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计算机断层扫描定义的身体成分作为 2019 年冠状病毒病不良结局和住院死亡率的预后标志物。

Computed tomography-defined body composition as prognostic markers for unfavourable outcomes and in-hospital mortality in coronavirus disease 2019.

机构信息

Department of Diagnostic and Interventional Radiology, University of Leipzig, Leipzig, Germany.

Institute of Medical Epidemiology, Biostatistics, and Informatics, Martin-Luther-University Halle-Wittenberg, Halle (Saale), Germany.

出版信息

J Cachexia Sarcopenia Muscle. 2022 Feb;13(1):159-168. doi: 10.1002/jcsm.12868. Epub 2022 Jan 12.

Abstract

BACKGROUND

Low skeletal muscle mass (LSMM) and visceral fat areas can be assessed by cross-sectional images. These parameters are associated with several clinically relevant factors in various disorders with predictive and prognostic implications. Our aim was to establish the effect of computed tomography (CT)-defined LSMM and fat areas on unfavourable outcomes and in-hospital mortality in coronavirus disease 2019 (COVID-19) patients based on a large patient sample.

METHODS

MEDLINE library, Cochrane, and Scopus databases were screened for the associations between CT-defined LSMM as well as fat areas and in-hospital mortality in COVID-19 patients up to September 2021. In total, six studies were suitable for the analysis and included into the present analysis.

RESULTS

The included studies comprised 1059 patients, 591 men (55.8%) and 468 women (44.2%), with a mean age of 60.1 years ranging from 48 to 66 years. The pooled prevalence of LSMM was 33.6%. The pooled odds ratio for the effect of LSMM on in-hospital mortality in univariate analysis was 5.84 [95% confidence interval (CI) 1.07-31.83]. It was 2.73 (95% CI 0.54-13.70) in multivariate analysis. The pooled odds ratio of high visceral fat area on unfavourable outcome in univariate analysis was 2.65 (95% CI 1.57-4.47).

CONCLUSIONS

Computed tomography-defined LSMM and high visceral fat area have a relevant association with in-hospital mortality in COVID-19 patients and should be included as relevant prognostic biomarkers into clinical routine.

摘要

背景

通过横断面图像可以评估低骨骼肌量(LSMM)和内脏脂肪面积。这些参数与多种不同疾病中的多种临床相关因素相关,具有预测和预后意义。我们的目的是基于大量患者样本,确定 CT 定义的 LSMM 和脂肪面积对 2019 年冠状病毒病(COVID-19)患者不良结局和住院死亡率的影响。

方法

对 MEDLINE 库、Cochrane 和 Scopus 数据库进行筛选,以确定 CT 定义的 LSMM 以及 COVID-19 患者的脂肪面积与住院死亡率之间的关联,检索时间截至 2021 年 9 月。共有六项研究适合进行分析并纳入本分析。

结果

纳入的研究共纳入 1059 名患者,其中男性 591 名(55.8%),女性 468 名(44.2%),平均年龄为 60.1 岁,年龄范围为 48-66 岁。LSMM 的总患病率为 33.6%。在单因素分析中,LSMM 对住院死亡率的影响的合并优势比为 5.84(95%置信区间 1.07-31.83)。在多因素分析中为 2.73(95%置信区间 0.54-13.70)。在单因素分析中,高内脏脂肪面积对不良结局的合并优势比为 2.65(95%置信区间 1.57-4.47)。

结论

CT 定义的 LSMM 和高内脏脂肪面积与 COVID-19 患者的住院死亡率有相关关系,应作为相关的预后生物标志物纳入临床常规。

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