Clinical prediction rule for SARS-CoV-2 infection from 116 U.S. emergency departments
Authors: Kline Jeffrey A. , Camargo Carlos A. , Courtney D. Mark , Kabrhel Christopher , Nordenholz Kristen E. , Aufderheide Thomas , Baugh Joshua , Beiser David , Bennett Christopher , Bledsoe Joseph , Castillo Edward , Chisholm-Straker Makini , Goldberg Elizabeth , House Hans , House Stacey , Jang Timothy , Kabrhel Chris , Lim Stephen , Madsen Troy , McCarthy Danielle , Meltzer Andrew , Moore Stephen , Newgard Craig , Pagenhardt Justine , Pettit Katherine L. , Pulia Michael , Puskarich Michael , Southerland Lauren , Sparks Scott , Turner-Lawrence Danielle , Vrablik Marie , Wang Alfred , Weekes Anthony , Westafer Lauren , Wilburn John 
Published: January 2021

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 rule 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 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.

Results

Multivariable 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).

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 decision about isolation and testing at high throughput checkpoints.

Key points

Question

Can 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?

Findings

From 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%).

Meaning

Clinical criteria can estimate the probability of SARS-CoV-2 infection.