Bargehr Johannes, Thomas Colleen S, Oken Keith R, Thomas Randal J, Lopez-Jimenez Francisco, Trejo-Gutierrez Jorge F
Department of Cardiovascular Diseases, Mayo Clinic Florida, Jacksonville, Florida; Division of Cardiovascular Medicine, University of Cambridge, Addenbrooke's Hospital, Cambridge, United Kingdom.
Division of Biomedical Statistics and Informatics, Mayo Clinic Florida, Jacksonville, Florida.
Am J Cardiol. 2017 Mar 1;119(5):687-691. doi: 10.1016/j.amjcard.2016.08.005. Epub 2016 Aug 24.
Cardiac rehabilitation (CR) improves exercise capacity (EC), but not all CR participants achieve such improvements. Our primary aim was to develop a tool to identify those with suboptimal improvement in EC after CR. We retrospectively analyzed 541 patients enrolled in a phase-II CR program after a cardiac event or intervention from 2003 to 2014. EC was assessed with the 6-minute walk test. We developed a multivariate linear regression model and corresponding nomogram to predict EC after CR. The predictors included in the final model were age, gender, baseline EC, primary referral diagnosis, body mass index, systolic blood pressure at rest, triglycerides, low-density lipoprotein cholesterol, lipid-lowering medication use, and an interaction term of low-density lipoprotein cholesterol with lipid-lowering therapy. The prediction model was internally validated using bootstrap methods, and a nomogram was created for ease of use. In conclusion, this tool helps to identify those patients with suboptimal improvement in EC who could be targeted for individualized interventions to increase their performance.
心脏康复(CR)可提高运动能力(EC),但并非所有参与心脏康复的患者都能实现这种改善。我们的主要目的是开发一种工具,以识别那些在心脏康复后运动能力改善不理想的患者。我们回顾性分析了2003年至2014年期间因心脏事件或干预而参加II期心脏康复计划的541例患者。通过6分钟步行试验评估运动能力。我们开发了一个多变量线性回归模型和相应的列线图来预测心脏康复后的运动能力。最终模型中纳入的预测因素包括年龄、性别、基线运动能力、主要转诊诊断、体重指数、静息收缩压、甘油三酯、低密度脂蛋白胆固醇、降脂药物使用情况,以及低密度脂蛋白胆固醇与降脂治疗的交互项。使用自助法对预测模型进行内部验证,并创建列线图以便于使用。总之,该工具有助于识别那些运动能力改善不理想的患者,这些患者可作为个体化干预的目标,以提高他们的运动表现。