Development of a scoring system for the prediction of in-hospital mortality among COVID-19 patients

The aim of this study is to develop and validate a scoring system as a tool for predicting the in-hospital mortality in COVID-19 patients in early stage of disease. This retrospective cohort study, conducted on 893 COVID-19 patients in Tehran from February 18 to July 20, 2020. Potential factors were...

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Published inClinical epidemiology and global health Vol. 12; p. 100871
Main Authors Haji Aghajani, Mohammad, Sistanizad, Mohammad, Pourhoseingholi, Asma, Asadpoordezaki, Ziba, Taherpour, Niloufar
Format Journal Article
LanguageEnglish
Published India Elsevier B.V 01.10.2021
The Authors. Published by Elsevier B.V. on behalf of INDIACLEN
Elsevier
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Summary:The aim of this study is to develop and validate a scoring system as a tool for predicting the in-hospital mortality in COVID-19 patients in early stage of disease. This retrospective cohort study, conducted on 893 COVID-19 patients in Tehran from February 18 to July 20, 2020. Potential factors were chosen via stepwise selection and multivariable logistic regression model. Cross-validation method was employed to assess the predictive performance of the model as well as the scoring system such as discrimination, calibration, and validity indices. The COVID-19 patients’ median age was 63 yrs (54.98% male) and 233 (26.09%) patients expired during the study. The scoring system was developed based on 8 selected variables: age ≥55 yrs (OR = 5.67, 95% CI: 3.25–9.91), males (OR = 1.51, 95% CI: 1.007–2.29), ICU need (OR = 16.32, 95% CI 10.13–26.28), pulse rate >90 (OR = 1.89, 95% CI: 1.26–2.83), lymphocytes <17% (OR = 2.33, 95%CI: 1.54–3.50), RBC ≤4, 10 6/L (OR = 2.10, 95% CI: 1.35–3.26), LDH >700 U/L (OR = 1.68, 95%CI: 1.13–2.51) and troponin I level >0.03 ng/mL (OR = 1.75, 95%CI: 1.17–2.62). The AUC and the accuracy of scoring system after cross-validation were 79.4% and 79.89%, respectively. This study showed that developed scoring system has a good performance and can use to help physicians for identifying high-risk patients in early stage of disease.
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ISSN:2213-3984
2452-0918
2213-3984
DOI:10.1016/j.cegh.2021.100871