TY  - JOUR
AU  - Appel, Katharina S
AU  - Geisler, Ramsia
AU  - Maier, Daniel
AU  - Miljukov, Olga
AU  - Hopff, Sina M
AU  - Vehreschild, Jörg J
TI  - A Systematic Review of Predictor Composition, Outcomes, Risk of Bias, and Validation of COVID-19 Prognostic Scores.
JO  - Clinical infectious diseases
VL  - 78
IS  - 4
SN  - 1058-4838
CY  - Oxford
PB  - Oxford Journals
M1  - DKFZ-2023-02170
SP  - 889-899
PY  - 2024
N1  - 2024 Apr 10;78(4):889-899
AB  - Numerous prognostic scores have been published to support risk stratification for patients with Coronavirus disease 2019 (COVID-19).We performed a systematic review to identify the scores for confirmed or clinically assumed COVID-19 cases. An in-depth assessment and risk of bias (ROB) analysis (Prediction model Risk Of Bias ASsessment Tool (PROBAST)) was conducted for scores fulfilling predefined criteria ((I) area under the curve (AUC) ≥ 0.75; (II) a separate validation cohort present; (III) training data from a multicenter setting (≥ 2 centers); (IV) point-scale scoring system).Out of 1,522 studies extracted from MEDLINE/Web of Science (20/02/2023), we identified 242 scores for COVID-19 outcome prognosis (mortality 109, severity 116, hospitalization 14, long-term sequelae 3). Most scores were developed using retrospective (75.2
KW  - COVID-19 (Other)
KW  - Pandemic preparedness (Other)
KW  - Prediction models (Other)
KW  - Predictors (Other)
KW  - Scores (Other)
LB  - PUB:(DE-HGF)16
C6  - pmid:37879096
DO  - DOI:10.1093/cid/ciad618
UR  - https://inrepo02.dkfz.de/record/284986
ER  -