to an alternate diagnosis in the ED (Table 1) . Most patients arrived from home and were full code. The most common comorbidities were hypertension, diabetes and mental health illness. Of 3,113 patients admitted without COVID-19 compatible symptoms, 13 (0.4%, 95% CI 0.19% -0.64%) tested positive for COVID-19. Of the 12,570 with COVID-19-compatible symptoms, 109 patients (0.9%, 95% CI 0.70% -1.03%) tested positive for COVID-19. Among the 122 individuals who tested positive for COVID-19, 33 (27.0%, 95% CI 19.0% -35.0%) were from a geographic region that had a moving average daily incident rate of ≥ 8 infections per 100,000 population. The diagnostic yield of testing among patients with COVID-19 compatible symptoms admitted for alternative diagnoses did not vary substantially by presenting symptom (Figure 2 ) or ED diagnosis ( Figure 3 ). When examining the association between patient factors and screening positive self-reported fever, being a healthcare worker, having a positive household contact or institutional exposure, and being from an area where the seven-day moving average incident COVID-19 case count was ≥ 8 per 100,000 population were associate with a greater risk of testing positive. The most important risk factor was reporting a household contact or being the caregiver of a known COVID-19 case. Our aim was to evaluate the diagnostic yield of screening non-COVID-19 admissions for SARS-CoV-2 across Canada in 2020 and identify patient-level risk factors for positive tests. The diagnostic yield of screening patients with non-COVID-19 related ED diagnoses who were admitted to hospital was low overall, and extremely low in patients without COVID compatible symptoms. The most important patient factors associated with a positive test were having a positive household contact, being a healthcare worker, or having had an institutional exposure to COVID-19. Those factors were more important that a high (≥8 daily cases per 100,000 population) 7-day moving average incident COVID-19 case count. Our study has several strengths. We used data from a large pan-Canadian registry that enrolls from large geographically and culturally diverse areas and is one of the largest registries in the world. CCEDRRN's patient enrolment and data verification protocols are rigorous, ensuring consecutive eligible patients and high-quality clinical data (13). We have previously demonstrated the inter-rater reliability for our data collection methods, including for symptoms (13). Prior studies have examined the diagnostic yield of universal screening in single centers with varied diagnostic yield estimates between 0 and 15.5% (3) (4) (5) (6) (7) (8) . Many of these were case series with limited methods from the early pandemic. There is one known multi-center study which examines the benefit of universal screening for elective and emergent surgical admissions at 14 centers in the Netherlands (1). Like our study, the authors found that the overall COVID-19 NAAT positivity varied with community prevalence. Our finding that positive SARS-CoV-2 tests were associated with self-reported or measured fever is in keeping with a prior Cochrane systematic review that noted considerable variability in COVID-19 associated symptoms (17). Our study is interesting in the context of the IDSA recommendations which were based on expert opinion and of "very low certainty" (12) . The IDSA panel recommended avoiding universal screening for COVID-19 in times and areas of low COVID prevalence, defined as a disease prevalence of under 2% , or fewer than 2,000 active cases per 100,000 population, a threshold so high that it was never met at any of our study sites, even though multiple sites were in COVID-19 hotspots in 2020 (12) . This threshold would have equated to over 6 million cases of active COVID-19 infection in the United States at any given time, which would have vastly overwhelmed hospital capacity, and thus represents an untenable threshold for hospitals. It is therefore not surprising that the prevalence of COVID-19 during the study period was far below the IDSA recommended threshold for initiating screening. While the number needed to screen to identify one positive case among admitted patients in our study was between 110 and 250 among unvaccinated patients, we propose that the IDSA screening threshold likely needs to be adopted. A limitation of our study is that we only considered NAATs and did not consider the diagnostic yield of antigen-based COVID-19 tests, as they were not widespread in Canada in 2020 (16). We were unable to examine the sensitivity and specificity of the SARS-CoV-2 NAATs as we were unable to define false positive tests, so it is possible that some of the positive test results we encountered are false positives, leading to an overestimation of diagnostic yield. While our study is based on a Canadian population without international sites, we believe our findings are generalizable given their wide geographic spread, and the cultural and racial diversity of our patient population. Finally, as data becomes available on the fourth wave of the pandemic, a future study should examine the impact of widespread vaccination on the yield of screening. As a larger proportion of the population is protected from severe disease and death through vaccination, decision makers should carefully consider the low diagnostic yield of a universal testing strategy going forward. We gratefully acknowledge the assistance of Mr. Rajan Bola in the preparation of this manuscript. And we thank the UBC clinical coordinating center staff, the UBC legal, ethics, privacy and contract staff and the research staff at each of the participating institutions in the network outlined in the attached Supplement (Supplement Tables 1-4 ). The network would not exist today without the dedication of these professionals. Thank you to all of our patient partners who shared their lived experiences and perspectives to ensure that the knowledge we co-create addresses the concerns of patients and the public. Creating the largest network of collaboration across Canadian Emergency Departments would not have been feasible without the tireless efforts of Emergency Department Chiefs, and research coordinators and research assistants at participating sites. Finally, our most humble and sincere gratitude to our colleagues in medicine, nursing, and the allied health professions who have been on the front lines of this pandemic from day one staffing our ambulances, Emergency Departments, hospitals and ICUs bravely facing the risks of COVID-19 to look after our fellow citizens and after one another. We dedicate this network to you. None identified. All rights reserved. No reuse allowed without permission. preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission. preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. V I D -1 9 c o m p a t i b l e s y m p t o m s ( N = 3 , 1 1 3 ) P a t i e n t s w i t h C O V I D -1 9 c o m p a t i b l e s y m p t o m s a t t r i b u t e d t o a n a l t e r n a t e d i a g n o s i s ( N = 1 preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. A p p e n d i x A : L i s t o f h o s p i t a l s i t e s , w i t h a n i n c l u s i o n s t a r t a n d e n d d a t e f o r t h i s s t u d y . S i t e N a m e P r o v i n c e S t a r t D a t e E n d D a t e V a n c o u v e r G e n e r a l H o s p i t a l B r i t i s h C o l u m b i a 1 -M a r -2 0 2 0 3 1 -A u g -2 0 2 0 L i o n s G a t e H o s p i t a l B r i t i s h C o l u m b i a 1 -M a r -2 0 2 0 2 9 -A p r -2 0 preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. 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