Mid-arm and calf circumferences are stronger mortality predictors than body mass index for patients with chronic obstructive pulmonary disease

对于慢性阻塞性肺疾病患者而言,上臂和小腿围比体重指数更能预测死亡率。

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Abstract

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is currently the third most common cause of death in the world. Patients with COPD experience airflow obstruction, weight loss, skeletal muscle dysfunction, and comorbidities. Anthropometric indicators are risk factors for mortality in geriatric assessment. PURPOSE: This study examined and compared the associations of anthropometric indicators, such as low body mass index (BMI), low mid-arm circumference (MAC), and low calf circumference (CC), with the prediction of a 3-year follow-up mortality risk in patients with COPD. METHODS: We recruited nonhospitalized patients with COPD without acute conditions from a general hospital in Taiwan. The BMI, MAC, and CC of all patients were measured, and they were followed for 3 years through telephone interviews and chart reviews. The Kaplan-Meier survival curves stratified by BMI, MAC, and CC were analyzed. Variables univariately associated with survival were entered into a multivariate Cox regression model. The Bayesian information criterion was used to compare the predictive ability of the three anthropometric indicators to predict mortality rate. RESULTS: In total, 104 patients were included (mean ± standard deviation age, 74.2±6.9 years; forced expiratory volume in 1 second [%], 58.4±20.4 predicted; males, 94.2%); 22 patients (21.2%) died during the 36-month follow-up. During this long-term follow-up, the three anthropometric indicators could predict mortality risk in patients with COPD (low BMI [<21 kg/m(2)], hazard ratio [HR] =2.78, 95% confidence interval [CI] =1.10-7.10; low MAC [<23.5 cm], HR =3.09, 95% CI =1.30-7.38; low CC [<30 cm], HR =4.40, 95% CI =1.82-10.63). CC showed the strongest potential in predicting the mortality risk, followed by MAC and BMI. CONCLUSION: Among the three anthropometric variables examined, CC can be considered a strong predictor of mortality risk in patients with COPD.

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