Risk Factors Associated with Hospital Mortality: Analysis of the Length ofStay Using Risk Prediction Cox Regression Non-Proportional Hazard Model  

作　　者：Mawahib Mohamed Abdelgayoum Ahmed Ahmed Elfaham Ahmed Asad Ahmed Alsaeidi Mohamed Shoukri Mawahib Mohamed Abdelgayoum Ahmed;Ahmed Elfaham;Ahmed Asad;Ahmed Alsaeidi;Mohamed Shoukri(Department of Accidents and Emergency Medicine, Barking Havering and Redbridge University Hospitals Trust Romford, London, UK;Department of Epidemiology and Biostatistics, University of Western Ontario, London, Ontario, Canada)

机构地区：[1]Department of Accidents and Emergency Medicine, Barking Havering and Redbridge University Hospitals Trust Romford, London, UK [2]Department of Epidemiology and Biostatistics, University of Western Ontario, London, Ontario, Canada

出　　处：《Open Journal of Emergency Medicine》2024年第4期156-168,共13页急诊医学(英文)

摘　　要：Background: In-hospital mortality is a key indicator of the quality of care. Studies so far have demonstrated the influence of patient and hospital-related factors on in-hospital mortality. Currently, new variables, such as components of metabolic syndrome as comorbid conditions, are being incorporated as independent risk factors. We aimed to identify which individual, clinical and hospital characteristics are related to hospital mortality. Objectives: Demonstrate that the Cox proportional hazard model is not appropriate for the analysis of hospital mortality data when diagnostic-related groups are incorporated in the covariate structure. Methods: A retrospective single-center observational study design was used. Sampling was conducted between January 2016 and December 2018. Patients over 10 years, admitted to the emergency department with a precited stay of at least 1 hour were included. Multivariate Cox regression for survival data analyses was employed to analyze the data. Results: The sample consisted of 5897 patients. The mean age of all patients was 32.21 ± 0.29 years old, and the mean length of stay (LOS) was 9.47 ± 0.16 hours. We also categorized patients according to five Diagnosis Related Groups (DGR). Among the patients,1308 suffered from acute leukemia, 1127 had endocrine diseases, 1173 with kidney diseases, and 1016 had respiratory problems. At least one component of metabolic syndrome was present in 27.5% of the patients. During the observation period, 2299 (39%) died in hospital, and 3598 (61%) were discharged alive. We used the multivariate Cox regression non-proportional hazard model to evaluate the joint effect of these factors on the “Length of Stay” or LOS (the dependent variable of Cox regression). Age at admission, the presence of metabolic syndrome, and the DRG were significantly associated with the LOS.Background: In-hospital mortality is a key indicator of the quality of care. Studies so far have demonstrated the influence of patient and hospital-related factors on in-hospital mortality. Currently, new variables, such as components of metabolic syndrome as comorbid conditions, are being incorporated as independent risk factors. We aimed to identify which individual, clinical and hospital characteristics are related to hospital mortality. Objectives: Demonstrate that the Cox proportional hazard model is not appropriate for the analysis of hospital mortality data when diagnostic-related groups are incorporated in the covariate structure. Methods: A retrospective single-center observational study design was used. Sampling was conducted between January 2016 and December 2018. Patients over 10 years, admitted to the emergency department with a precited stay of at least 1 hour were included. Multivariate Cox regression for survival data analyses was employed to analyze the data. Results: The sample consisted of 5897 patients. The mean age of all patients was 32.21 ± 0.29 years old, and the mean length of stay (LOS) was 9.47 ± 0.16 hours. We also categorized patients according to five Diagnosis Related Groups (DGR). Among the patients,1308 suffered from acute leukemia, 1127 had endocrine diseases, 1173 with kidney diseases, and 1016 had respiratory problems. At least one component of metabolic syndrome was present in 27.5% of the patients. During the observation period, 2299 (39%) died in hospital, and 3598 (61%) were discharged alive. We used the multivariate Cox regression non-proportional hazard model to evaluate the joint effect of these factors on the “Length of Stay” or LOS (the dependent variable of Cox regression). Age at admission, the presence of metabolic syndrome, and the DRG were significantly associated with the LOS.

关 键 词：Diagnostic Related Groups Length of Stay Metabolic Syndrome Multivariate Cox-Regression Model Schoenfeld Residuals Deviance Residuals 

分 类 号：R73[医药卫生—肿瘤]