Similarity result of_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) Similarity result of_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. Tehran University of Medical Sciences (TUMS) Journals Publishing House, Turnitin Universitas Sriwijaya. (Submitted)

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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:	Other
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) #3 Repository of Lecturer Academic Credit Systems (TPAK) > Results of Ithenticate Plagiarism and Similarity Checker
Divisions:	04-Faculty of Medicine > 11718-Pathology Anatomy (Sp
Depositing User:	dr., Ph.D. Krisna Murti
Date Deposited:	29 Jan 2024 03:31
Last Modified:	29 Jan 2024 03:31
URI:	http://repository.unsri.ac.id/id/eprint/140113

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