G-1648

2025-10-19 17:25

Written by ARCIMS 26 ARCIMS 26 in Sunday 2025-10-19 17:25

Associated factors with patient s admission status between covid-19 patients in a hospital-based cohort study using multi-state survival models

 Shima Aminzadeh 1 ℗, Marjan Mansourian 2 ©   

 PhD Student, Student Research Committee, Department of Biostatistics and Epidemiology, School of Health, Isfahan University of Medical Sciences, Isfahan, Iran

 Department of Biostatistics and Epidemiology, School of Health, Isfahan University of Medical Sciences, Isfahan, Iran

Email: shima.aminzadeh.biostat@gmail.com
 

 


 
Abstract

Introduction: Multi-state models are one of the most common models used to describe the process and progression path in survival studies. At any point in time, an individual adopts one of a set of discrete states and may transition from one state to another over time. The analytical complexity of these models depends on the number of defined states and the number of possible transitions between states. The aim of these models is to provide a comprehensive view of the disease process or life history of an individual. Therefore, in this study, we modeled the factors related to the change in the status of patients with COVID-19 infectious disease by using multi-state survival models. Methods and Materials: In the present study, data from 634 patients with COVID-19 hospitalized in Khorshid Hospital of Isfahan were used to model multi-state survival. The progression of the patients' disease was examined in four states (general ward hospitalization, ICU hospitalization, discharge, and death). Data analysis was performed in two-state models using the Cox Markov proportional hazards regression model and in models with more than two states using the Cox Markov stratified regression model to achieve the desired results. Results: This study included 389 (61%) men and 245 (39%) women, with a mean age of 57 (15.41) years. The median and mean hospital stay for patients until discharge were 5 and 9 days, respectively. According to these models, middle-aged men who smoked had some important blood factors such as platelet levels, sodium levels, potassium levels, magnesium levels, inflammatory factors, and liver factors, along with underlying diseases such as diabetes, hypertension, cardiovascular diseases, and respiratory diseases, at higher risk for admission to intensive care units and even death (p-value 0.001). These factors also had an increased relative risk compared to their reference category (HR 1). The probability of transferring from a general inpatient ward to discharge was higher than that of discharging from an ICU at all times. The probability of transferring from an ICU to death was also higher than that of transferring from a general inpatient ward at all times. Conclusion and Discussion: The results of this study show that elderly people, men, smokers, patients with underlying diseases such as hypertension, diabetes, respiratory and cardiovascular patients are at risk of hospitalization due to COVID-19, transfer to intensive care and death. Multiple underlying diseases are a predisposing factor for high mortality. It is recommended that these individuals receive more attention from relevant specialists. These individuals should be monitored and screened frequently.


Keywords: Survival Analysis, Multi-State Models, COVID-19

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