From the Department of Cardiology, West China Hospital, Sichuan University, 37 Guoxue Street, Wuhou District, Chengdu 610041, China.
From the Department of Cardiology, West China Hospital, Sichuan University, 37 Guoxue Street, Wuhou District, Chengdu 610041, China
QJM. 2015 Aug;108(8):641-7. doi: 10.1093/qjmed/hcv013. Epub 2015 Jan 21.
'Obesity paradox' was not consistently observed in Asians with coronary artery disease (CAD).
The study investigated the association between body composition and outcomes in Chinese patients with CAD.
Cohort study.
A total of 3280 patients with angiographically validated CAD were consecutively included. Body fat (BF) percentage and lean mass index (LMI) were evaluated using the Clínica Universidad de Navarra-Body Adiposity Estimator. The rate of mortality from any cause was compared across groups classified by the quartiles of LMI.
During a median period of 24 months, 288 (8.8%) participants died. There was a close association between increasing LMI and reducing mortality rate. However, univariate analyses did not find protective effect of BF on survival. After adjusting for age, sex, diabetes, current smoking, systolic blood pressure, creatinine, white blood cell count, haemoglobin and medication, Cox regression analyses showed that the significant relation between higher quartiles (Q) of LMI and survival benefit (Q4, hazard ratio 0.58 (95% confidence interval: 0.36-0.94) vs. Q3, 0.60 (0.39-0.91) vs. Q2, 0.60 (0.41-0.88) vs. Q1, reference) remained.
Low LMI but not BF predicts all-cause mortality in Chinese patients with CAD.
在患有冠心病（CAD）的亚洲人中，“肥胖悖论”并不总是存在。
本研究旨在探讨中国人的体成分与 CAD 患者结局的相关性。
队列研究。
共连续纳入 3280 例经血管造影证实的 CAD 患者。采用 Clinica Universidad de Navarra-Body Adiposity Estimator 评估体脂肪（BF）百分比和瘦体重指数（LMI）。比较根据 LMI 四分位数分组的死亡率。
在中位 24 个月的随访期间，288 名（8.8%）患者死亡。随着 LMI 的增加，死亡率呈下降趋势，二者之间存在密切关联。然而，单因素分析并未发现 BF 对生存有保护作用。在调整年龄、性别、糖尿病、当前吸烟、收缩压、肌酐、白细胞计数、血红蛋白和药物等因素后，Cox 回归分析显示，LMI 较高四分位数（Q）与生存获益之间存在显著相关性（Q4：风险比 0.58（95%置信区间：0.36-0.94）与 Q3，0.60（0.39-0.91）与 Q2，0.60（0.41-0.88）与 Q1，参考）。
在 CAD 患者中，低 LMI 而不是 BF 预测全因死亡率。
