TY  - JOUR
A1  - Werfel, Stanislas
A1  - Jakob, Carolin Ellen Marianne
A1  - Borgmann, Stefan
A1  - Schneider, Jochen
A1  - Spinner, Christoph Daniel
A1  - Schons, Maximilian
A1  - Hower, Martin
A1  - Wille, Kai
A1  - Haselberger, Martina Maria
A1  - Heuzeroth, Hanno
A1  - Rüthrich, Maria Madeleine
A1  - Dolff, Sebastian Conrad Johannes
A1  - Kessel, Johanna
A1  - Heemann, Uwe
A1  - Vehreschild, Jörg Janne
A1  - Rieg, Siegbert
A1  - Schmaderer, Christoph
T1  - Development and validation of a simplified risk score for the prediction of critical COVID-19 illness in newly diagnosed patients
T2  - Journal of medical virology
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.
KW  - COVID‐19
KW  - logistic models
KW  - machine learning
KW  - risk factors
Y1  - 2021
UR  - http://publikationen.ub.uni-frankfurt.de/frontdoor/index/index/docId/63957
UR  - https://nbn-resolving.org/urn:nbn:de:hebis:30:3-639578
SN  - 1096-9071
N1  - Funding information: German Centre for Infection Research; Willy Robert Pitzer Foundation
VL  - 93
IS  - 12
SP  - 6703
EP  - 6713
PB  - Wiley
CY  - Bognor Regis [u.a.]
ER  -