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Rehabilitation Practice and Science

Translated Title

以三分鐘登階測試結合心率變異預測心臟病患之尖峰攝氧量

Abstract

Background: Peak oxygen consumption (Peak VO_2) is a recognized indicator of overall functions of the cardiac-vascular system, and the cardiopulmonary exercise test (CPET) is considered the golden standard for determining peak VO_2. However, there are limitations to performing CPET, including high cost, long testing time, staff risks and participant’s discomfort during the test. In contrast, Submaximal exercise testing can be an alternative for assessing cardiovascular fitness with minimal risk and lower cost. The step test, one of the submaximal exercise tests, was the first to be described as a method for assessing exercise capacity in the early 20th century. Various protocols have been developed since then, all of them have been proved by previous studies to be useful in different needs and all have shown good reliability and validity. However, to date, clinical evidence on cardiac disease population is sparse, and scientists have pointed out that it is necessary to estimate the participants' physiological parameters during submaximal exercise to reveal their real capacity. Heart rate variability (HRV) is the physiological phenomenon of variation in the time interval between heartbeats and it is influenced by the autonomic nervous system (ANS). The ANS has been proved to be an important role for cardiac-autonomic modulation and arterial stiffness control. Therefore, analysis of HRV and arterial stiffness may provide us with useful information about autonomic control of the cardiovascular system, and furthermore, it may be an effective tool for assessing one's cardiopulmonary fitness and predicting the prognosis for patients with cardiac diseases. Taking into account the above factors, the aim of this study was to develop a unique, tailored 3- minute step test that combined ANS modulation to predict peak VO_2 in patients with cardiac diseases. Methods: Twenty-three subjects with cardiac-vascular disease history were recruited. All subjects received CPET (Grading protocol, 10W/min) and were further divided into the NYHA class III group (FcIII) and the class II (FcII) group according to their performance. Then, all subjects took the 3-minute step test with ANS activity evaluation. HRV parameters and arterial stiffness indexes were recorded and analyzed in the ＂pre-exercise＂, ＂in-motion＂ and ＂recovery＂ phases of the step test. Minute ventilation (VE), oxygen consumption (VO_2) and carbonic dioxide production (VCO_2) were measured breath by breath using a gas analyzing system in the CPET test. Correlations between 3-minute step test and the CPET parameters were assessed using the Pearson's correlation coefficient method. Results: All patients completed the CPET and were divided into 2 groups (Fc II: n=12, Fc III: n=11) according to their peak VO_2 performance. Five of the eleven patients in the Fc III group did not complete the 3-minute step test (two with atrial arrhythmia, two with head dizziness plus dyspnea and one complained of knee pain during test), and eleven of the twelve patients in the Fc II group completed the test. There were no differences between the groups at baseline, including age, BMI, cardiac output, cardiac index and cardiac medications. In the recovery phase, the Fc II group had higher HRV parameters (SDNN, SD2, lnLF, lnHF, lnTP and arterial reflex indexes) than the Fc III group. In the entire step test process, the Fc II group still had higher average SDNN and SD2. There were strong positive correlations among average SDNN (r=0.88, p=0.001), average SD2 (r=0.89, p=0.001) and the peak VO_2. Also, SDNN (r=0.67, p=0.02), SD2 (r=0.691, p=0.01), lnLF (r=0.83, p=0.01), lnHF (r=0.72, p=0.01) and lnTP (r=0.76, p=0.004) showed significant correlations with the peak VO_2 in the recovery phase. Arterial stiffness indexes were not significantly correlated with the peak VO_2,but positively correlated with nHF (r= 0.68, p= 0.01) and negatively correlated with LF/HF(r= -0.66, p=0.02). Conclusions: This study showed that peak VO_2 has high correlation with the activity of ANS, especially the HRV. Therefore, it may be feasible and reliable to use a step test combined with heart rate variability parameters to predict the cardiopulmonary fitness in patients with heart disease. The best prediction formula could be: ＂Peak VO_2 predict = 9.684 + 0.062 x avg SD2＂ with 78.8% statistical explanatory power (R^2 = 0.788) or ＂Peak VO_2 predict = 9.8293 + 0.0853 x avg SDNN＂ with 76.9% power (R^2 = 0.769). In the future, clinical physiotherapists may use this safe and feasible method to predict and monitor patients' cardiopulmonary fitness condition and establish proper prescriptions in cardiac rehabilitation. Acknowledgement：The authors wish to thank the support of the Center for Big Data Analytics and Statistics (Grant CLRP3D0043) at Chang Gung Memorial Hospital.

Language

Traditional Chinese

First Page

75

Last Page

87

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