Suppr超能文献

计算机断层扫描评估的心脏脂肪组织体积是 2 型糖尿病 COVID-19 患者早期死亡和重症的特异性和独立预测因子。

Cardiac adipose tissue volume assessed by computed tomography is a specific and independent predictor of early mortality and critical illness in COVID-19 in type 2-diabetic patients.

机构信息

Sorbonne Université, Unité d'imagerie cardiovasculaire et thoracique, Hôpital La Pitié Salpêtrière (AP-HP), Laboratoire d'Imagerie Biomédicale, INSERM, CNRS, Institute of Cardiometabolism and Nutrition, Paris, France, Paris, France.

Sorbonne Université, Département de diabétologie, Hôpital La Pitié Salpêtrière (AP-HP), Institute of Cardiometabolism and Nutrition, Paris, France, Paris, France.

出版信息

Cardiovasc Diabetol. 2022 Dec 31;21(1):294. doi: 10.1186/s12933-022-01722-2.

Abstract

BACKGROUND

Patients with type 2-diabetes mellitus (T2D), are characterized by visceral and ectopic adipose tissue expansion, leading to systemic chronic low-grade inflammation. As visceral adiposity is associated with severe COVID-19 irrespective of obesity, we aimed to evaluate and compare the predictive value for early intensive care or death of three fat depots (cardiac, visceral and subcutaneous) using computed tomography (CT) at admission for COVID-19 in consecutive patients with and without T2D.

METHODS

Two hundred and two patients admitted for COVID-19 were retrospectively included between February and June 2020 and distributed in two groups: T2D or non-diabetic controls. Chest CT with cardiac (CATi), visceral (VATi) and subcutaneous adipose tissue (SATi) volume measurements were performed at admission. The primary endpoint was a composite outcome criteria including death or ICU admission at day 21 after admission. Threshold values of adipose tissue components predicting adverse outcome were determined.

RESULTS

One hundred and eight controls [median age: 76(IQR:59-83), 61% male, median BMI: 24(22-27)] and ninety-four T2D patients [median age: 70(IQR:61-77), 70% male, median BMI: 27(24-31)], were enrolled in this study. At day 21 after admission, 42 patients (21%) had died from COVID-19, 48 (24%) required intensive care and 112 (55%) were admitted to a conventional care unit (CMU). In T2D, CATi was associated with early death or ICU independently from age, sex, BMI, dyslipidemia, CRP and coronary calcium (CAC). (p = 0.005). Concerning T2D patients, the cut-point for CATi was  > 100 mL/m with a sensitivity of 0.83 and a specificity of 0.50 (AUC = 0.67, p = 0.004) and an OR of 4.71 for early ICU admission or mortality (p = 0.002) in the fully adjusted model. Other adipose tissues SATi or VATi were not significantly associated with early adverse outcomes. In control patients, age and male sex (OR = 1.03, p = 0.04) were the only predictors of ICU or death.

CONCLUSIONS

Cardiac adipose tissue volume measured in CT at admission was independently predictive of early intensive care or death in T2D patients with COVID-19 but not in non-diabetics. Such automated CT measurement could be used in routine in diabetic patients presenting with moderate to severe COVID-19 illness to optimize individual management and prevent critical evolution.

摘要

背景

2 型糖尿病(T2D)患者的特征是内脏和异位脂肪组织扩张,导致全身慢性低度炎症。由于内脏肥胖与 COVID-19 的严重程度有关,而与肥胖无关,因此我们旨在评估和比较三种脂肪组织(心脏、内脏和皮下)在连续患有和不患有 T2D 的 COVID-19 患者入院时使用计算机断层扫描(CT)的预测价值,用于早期重症监护或死亡。

方法

2020 年 2 月至 6 月期间,回顾性纳入 202 名因 COVID-19 入院的患者,并将其分为两组:T2D 或非糖尿病对照组。入院时进行胸部 CT 以测量心脏(CATi)、内脏(VATi)和皮下脂肪组织(SATi)的体积。主要终点是包括入院后 21 天内死亡或 ICU 入院的复合结果标准。确定预测不良结局的脂肪组织成分的阈值值。

结果

本研究纳入了 108 名对照组[中位年龄:76(IQR:59-83),61%男性,中位 BMI:24(22-27)]和 94 名 T2D 患者[中位年龄:70(IQR:61-77),70%男性,中位 BMI:27(24-31)]。入院后第 21 天,42 名患者(21%)因 COVID-19 死亡,48 名(24%)需要重症监护,112 名(55%)入住普通病房(CMU)。在 T2D 中,CATi 与年龄、性别、BMI、血脂异常、CRP 和冠状动脉钙(CAC)独立相关,与早期死亡或 ICU 相关。(p = 0.005)。对于 T2D 患者,CATi 的截断值为 > 100 mL/m,灵敏度为 0.83,特异性为 0.50(AUC = 0.67,p = 0.004),OR 为 4.71,用于预测早期 ICU 入院或死亡率(p = 0.002),在完全调整的模型中。其他脂肪组织 SATi 或 VATi 与早期不良结局无显著相关性。在对照组患者中,年龄和男性(OR = 1.03,p = 0.04)是 ICU 或死亡的唯一预测因素。

结论

入院时 CT 测量的心脏脂肪组织体积可独立预测 T2D 合并 COVID-19 患者的早期重症监护或死亡,但不能预测非糖尿病患者。这种自动 CT 测量可在患有中度至重度 COVID-19 疾病的糖尿病患者中常规使用,以优化个体管理并预防病情恶化。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/96da/9805681/1d2786c997ed/12933_2022_1722_Fig1_HTML.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验