Suppr超能文献

手臂运动应激灌注成像可预测临床转归。

Arm exercise stress perfusion imaging predicts clinical outcome.

机构信息

St. Louis Veterans Affairs Medical Center and the Department of Internal Medicine, Washington University School of Medicine, St. Louis, Missouri, USA.

出版信息

J Appl Physiol (1985). 2011 Dec;111(6):1546-53. doi: 10.1152/japplphysiol.00725.2011. Epub 2011 Aug 18.

Abstract

Treadmill exercise capacity in resting metabolic equivalents (METs) and stress hemodynamic, electrocardiographic (ECG), and myocardial perfusion imaging (MPI) responses are independently predictive of adverse clinical events. However, limited data exist for arm ergometer stress testing (AXT) in patients who cannot perform leg exercise because of lower extremity disabilities. We sought to determine the extent to which AXT METs, hemodynamic, ECG, and MPI responses to arm exercise add independent incremental value to demographic and clinical variables for prediction of all-cause mortality, myocardial infarction (MI), or late coronary revascularization, individually or as a composite. A prospective cohort of 186 patients aged 64 ± 10 (SD) yr, unable to perform lower extremity exercise, underwent AXT MPI for clinical reasons between 1997 and 2002, and were followed for 62 ± 23 mo, to an endpoint of death or 12/31/2006. Average annual rates were 5.4% for mortality, 2.2% for MI, 2.5% for late coronary revascularization, and 8.0% for combined events. After adjustment for age and clinical variables, AXT METs [P < 0.05; hazard ratio (HR) = 0.59; confidence interval (CI) = 0.35-0.84] and abnormal MPI (P < 0.01; HR = 2.48; CI = 2.15-2.81) were independently predictive of mortality. A positive AXT ECG (P < 0.05; HR = 2.61; CI = 2.13-3.10) was predictive of MI. Death and MI combined were prognosticated by METs (P < 0.05; HR = 0.63; CI = 0.41-0.85), MPI (P < 0.05; HR = 1.77; CI = 1.49-2.05), and a positive AXT ECG (P < 0.05; HR = 1.86; CI = 1.55-2.17). In conclusion, for high risk older patients who cannot perform leg exercise because of lower extremity disabilities, AXT METs are as important as MPI for prediction of mortality alone and death and MI combined, and a positive AXT ECG prognosticates MI alone and death and MI combined.

摘要

在静息代谢等价物 (METs) 中进行跑步机运动能力测试,以及压力血液动力学、心电图 (ECG) 和心肌灌注成像 (MPI) 反应可独立预测不良临床事件。然而,由于下肢残疾而无法进行腿部运动的患者进行手臂测力计压力测试 (AXT) 的相关数据有限。我们旨在确定在因下肢残疾而无法进行腿部运动的患者中,手臂运动的 AXT METs、血液动力学、心电图和 MPI 反应在预测全因死亡率、心肌梗死 (MI) 或晚期冠状动脉血运重建方面,单独或作为复合终点,对人口统计学和临床变量的独立增量价值的程度。一项前瞻性队列研究纳入了 186 名年龄 64 ± 10 岁(标准差)的患者,因下肢运动受限而无法进行下肢运动,1997 年至 2002 年间因临床原因进行了 AXT MPI,随访 62 ± 23 个月,直至死亡或 2006 年 12 月 31 日。死亡率的年平均发生率为 5.4%,MI 为 2.2%,晚期冠状动脉血运重建为 2.5%,复合事件为 8.0%。在调整年龄和临床变量后,AXT METs [P < 0.05;风险比 (HR) = 0.59;置信区间 (CI) = 0.35-0.84] 和异常 MPI (P < 0.01;HR = 2.48;CI = 2.15-2.81) 独立预测死亡率。AXT ECG 阳性 (P < 0.05;HR = 2.61;CI = 2.13-3.10) 预测 MI。死亡率和 MI 合并的预后由 METs (P < 0.05;HR = 0.63;CI = 0.41-0.85)、MPI (P < 0.05;HR = 1.77;CI = 1.49-2.05) 和 AXT ECG 阳性 (P < 0.05;HR = 1.86;CI = 1.55-2.17) 预测。总之,对于因下肢残疾而无法进行腿部运动的高危老年患者,AXT METs 与 MPI 一样重要,可单独预测死亡率和死亡率与 MI 合并,AXT ECG 阳性可单独预测 MI 和死亡率与 MI 合并。

相似文献

1
Arm exercise stress perfusion imaging predicts clinical outcome.手臂运动应激灌注成像可预测临床转归。
J Appl Physiol (1985). 2011 Dec;111(6):1546-53. doi: 10.1152/japplphysiol.00725.2011. Epub 2011 Aug 18.
2
Arm exercise testing predicts clinical outcome.手臂运动测试可预测临床结果。
Am Heart J. 2009 Jan;157(1):69-76. doi: 10.1016/j.ahj.2008.09.007. Epub 2008 Nov 1.

引用本文的文献

本文引用的文献

2
Arm exercise testing predicts clinical outcome.手臂运动测试可预测临床结果。
Am Heart J. 2009 Jan;157(1):69-76. doi: 10.1016/j.ahj.2008.09.007. Epub 2008 Nov 1.
3
Prognostic value of heart rate increase at onset of exercise testing.运动试验开始时心率增加的预后价值。
Circulation. 2007 Jan 30;115(4):468-74. doi: 10.1161/CIRCULATIONAHA.106.666388. Epub 2007 Jan 22.
9
Prognostic value of myocardial perfusion imaging in patients with high exercise tolerance.
Circulation. 1999 Feb 23;99(7):867-72. doi: 10.1161/01.cir.99.7.867.

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验