根据心衰患者的六分钟步行距离估算心肺运动测试期间的最大工作率

IF 1.9 Q3 PERIPHERAL VASCULAR DISEASE
Giancarlo Piaggi , Mara Paneroni , Roberto Maestri , Elisabetta Salvioni , Ugo Corrà , Angelo Caporotondi , Simonetta Scalvini , Piergiuseppe Agostoni , Maria Teresa La Rovere
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引用次数: 0

摘要

背景建议慢性心力衰竭(CHF)患者进行运动,其强度通常设定为心肺运动测试(CPX)或症状限制增量测试(SLIT)中最大工作率(MWR)的百分比。由于后勤/成本方面的限制,这些测试在心脏康复中并不总是可用,因此我们旨在开发一个预测模型,利用人体测量和临床测量方法以及最广泛使用的运动场测试--6 分钟步行测试(6 MWT)来估算慢性阻塞性肺病患者 CPX 时的最大做功率(estMWR@CPX)。600 名纽约心脏协会(NYHA)功能分级为 I-III 级的 HF 患者接受了 CPX 和 6 MWT,通过多变量线性回归分析,我们定义了几个预测模型,以确定 estMWR@CPX.ResultsThe 最佳模型包括 6 MWT、性别、年龄、体重、NYHA 分级、左心室射血分数(LVEF)、吸烟状况和慢性阻塞性肺病 COPD(调整后 R2 = 0.55;95% LoA -39 至 33 W)。如果将 LVEF 排除在预测因素之外,所得模型的表现仅稍差一些(调整后 R2 = 0.54;95% LoA -42 至 34 W)。只有在 34% 的病例中,ESTMWR@CPX 与实际 MWR@CPX 之间的百分比差绝对值为 10%。EstMWR@CPX 往往会高估真实 MWR@CPX.ConclusionsOur 的低值,而低估真实的高值,结果表明所评估的预测模型缺乏准确性;因此,为了准确地开出循环测力计运动训练处方,有必要通过 CPX 或 SLIT 评估 MWR。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Estimating maximum work rate during cardiopulmonary exercise testing from the six-minute walk distance in patients with heart failure

Background

Exercise is recommended for patients with chronic heart failure (CHF) and its intensity is usually set as a percentage of the maximal work rate (MWR) during cardiopulmonary exercise testing (CPX) or a symptom-limited incremental test (SLIT). As these tests are not always available in cardiac rehabilitation due to logistic/cost constraints, we aimed to develop a predictive model to estimate MWR at CPX (estMWR@CPX) in CHF patients using anthropometric and clinical measures and the 6-min walk test (6 MWT), the most widely used exercise field test.

Methods

This is a multicentre cross-sectional retrospective study in a cardiac rehabilitation setting. Six hundred patients with HF in New York Heart Association (NYHA) functional class I-III underwent both CPX and 6 MWT and, through multivariable linear regression analysis, we defined several predictive models to define estMWR@CPX.

Results

The best model included 6 MWT, sex, age, weight, NYHA class, left ventricular ejection fraction (LVEF), smoking status and chronic obstructive pulmonary disease COPD (adjusted R2 = 0.55; 95% LoA −39 to 33 W). When LVEF was excluded as a predictor, the resulting model performed only slightly worse (adjusted R2 = 0.54; 95% LoA −42 to 34 W). Only in 34% of cases was the percentage difference between estMWR@CPX and real MWR@CPX <10% in absolute value. EstMWR@CPX tended to overestimate low values and underestimate high values of true MWR@CPX.

Conclusions

Our results showed a lack of accuracy in the predictive model evaluated; therefore, for an accurate prescription of cycle-ergometer exercise training, it is necessary to assess MWR by CPX or SLIT.

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