Azarkar Ghodsiyeh, Osmani Freshteh
Department of Biostatistics and Epidemiology, Faculty of Health, Birjand University of Medical Sciences, Birjand, Iran.
Infectious Disease Research Center, Birjand University of Medical Sciences, Birjand, Iran.
Eur J Med Res. 2021 Jul 21;26(1):79. doi: 10.1186/s40001-021-00553-3.
The coronavirus disease 2019(COVID-19) has affected mortality worldwide. The Cox proportional hazard (CPH) model is becoming more popular in time-to-event data analysis. This study aimed to evaluate the clinical characteristics in COVID-19 inpatients including (survivor and non-survivor); thus helping clinicians give the right treatment and assess prognosis and guide the treatment.
This single-center study was conducted at Hospital for COVID-19 patients in Birjand. Inpatients with confirmed COVID-19 were included. Patients were classified as the discharged or survivor group and the death or non-survivor group based on their outcome (improvement or death). Clinical, epidemiological characteristics, as well as laboratory parameters, were extracted from electronic medical records. Independent sample T test and the Chi-square test or Fisher's exact test were used to evaluate the association of interested variables. The CPH model was used for survival analysis in the COVID-19 death patients. Significant level was set as 0.05 in all analyses.
The results showed that the mortality rate was about (17.4%). So that, 62(17%) patients had died due to COVID-19, and 298 (83.6%) patients had recovered and discharged. Clinical parameters and comorbidities such as oxygen saturation, lymphocyte and platelet counts, hemoglobin levels, C-reactive protein, and liver and kidney function, were statistically significant between both studied groups. The results of the CPH model showed that comorbidities, hypertension, lymphocyte counts, platelet count, and C-reactive protein level, may increase the risk of death due to the COVID-19 as risk factors in inpatients cases.
Patients with, lower lymphocyte counts in hemogram, platelet count and serum albumin, and high C-reactive protein level, and also patients with comorbidities may have more risk for death. So, it should be given more attention to risk management in the progression of COVID-19 disease.
2019年冠状病毒病(COVID-19)已影响全球死亡率。Cox比例风险(CPH)模型在事件发生时间数据分析中越来越受欢迎。本研究旨在评估COVID-19住院患者(包括幸存者和非幸存者)的临床特征;从而帮助临床医生进行正确的治疗、评估预后并指导治疗。
本单中心研究在比尔詹德的COVID-19患者医院进行。纳入确诊为COVID-19的住院患者。根据患者的结局(好转或死亡)将其分为出院或存活组以及死亡或非存活组。从电子病历中提取临床、流行病学特征以及实验室参数。采用独立样本T检验和卡方检验或Fisher精确检验来评估感兴趣变量之间的关联。CPH模型用于COVID-19死亡患者的生存分析。所有分析的显著性水平设定为0.05。
结果显示死亡率约为(17.4%)。即,62名(17%)患者死于COVID-19,298名(83.6%)患者康复出院。两组研究对象在临床参数和合并症方面,如血氧饱和度、淋巴细胞和血小板计数、血红蛋白水平、C反应蛋白以及肝肾功能,差异具有统计学意义。CPH模型结果显示,合并症、高血压、淋巴细胞计数、血小板计数和C反应蛋白水平,可能作为住院患者因COVID-19死亡的危险因素增加死亡风险。
血常规中淋巴细胞计数、血小板计数和血清白蛋白较低,C反应蛋白水平较高的患者,以及患有合并症的患者可能有更高的死亡风险。因此,在COVID-19疾病进展过程中应更加重视风险管理。