Division of Cardiology, Department of Internal Medicine, Teikyo University Hospital, Tokyo, Japan.
Division of Cardiovascular Medicine, Toyohashi Heart Center, Aichi, Japan.
Catheter Cardiovasc Interv. 2018 Dec 1;92(7):1365-1373. doi: 10.1002/ccd.27547. Epub 2018 Feb 22.
The prognostic impact of skeletal muscle mass, assessed using lean body mass (LBM), remain unclear in patients who underwent transcatheter aortic valve replacement (TAVR). The aim of this study to assess prognostic impact of LBM on mortality after TAVR.
We assessed 1,613 patients (median age 85 years, 70% female) who underwent TAVI from October 2013 to April 2016 using OCEAN (Optimized transCathEter vAlvular interveNtion)-TAVI registry data. LBM was calculated using the James formula. The primary endpoint was all-cause death after TAVR.
Median follow-up period was 287 days (interquartile range 110-462). The Kaplan-Meier analysis demonstrated that patients with low LBM had significantly higher incidence of all-cause death than those with high LBM in male (32.3% vs. 9.9%, log rank P < 0.001) and female (15.8% vs. 9.2%, log-rank P = 0.011). On contrary, the risk stratification using body mass index (BMI) could not validate into female patients who underwent TAVR. The multivariate analysis showed that the LBM was an independent predictor of all-cause death in male (Hazard ratio [HR] 0.93; 95% confidence interval [CI] 0.89-0.98) and female (HR 0.94; 95% CI 0.89-0.99). Inversely, the assessment using BMI could not identify the high-risk population in a female.
The patients with low LBM had the higher incidence of all-cause death after TAVR than those with high LBM, regardless of gender. Thus, the risk stratification using LBM might provide further insight to identify the high-risk TAVR population, compared to conventional risk stratification using BMI.
使用去脂体重(LBM)评估的骨骼肌量对行经导管主动脉瓣置换术(TAVR)患者的预后影响仍不清楚。本研究旨在评估 LBM 对 TAVR 后死亡率的预后影响。
我们评估了 2013 年 10 月至 2016 年 4 月期间接受 OCEAN(优化经导管瓣膜介入治疗)-TAVI 登记研究数据的 1613 名患者(中位年龄 85 岁,70%为女性)。LBM 使用 James 公式计算。主要终点是 TAVR 后的全因死亡。
中位随访时间为 287 天(四分位距 110-462)。Kaplan-Meier 分析表明,男性(32.3% vs. 9.9%,log-rank P<0.001)和女性(15.8% vs. 9.2%,log-rank P=0.011)中 LBM 较低的患者全因死亡发生率明显高于 LBM 较高的患者。相反,使用体重指数(BMI)进行风险分层不能验证 TAVR 后女性患者的情况。多变量分析表明,LBM 是男性(风险比 [HR] 0.93;95%置信区间 [CI] 0.89-0.98)和女性(HR 0.94;95% CI 0.89-0.99)全因死亡的独立预测因子。相反,在女性中,使用 BMI 评估不能识别高危人群。
无论性别如何,LBM 较低的患者 TAVR 后全因死亡率均高于 LBM 较高的患者。因此,与使用 BMI 进行的传统风险分层相比,使用 LBM 进行风险分层可能提供进一步的见解,以识别高危 TAVR 人群。