Dentistry Clinical Research Development Center, Birjand University of Medical Sciences, Birjand, Iran.
Infectious disease Research center, Birjand University of Medical Sciences, Birjand, Iran.
Disaster Med Public Health Prep. 2022 Aug 18;17:e233. doi: 10.1017/dmp.2022.193.
The survival cox analysis is becoming more popular in time-to-event data analysis. When there are unobserved /unmeasured individual factors, then the results of this model may not be dependable. Hence, this study aimed to determine the factors associated with Covid-19 patients' survival time with considering frailty factor.
This study was conducted at 1 of the hospitals in Iran, so that hospitalized patients with COVID-19 were included. Epidemiological, clinical, laboratory, and outcome data on admission were extracted from electronic medical records. Gamma-frailty Cox model was used to identify the effects of the risk factors.
A total of 360 patients with COVID-19 enrolled in the study. The median age was 74 years (IQR 61 - 83), 903 (57·7%) were men, and 661 (42·3%) were women; the mortality rate was 17%. The Cox frailty model showed that there is at least a latent factor in the model ( = 0.005). Age and platelet count were negatively associated with the length of stay, while red blood cell count was positively associated with the length of stay of patients.
The Cox frailty model indicates that in addition to age, the frailty factor is a useful predictor of survival in Covid-19 patients.
生存 Cox 分析在时间事件数据分析中越来越流行。当存在未观察到/未测量的个体因素时，该模型的结果可能不可靠。因此，本研究旨在确定与考虑脆弱因素的新冠患者生存时间相关的因素。
本研究在伊朗的 1 家医院进行，纳入了住院的新冠患者。从电子病历中提取入院时的流行病学、临床、实验室和结局数据。使用伽马脆弱 Cox 模型来确定风险因素的影响。
共纳入 360 例新冠患者。中位年龄为 74 岁（IQR 61-83），903 例（57.7%）为男性，661 例（42.3%）为女性；死亡率为 17%。Cox 脆弱模型表明模型中至少存在一个潜在因素（ = 0.005）。年龄和血小板计数与住院时间呈负相关，而红细胞计数与患者住院时间呈正相关。
Cox 脆弱模型表明，除年龄外，脆弱因素是新冠患者生存的有用预测因子。
