Suppr超能文献

使用陡坡试验验证和优化预测模型以估计癌症幸存者的运动能力

Validation and Refinement of Prediction Models to Estimate Exercise Capacity in Cancer Survivors Using the Steep Ramp Test.

作者信息

Stuiver Martijn M, Kampshoff Caroline S, Persoon Saskia, Groen Wim, van Mechelen Willem, Chinapaw Mai J M, Brug Johannes, Nollet Frans, Kersten Marie-José, Schep Goof, Buffart Laurien M

机构信息

Department of Physical Therapy, Netherlands Cancer Institute, Amsterdam, The Netherlands; Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands; ACHIEVE, Faculty of Health, Amsterdam University of Applied Sciences, Amsterdam, The Netherlands.

Department of Public & Occupational Health/EMGO+ Institute, VU University Medical Center, Amsterdam, The Netherlands.

出版信息

Arch Phys Med Rehabil. 2017 Nov;98(11):2167-2173. doi: 10.1016/j.apmr.2017.02.013. Epub 2017 Mar 18.

Abstract

OBJECTIVE

To further test the validity and clinical usefulness of the steep ramp test (SRT) in estimating exercise tolerance in cancer survivors by external validation and extension of previously published prediction models for peak oxygen consumption (Vo) and peak power output (W).

DESIGN

Cross-sectional study.

SETTING

Multicenter.

PARTICIPANTS

Cancer survivors (N=283) in 2 randomized controlled exercise trials.

INTERVENTIONS

Not applicable.

MAIN OUTCOME MEASURES

Prediction model accuracy was assessed by intraclass correlation coefficients (ICCs) and limits of agreement (LOA). Multiple linear regression was used for model extension. Clinical performance was judged by the percentage of accurate endurance exercise prescriptions.

RESULTS

ICCs of SRT-predicted Vo and W with these values as obtained by the cardiopulmonary exercise test were .61 and .73, respectively, using the previously published prediction models. 95% LOA were ±705mL/min with a bias of 190mL/min for Vo and ±59W with a bias of 5W for W. Modest improvements were obtained by adding body weight and sex to the regression equation for the prediction of Vo (ICC, .73; 95% LOA, ±608mL/min) and by adding age, height, and sex for the prediction of W (ICC, .81; 95% LOA, ±48W). Accuracy of endurance exercise prescription improved from 57% accurate prescriptions to 68% accurate prescriptions with the new prediction model for W.

CONCLUSIONS

Predictions of Vo and W based on the SRT are adequate at the group level, but insufficiently accurate in individual patients. The multivariable prediction model for W can be used cautiously (eg, supplemented with a Borg score) to aid endurance exercise prescription.

摘要

目的

通过外部验证以及扩展先前发表的关于峰值耗氧量(Vo)和峰值功率输出(W)的预测模型,进一步检验陡坡试验(SRT)在评估癌症幸存者运动耐力方面的有效性和临床实用性。

设计

横断面研究。

地点

多中心。

参与者

2项随机对照运动试验中的癌症幸存者(N = 283)。

干预措施

不适用。

主要观察指标

通过组内相关系数(ICC)和一致性界限(LOA)评估预测模型的准确性。使用多元线性回归进行模型扩展。通过准确的耐力运动处方百分比判断临床性能。

结果

使用先前发表的预测模型,SRT预测的Vo和W与心肺运动试验获得的值的ICC分别为0.61和0.73。Vo的95% LOA为±705mL/分钟,偏差为190mL/分钟;W的95% LOA为±59W,偏差为5W。通过在预测Vo的回归方程中加入体重和性别(ICC,0.73;95% LOA,±608mL/分钟)以及在预测W的方程中加入年龄、身高和性别(ICC,0.81;95% LOA,±48W),有适度改善。新的W预测模型使耐力运动处方的准确性从57%提高到68%。

结论

基于SRT对Vo和W的预测在群体水平上是足够的,但在个体患者中准确性不足。W的多变量预测模型可谨慎使用(例如,辅以伯格评分)以辅助耐力运动处方。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验