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乌克兰外喀尔巴阡地区重症钩端螺旋体病致死率的预测因素

Predictors of lethality in severe leptospirosis in Transcarpathian region of Ukraine.

作者信息

Petakh Pavlo, Nykyforuk Andriy

机构信息

Department of Biochemistry and Pharmacology, Uzhhorod National University, Uzhhorod, Ukraine.

Department of Microbiology, Virology, and Immunology, I. Horbachevsky Ternopil National Medical University, Ternopil, Ukraine.

出版信息

Infez Med. 2022 Jun 1;30(2):272-276. doi: 10.53854/liim-3002-13. eCollection 2022.

Abstract

Leptospirosis is one of the most widespread zoonoses in the Transcarpathian region, with an average lethality of 12.5%. To determine the predictors of lethality, a retrospective study of 97 medical records of patients with leptospirosis in the period from 2009 to 2018 was conducted. Quantitative variables in the presence of normal distribution were compared using a paired Student's t-test, and in the case of an abnormal distribution, the Mann-Whitney U test was used. The criterion χ was used for qualitative variables. Multivariate analysis was used for the calculation of the Odds ratio. The following factors that are associated with death from leptospirosis have been identified: total bilirubin greater than 300 mcmol/L (OR, 4.25; 95% confidence interval [CI], 1.57-11.53), platelets less than 50 × (10/L) (OR, 3.95; 95% confidence interval [CI], 1.45-10.73), creatinine above 200 mcmol/L (OR, 1.95; 95% confidence interval [CI], 1.47-2.60) and jaundice (OR, 1.39; 95% confidence interval [CI], 1.21-1.60). Detection of these predictors will help to quickly identify a patient at risk of severe course of the disease and death, which will allow deciding on the use of early intensive care.

摘要

钩端螺旋体病是外喀尔巴阡地区最普遍的人畜共患病之一,平均致死率为12.5%。为了确定致死率的预测因素,对2009年至2018年期间97例钩端螺旋体病患者的病历进行了回顾性研究。对呈正态分布的定量变量使用配对学生t检验进行比较,对于分布异常的情况,则使用曼-惠特尼U检验。定性变量使用χ检验标准。使用多变量分析来计算优势比。已确定以下与钩端螺旋体病死亡相关的因素:总胆红素大于300 μmol/L(优势比,4.25;95%置信区间[CI],1.57 - 11.53)、血小板少于50×(10⁹/L)(优势比,3.95;95%置信区间[CI],1.45 - 10.73)、肌酐高于200 μmol/L(优势比,1.95;95%置信区间[CI],1.47 - 2.60)和黄疸(优势比,1.39;95%置信区间[CI],1.21 - 1.60)。检测这些预测因素将有助于快速识别有疾病严重病程和死亡风险的患者,从而能够决定是否使用早期重症监护。

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