TY - JOUR
T1 - Development and validation of a simplified risk score for the prediction of critical COVID-19 illness in newly diagnosed patients
AU - the LEOSS study group
AU - Werfel, Stanislas
AU - Jakob, Carolin E.M.
AU - Borgmann, Stefan
AU - Schneider, Jochen
AU - Spinner, Christoph
AU - Schons, Maximilian
AU - Hower, Martin
AU - Wille, Kai
AU - Haselberger, Martina
AU - Heuzeroth, Hanno
AU - Rüthrich, Maria M.
AU - Dolff, Sebastian
AU - Kessel, Johanna
AU - Heemann, Uwe
AU - Vehreschild, Jörg J.
AU - Rieg, Siegbert
AU - Schmaderer, Christoph
N1 - Publisher Copyright:
© 2021 The Authors. Journal of Medical Virology Published by Wiley Periodicals LLC
PY - 2021/12
Y1 - 2021/12
N2 - Scores to identify patients at high risk of progression of coronavirus disease (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), may become instrumental for clinical decision-making and patient management. We used patient data from the multicentre Lean European Open Survey on SARS-CoV-2-Infected Patients (LEOSS) and applied variable selection to develop a simplified scoring system to identify patients at increased risk of critical illness or death. A total of 1946 patients who tested positive for SARS-CoV-2 were included in the initial analysis and assigned to derivation and validation cohorts (n = 1297 and n = 649, respectively). Stability selection from over 100 baseline predictors for the combined endpoint of progression to the critical phase or COVID-19-related death enabled the development of a simplified score consisting of five predictors: C-reactive protein (CRP), age, clinical disease phase (uncomplicated vs. complicated), serum urea, and D-dimer (abbreviated as CAPS-D score). This score yielded an area under the curve (AUC) of 0.81 (95% confidence interval [CI]: 0.77–0.85) in the validation cohort for predicting the combined endpoint within 7 days of diagnosis and 0.81 (95% CI: 0.77–0.85) during full follow-up. We used an additional prospective cohort of 682 patients, diagnosed largely after the “first wave” of the pandemic to validate the predictive accuracy of the score and observed similar results (AUC for the event within 7 days: 0.83 [95% CI: 0.78–0.87]; for full follow-up: 0.82 [95% CI: 0.78–0.86]). An easily applicable score to calculate the risk of COVID-19 progression to critical illness or death was thus established and validated.
AB - Scores to identify patients at high risk of progression of coronavirus disease (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), may become instrumental for clinical decision-making and patient management. We used patient data from the multicentre Lean European Open Survey on SARS-CoV-2-Infected Patients (LEOSS) and applied variable selection to develop a simplified scoring system to identify patients at increased risk of critical illness or death. A total of 1946 patients who tested positive for SARS-CoV-2 were included in the initial analysis and assigned to derivation and validation cohorts (n = 1297 and n = 649, respectively). Stability selection from over 100 baseline predictors for the combined endpoint of progression to the critical phase or COVID-19-related death enabled the development of a simplified score consisting of five predictors: C-reactive protein (CRP), age, clinical disease phase (uncomplicated vs. complicated), serum urea, and D-dimer (abbreviated as CAPS-D score). This score yielded an area under the curve (AUC) of 0.81 (95% confidence interval [CI]: 0.77–0.85) in the validation cohort for predicting the combined endpoint within 7 days of diagnosis and 0.81 (95% CI: 0.77–0.85) during full follow-up. We used an additional prospective cohort of 682 patients, diagnosed largely after the “first wave” of the pandemic to validate the predictive accuracy of the score and observed similar results (AUC for the event within 7 days: 0.83 [95% CI: 0.78–0.87]; for full follow-up: 0.82 [95% CI: 0.78–0.86]). An easily applicable score to calculate the risk of COVID-19 progression to critical illness or death was thus established and validated.
KW - COVID-19
KW - logistic models
KW - machine learning
KW - risk factors
UR - http://www.scopus.com/inward/record.url?scp=85112513815&partnerID=8YFLogxK
U2 - 10.1002/jmv.27252
DO - 10.1002/jmv.27252
M3 - Article
C2 - 34331717
AN - SCOPUS:85112513815
SN - 0146-6615
VL - 93
SP - 6703
EP - 6713
JO - Journal of Medical Virology
JF - Journal of Medical Virology
IS - 12
ER -