tetano
Editor, Senior Moderator
PLoS One
. 2021 Mar 10;16(3):e0248438.
doi: 10.1371/journal.pone.0248438. eCollection 2021.
Clinical prediction rule for SARS-CoV-2 infection from 116 U.S. emergency departments 2-22-2021
Jeffrey A Kline[SUP] 1 [/SUP], Carlos A Camargo Jr[SUP] 2 [/SUP], D Mark Courtney[SUP] 3 [/SUP], Christopher Kabrhel[SUP] 2 [/SUP], Kristen E Nordenholz[SUP] 4 [/SUP], Thomas Aufderheide[SUP] 5 [/SUP], Joshua J Baugh[SUP] 2 [/SUP], David G Beiser[SUP] 6 [/SUP], Christopher L Bennett[SUP] 7 [/SUP], Joseph Bledsoe[SUP] 8 [/SUP], Edward Castillo[SUP] 9 [/SUP], Makini Chisolm-Straker[SUP] 10 [/SUP], Elizabeth M Goldberg[SUP] 11 [/SUP], Hans House[SUP] 12 [/SUP], Stacey House[SUP] 13 [/SUP], Timothy Jang[SUP] 14 [/SUP], Stephen C Lim[SUP] 15 [/SUP], Troy E Madsen[SUP] 16 [/SUP], Danielle M McCarthy[SUP] 17 [/SUP], Andrew Meltzer[SUP] 18 [/SUP], Stephen Moore[SUP] 19 [/SUP], Craig Newgard[SUP] 20 [/SUP], Justine Pagenhardt[SUP] 21 [/SUP], Katherine L Pettit[SUP] 1 [/SUP], Michael S Pulia[SUP] 22 [/SUP], Michael A Puskarich[SUP] 23 [/SUP], Lauren T Southerland[SUP] 24 [/SUP], Scott Sparks[SUP] 25 [/SUP], Danielle Turner-Lawrence[SUP] 26 [/SUP], Marie Vrablik[SUP] 27 [/SUP], Alfred Wang[SUP] 1 [/SUP], Anthony J Weekes[SUP] 28 [/SUP], Lauren Westafer[SUP] 29 [/SUP], John Wilburn[SUP] 30 [/SUP]
Affiliations
Abstract
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.
. 2021 Mar 10;16(3):e0248438.
doi: 10.1371/journal.pone.0248438. eCollection 2021.
Clinical prediction rule for SARS-CoV-2 infection from 116 U.S. emergency departments 2-22-2021
Jeffrey A Kline[SUP] 1 [/SUP], Carlos A Camargo Jr[SUP] 2 [/SUP], D Mark Courtney[SUP] 3 [/SUP], Christopher Kabrhel[SUP] 2 [/SUP], Kristen E Nordenholz[SUP] 4 [/SUP], Thomas Aufderheide[SUP] 5 [/SUP], Joshua J Baugh[SUP] 2 [/SUP], David G Beiser[SUP] 6 [/SUP], Christopher L Bennett[SUP] 7 [/SUP], Joseph Bledsoe[SUP] 8 [/SUP], Edward Castillo[SUP] 9 [/SUP], Makini Chisolm-Straker[SUP] 10 [/SUP], Elizabeth M Goldberg[SUP] 11 [/SUP], Hans House[SUP] 12 [/SUP], Stacey House[SUP] 13 [/SUP], Timothy Jang[SUP] 14 [/SUP], Stephen C Lim[SUP] 15 [/SUP], Troy E Madsen[SUP] 16 [/SUP], Danielle M McCarthy[SUP] 17 [/SUP], Andrew Meltzer[SUP] 18 [/SUP], Stephen Moore[SUP] 19 [/SUP], Craig Newgard[SUP] 20 [/SUP], Justine Pagenhardt[SUP] 21 [/SUP], Katherine L Pettit[SUP] 1 [/SUP], Michael S Pulia[SUP] 22 [/SUP], Michael A Puskarich[SUP] 23 [/SUP], Lauren T Southerland[SUP] 24 [/SUP], Scott Sparks[SUP] 25 [/SUP], Danielle Turner-Lawrence[SUP] 26 [/SUP], Marie Vrablik[SUP] 27 [/SUP], Alfred Wang[SUP] 1 [/SUP], Anthony J Weekes[SUP] 28 [/SUP], Lauren Westafer[SUP] 29 [/SUP], John Wilburn[SUP] 30 [/SUP]
Affiliations
- PMID: 33690722
- DOI: 10.1371/journal.pone.0248438
Abstract
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.