Multicenter registry of United States emergency department patients tested for SARS‐CoV‐2

Kline, Jeffrey A.; Pettit, Katherine L.; Kabrhel, Christopher; Courtney, D. Mark; Nordenholz, Kristen E.; Camargo, Carlos A.

doi:10.1002/emp2.12313

Cited by 21 publications

(60 citation statements)

References 32 publications

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“…from logistic regression) [9]. A simpler version comprising 13 binary variables, scored with negative or positive point values (the CORC score, shown in Table 3) provides similar accuracy.…”

Section: Plos Onementioning

confidence: 98%

Clinical prediction rule for SARS-CoV-2 infection from 116 U.S. emergency departments 2-22-2021

et al. 2021

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Objectives Accurate and reliable criteria to rapidly estimate the probability of infection with the novel coronavirus-2 that causes the severe acute respiratory syndrome (SARS-CoV-2) and associated disease (COVID-19) remain an urgent unmet need, especially in emergency care. The objective was to derive and validate a clinical prediction score for SARS-CoV-2 infection that uses simple criteria widely available at the point of care. Methods Data came from the registry data from the national REgistry of suspected COVID-19 in EmeRgency care (RECOVER network) comprising 116 hospitals from 25 states in the US. Clinical variables and 30-day outcomes were abstracted from medical records of 19,850 emergency department (ED) patients tested for SARS-CoV-2. The criterion standard for diagnosis of SARS-CoV-2 required a positive molecular test from a swabbed sample or positive antibody testing within 30 days. The prediction score was derived from a 50% random sample (n = 9,925) using unadjusted analysis of 107 candidate variables as a screening step, followed by stepwise forward logistic regression on 72 variables. Results Multivariable regression yielded a 13-variable score, which was simplified to a 13-point score: +1 point each for age>50 years, measured temperature>37.5°C, oxygen saturation<95%, Black race, Hispanic or Latino ethnicity, household contact with known or suspected COVID-19, patient reported history of dry cough, anosmia/dysgeusia, myalgias or fever; and -1 point each for White race, no direct contact with infected person, or smoking. In the validation sample (n = 9,975), the probability from logistic regression score produced an area under the receiver operating characteristic curve of 0.80 (95% CI: 0.79–0.81), and this level of accuracy was retained across patients enrolled from the early spring to summer of 2020. In the simplified score, a score of zero produced a sensitivity of 95.6% (94.8–96.3%), specificity of 20.0% (19.0–21.0%), negative likelihood ratio of 0.22 (0.19–0.26). Increasing points on the simplified score predicted higher probability of infection (e.g., >75% probability with +5 or more points). Conclusion Criteria that are available at the point of care can accurately predict the probability of SARS-CoV-2 infection. These criteria could assist with decisions about isolation and testing at high throughput checkpoints.

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Section: Plos Onementioning

confidence: 98%

Clinical prediction rule for SARS-CoV-2 infection from 116 U.S. emergency departments 2-22-2021

et al. 2021

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“…Information about these sites, and the methods of the initial registry, are available elsewhere. 9 The primary objective of the registry was to obtain a large sample of ED patients with suspected SARS-CoV-2 and who had a molecular test performed in the ED as part of their usual care. The design, collection, recording and analysis of data for this report were conducted in accordance with the transparency in reporting of a multivariable prediction model for individual diagnosis and prognosis (TRIPOD) criteria.…”

Section: Methodsmentioning

confidence: 99%

“…Briefly, eligibility for enrollment required that a molecular diagnostic test was ordered and performed in the ED setting with suspicion of possible SARS-CoV-2 infection, or COVID-19 disease. 9 Patients could only be enrolled once. Otherwise, there were no age or symptom-based exclusions; however, the guidance was provided to exclude patients where the test was clearly done for automated, administrative purposes in the absence of any clinical suspicion for infection.…”

Section: Methodsmentioning

confidence: 99%

“…Data were collected from the electronic medical record, using a combination of electronic download for routinely collected, coded variables (e.g., age, vital signs and laboratory values), supplemented by chart review by research personnel, using methods previously described. 9 Each data form included 204 questions resulting in 360 answers, because many questions allowed multiple answers. Data were archived in the REDCap® system, with electronic programming to ensure completion of mandatory fields and sensible ranges for parametric data.…”

Section: Methodsmentioning

confidence: 99%

“…To address these needs, the authors created the RE gistry of suspected COV ID-19 in E me R gency care (RECOVER), a national network to capture data from patients tested for SARS-CoV-2 and evaluated in the ED. 9 This report addresses the primary goal of the initial network-wide registry, which was to create a quantitative pretest probability scoring system (putatively named the COVID-19 Rule Out Criteria [CORC score]) to predict a positive SARS-CoV-2 test, and relatedly the derivation and internal validation of a simplified version that can serve as a prediction rule to identify those at very low probability of disease (the CORC rule). The intent of the rule was to function similarly to the Wells pretest probability scoring criteria and Pulmonary Embolism Rule out Criteria (PERC rule) for acute pulmonary embolism, respectively, except the diagnostic target was SARS-CoV-2.…”

Section: Introductionmentioning

confidence: 99%

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Clinical prediction rule for SARS-CoV-2 infection from 116 U.S. emergency departments

Kline

2021

Preprint

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ObjectivesAccurate and reliable criteria to rapidly estimate the probability of infection with the novel coronavirus-2 that causes the severe acute respiratory syndrome (SARS-CoV-2) and associated disease (COVID-19) remain an urgent unmet need, especially in emergency care. The objective was to derive and validate a clinical prediction rule for SARS-CoV-2 infection that uses simple criteria widely available at the point of care.MethodsData came from the Registry data from the national REgistry of suspected COVID-19 in EmeRgency care (RECOVER network) comprising 116 hospitals from 25 states in the US. Clinical predictors and 30-day outcomes were abstracted from medical records of 19,850 emergency department (ED) patients tested for SARS-CoV-2. The criterion standard for diagnosis of SARS-CoV-2 required a positive molecular test from a swabbed sample or positive antibody testing within 30 days. The prediction rule was derived from a 50% random sample (n=9,925) using unadjusted analysis of 107 candidate variables as a screening step, followed by stepwise forward logistic regression on 72 variables.ResultsMultivariable regression yielded a 13-variable score, which was simplified to 13-point rule: +1 point each for age>50 years, measured temperature>37.5°C, oxygen saturation<95%, Black race, Hispanic or Latino ethnicity, household contact with known or suspected COVID-19, patient reported history of dry cough, anosmia/dysgeusia, myalgias or fever; and -1 point each for White race, no direct contact with infected person, or smoking. In the validation sample (n=9,975), the score produced an area under the receiver operating character curve of 0.80 (95% CI: 0.79-0.81), and this level of accuracy was retained across patients enrolled from the early spring to summer of 2020. In the simplified rule, a score of zero produced a sensitivity of 95.6% (94.8-96.3%), specificity of 20.0% (19.0-21.0%), likelihood ratio negative of 0.22 (0.19-0.26). Increasing points on the simplified rule predicted higher probability of infection (e.g., >75% probability with +5 or more points).ConclusionCriteria that are available at the point of care can accurately predict the probability of SARS-CoV-2 infection. These criteria could assist with decision about isolation and testing at high throughput checkpoints.Key pointsQuestionCan clinical criteria, derived solely from interview and vital signs accurately estimate the probability of infection from the novel coronavirus (SARS-CoV-2) that causes COVID-19?FindingsFrom derivation sample (n=9,925), we derived a set of 13 clinical criteria that produced an area under the receiver operating characteristic curve of 0.80 (0.79-0.81) in a validation sample (n=9,925). At a score of zero, the simplified version of the criteria produced sensitivity of 95.6% (94.8 to 96.3%), and specificity of 20.0% (19.0 to 21.0%).MeaningClinical criteria can estimate the probability of SARS-CoV-2 infection.

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Diagnosing COVID‐19

Pines

2023

Evidence‐Based Emergency Care

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Multicenter registry of United States emergency department patients tested for SARS‐CoV‐2

Cited by 21 publications

References 32 publications

Clinical prediction rule for SARS-CoV-2 infection from 116 U.S. emergency departments 2-22-2021

Clinical prediction rule for SARS-CoV-2 infection from 116 U.S. emergency departments 2-22-2021

Clinical prediction rule for SARS-CoV-2 infection from 116 U.S. emergency departments

Diagnosing COVID‐19

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