Scoring system for mortality prediction of in-hospital COVID-19 patients in resource-limited settings: a single center cohort study during Delta and Omicron waves

Murti, Krisna and Liana, Phey and Liberty, Iche Andriyani and Hafy, Zen and Umar, Tungki Pratama (2023) Scoring system for mortality prediction of in-hospital COVID-19 patients in resource-limited settings: a single center cohort study during Delta and Omicron waves. Frontiers in Emergency Medicine, 7 (4). pp. 1-10. ISSN 2717-3593

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Abstract

Objective: Coronavirus Disease 2019 (COVID-19)-related mortality includes several risk variables that are country-specific in nature. The development of a scoring system is necessary regarding the appearance of novel virus variants. The objective of this research is to develop a prognostic score for COVID-19 patients in resourceconstrained settings. Methods: This study used a retrospective and prospective cohort design to identify variables that influence COVID-19 patients’ in-hospital mortality. The receiver operating characteristic (ROC) curve analysis was utilized to determine the laboratory variables cut-off. Cox regression analysis was undertaken to determine the exact variables influencing the survival of COVID-19 patients. A scoring system was created using the best model based on the Hosmer-Lemeshow test (calibration) and the area under the curve (AUC) (discrimination ability). Results: Based on calibration and discrimination testing, model 2 (immune disorders, unconsciousness, cerebrovascular disease, onset, and oxygen saturation)was rated as the most advantageous model. Model 2 (without age adjustment) had a superior AUC than model 2A (with age). Cut-off was determined at 2, and calculated for onset ¸7 days (AUC=0.816, 95% CI: 0.742,0.890) and <7 days (AUC=0.850, 95% CI: 0.784,0.916). There was no difference in scoring systemutilization for subjects recruited during Delta or Omicron waves (P=0.527). Conclusion: The model (cut-off value ¸2) which incorporated age ¸65 years, immune disorders, decreased consciousness, increased respiratory rate, and oxygen saturation <95% is the best model in our study to predict COVID-19 patient mortality. Keywords: COVID-19; Prognostic; Scoring System; Survival

Item Type:	Article
Subjects:	R Medicine > R Medicine (General) > R5-920 Medicine (General) #3 Repository of Lecturer Academic Credit Systems (TPAK) > Articles Access for TPAK (Not Open Sources)
Divisions:	04-Faculty of Medicine > 11718-Pathology Anatomy (Sp
Depositing User:	dr., Ph.D. Krisna Murti
Date Deposited:	29 Jan 2024 02:38
Last Modified:	29 Jan 2024 02:38
URI:	http://repository.unsri.ac.id/id/eprint/140074

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