Heart Rate Variability-Guided Training for Improving Mortality Predictors in Patients with Coronary Artery Disease
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Design, Randomization, and Implementation
2.2. Participants
2.3. Measurements
2.3.1. At Home Day-to-Day Heart Rate Variability Assessment
2.3.2. Laboratory-Based Heart Rate Variability Assessment
2.3.3. Cardiopulmonary Exercise Test
2.3.4. Secondary Outcomes
2.4. Exercise Training Programs
2.5. Statistical Analyses
3. Results
Mortality Predictors
4. Discussion
5. Strengths and Limitations
6. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Anderson, L.; Oldridge, N.; Thompson, D.R.; Zwisler, A.D.; Rees, K.; Martin, N.; Taylor, R.S. Exercise-Based Cardiac Rehabilitation for Coronary Heart Disease: Cochrane Systematic Review and Meta-Analysis. J. Am. Coll. Cardiol. 2016, 67, 1–12. [Google Scholar] [CrossRef] [Green Version]
- Chen, X.J.; Barywani, S.B.; Hansson, P.O.; Östgärd Thunström, E.; Rosengren, A.; Ergatoudes, C.; Mandalenakis, Z.; Caidahl, K.; Fu, M.L. Impact of changes in heart rate with age on all-cause death and cardiovascular events in 50-year-old men from the general population. Open Heart 2019, 6, e000856. [Google Scholar] [CrossRef]
- Cole, C.R.; Blackstone, E.H.; Pashkow, F.J.; Snader, C.E.; Lauer, M.S. Heart-rate recovery immediately after exercise as a predictor of mortality. N. Engl. J. Med. 1999, 341, 1351–1357. [Google Scholar] [CrossRef] [PubMed]
- Kodama, S.; Saito, K.; Tanaka, S.; Maki, M.; Yachi, Y.; Asumi, M.; Sugawara, A.; Totsuka, K.; Shimano, H.; Ohashi, Y.; et al. Cardiorespiratory fitness as a quantitative predictor of all-cause mortality and cardiovascular events in healthy men and women: A meta-analysis. JAMA 2009, 301, 2024–2035. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Tsuji, H.; Larson, M.G.; Venditti, F.J., Jr.; Manders, E.S.; Evans, J.C.; Feldman, C.L.; Levy, D. Impact of reduced heart rate variability on risk for cardiac events. The Framingham Heart Study. Circulation 1996, 94, 2850–2855. [Google Scholar] [CrossRef] [PubMed]
- Ezzatvar, Y.; Izquierdo, M.; Núñez, J.; Calatayud, J.; Ramírez-Vélez, R.; García-Hermoso, A. Cardiorespiratory fitness measured with cardiopulmonary exercise testing and mortality in patients with cardiovascular disease: A systematic review and meta-analysis. J. Sport Health Sci. 2021, 10, 609–619. [Google Scholar] [CrossRef]
- Martinez, D.G.; Nicolau, J.C.; Lage, R.L.; Toschi-Dias, E.; de Matos, L.D.; Alves, M.J.; Trombetta, I.C.; Dias da Silva, V.J.; Middlekauff, H.R.; Negrão, C.E.; et al. Effects of long-term exercise training on autonomic control in myocardial infarction patients. Hypertension 2011, 58, 1049–1056. [Google Scholar] [CrossRef] [Green Version]
- Medeiros, W.M.; de Luca, F.A.; de Figueredo Júnior, A.R.; Mendes, F.A.R.; Gun, C. Heart rate recovery improvement in patients following acute myocardial infarction: Exercise training, β-blocker therapy or both. Clin. Physiol. Funct. Imaging 2018, 38, 351–359. [Google Scholar] [CrossRef]
- Manresa-Rocamora, A.; Sarabia, J.M.; Sánchez-Meca, J.; Oliveira, J.; Vera-Garcia, F.J.; Moya-Ramón, M. Are the Current Cardiac Rehabilitation Programs Optimized to Improve Cardiorespiratory Fitness in Patients? A Meta-Analysis. J. Aging Phys. Act. 2020, 29, 327–342. [Google Scholar] [CrossRef]
- Malik, M. Heart rate variability: Standards of measurement, physiological interpretation and clinical use. Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology. Circulation 1996, 93, 1043–1065. [Google Scholar] [CrossRef]
- Peçanha, T.; Bartels, R.; Brito, L.C.; Paula-Ribeiro, M.; Oliveira, R.S.; Goldberger, J.J. Methods of assessment of the post-exercise cardiac autonomic recovery: A methodological review. Int. J. Cardiol. 2017, 227, 795–802. [Google Scholar] [CrossRef] [PubMed]
- Nenna, A.; Lusini, M.; Spadaccio, C.; Nappi, F.; Greco, S.M.; Barbato, R.; Covino, E.; Chello, M. Heart rate variability: A new tool to predict complications in adult cardiac surgery. J. Geriatr. Cardiol. 2017, 14, 662–668. [Google Scholar] [PubMed]
- Zoccali, C.; Mallamaci, F.; Parlongo, S.; Cutrupi, S.; Benedetto, F.A.; Tripepi, G.; Bonanno, G.; Rapisarda, F.; Fatuzzo, P.; Seminara, G.; et al. Plasma norepinephrine predicts survival and incident cardiovascular events in patients with end-stage renal disease. Circulation 2002, 105, 1354–1359. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Plews, D.J.; Laursen, P.B.; Stanley, J.; Kilding, A.E.; Buchheit, M. Training adaptation and heart rate variability in elite endurance athletes: Opening the door to effective monitoring. Sports Med. 2013, 43, 773–781. [Google Scholar] [CrossRef]
- Ciccone, A.B.; Siedlik, J.A.; Wecht, J.M.; Deckert, J.A.; Nguyen, N.D.; Weir, J.P. Reminder: RMSSD and SD1 are identical heart rate variability metrics. Muscle Nerve 2017, 56, 674–678. [Google Scholar] [CrossRef] [PubMed]
- Shaffer, F.; Ginsberg, J.P. An Overview of Heart Rate Variability Metrics and Norms. Front. Public Health 2017, 5, 258. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Perini, R.; Orizio, C.; Comandè, A.; Castellano, M.; Beschi, M.; Veicsteinas, A. Plasma norepinephrine and heart rate dynamics during recovery from submaximal exercise in man. Eur. J. Appl. Physiol. Occup. Physiol. 1989, 58, 879–883. [Google Scholar] [CrossRef]
- Manresa-Rocamora, A.; Ribeiro, F.; Sarabia, J.M.; Íbias, J.; Oliveira, N.L.; Vera-García, F.J.; Moya-Ramón, M. Exercise-based cardiac rehabilitation and parasympathetic function in patients with coronary artery disease: A systematic review and meta-analysis. Clin. Auton. Res. 2020, 31, 187–203. [Google Scholar] [CrossRef]
- Manresa-Rocamora, A.; Flatt, A.A.; Casanova-Lizón, A.; Ballester-Ferrer, J.A.; Sarabia, J.M.; Vera-Garcia, F.J.; Moya-Ramón, M. Heart rate-based indices to detect parasympathetic hyperactivity in functionally overreached athletes. A meta-analysis. Scand. J. Med. Sci. Sports 2021, 31, 1164–1182. [Google Scholar] [CrossRef]
- Plews, D.J.; Laursen, P.B.; Le Meur, Y.; Hausswirth, C.; Kilding, A.E.; Buchheit, M. Monitoring training with heart rate-variability: How much compliance is needed for valid assessment? Int. J. Sports Physiol. Perform. 2014, 9, 783–790. [Google Scholar] [CrossRef]
- Witvrouwen, I.; Van Craenenbroeck, E.M.; Abreu, A.; Moholdt, T.; Kränkel, N. Exercise training in women with cardiovascular disease: Differential response and barriers—Review and perspective. Eur. J. Prev. Cardiol. 2021, 28, 779–790. [Google Scholar] [CrossRef] [PubMed]
- Skinner, J.S.; Jaskólski, A.; Jaskólska, A.; Krasnoff, J.; Gagnon, J.; Leon, A.S.; Rao, D.C.; Wilmore, J.H.; Bouchard, C. Age, sex, race, initial fitness, and response to training: The HERITAGE Family Study. J. Appl. Physiol. 2001, 90, 1770–1776. [Google Scholar] [CrossRef] [Green Version]
- Hedelin, R.; Bjerle, P.; Henriksson-Larsén, K. Heart rate variability in athletes: Relationship with central and peripheral performance. Med. Sci. Sports Exerc. 2001, 33, 1394–1398. [Google Scholar] [CrossRef] [PubMed]
- Compostella, L.; Nicola, R.; Tiziana, S.; Caterina, C.; Fabio, B. Autonomic dysfunction predicts poor physical improvement after cardiac rehabilitation in patients with heart failure. Res. Cardiovasc. Med. 2014, 3, e25237. [Google Scholar] [CrossRef] [PubMed]
- Bellenger, C.R.; Fuller, J.T.; Thomson, R.L.; Davison, K.; Robertson, E.Y.; Buckley, J.D. Monitoring Athletic Training Status Through Autonomic Heart Rate Regulation: A Systematic Review and Meta-Analysis. Sports Med. 2016, 46, 1461–1486. [Google Scholar] [CrossRef]
- Javaloyes, A.; Sarabia, J.M.; Lamberts, R.P.; Moya-Ramon, M. Training Prescription Guided by Heart Rate Variability in Cycling. Int. J. Sports Physiol. Perform. 2018; 1–28, Online ahead of print. [Google Scholar]
- Kiviniemi, A.M.; Hautala, A.J.; Kinnunen, H.; Nissilä, J.; Virtanen, P.; Karjalainen, J.; Tulppo, M.P. Daily exercise prescription on the basis of HR variability among men and women. Med. Sci. Sports Exerc. 2010, 42, 1355–1363. [Google Scholar] [CrossRef]
- da Silva, D.F.; Ferraro, Z.M.; Adamo, K.B.; Machado, F.A. Endurance Running Training Individually Guided by HRV in Untrained Women. J. Strength Cond. Res. 2019, 33, 736–746. [Google Scholar] [CrossRef]
- Plews, D.J.; Laursen, P.B.; Kilding, A.E.; Buchheit, M. Evaluating training adaptation with heart-rate measures: A methodological comparison. Int. J. Sports Physiol. Perform. 2013, 8, 688–691. [Google Scholar] [CrossRef]
- Kiviniemi, A.M.; Hautala, A.J.; Kinnunen, H.; Tulppo, M.P. Endurance training guided individually by daily heart rate variability measurements. Eur. J. Appl. Physiol. 2007, 101, 743–751. [Google Scholar] [CrossRef]
- Behrens, K.; Hottenrott, K.; Weippert, M.; Montanus, H.; Kreuzfeld, S.; Rieger, A.; Lübke, J.; Werdan, K.; Stoll, R. Individualization of exercise load control for inpatient cardiac rehabilitation. Development and evaluation of a HRV-based intervention program for patients with ischemic heart failure. Herz 2015, 40 (Suppl. 1), 61–69. [Google Scholar] [CrossRef]
- Javaloyes, A.; Sarabia, J.M.; Lamberts, R.P.; Plews, D.; Moya-Ramon, M. Training Prescription Guided by Heart Rate Variability Vs. Block Periodization in Well-Trained Cyclists. J. Strength Cond. Res. 2020, 34, 1511–1518. [Google Scholar] [CrossRef] [PubMed]
- Plews, D.J.; Scott, B.; Altini, M.; Wood, M.; Kilding, A.E.; Laursen, P.B. Comparison of Heart-Rate-Variability Recording With Smartphone Photoplethysmography, Polar H7 Chest Strap, and Electrocardiography. Int. J. Sports Physiol. Perform. 2017, 12, 1324–1328. [Google Scholar] [CrossRef] [PubMed]
- Esco, M.R.; Flatt, A.A. Ultra-short-term heart rate variability indexes at rest and post-exercise in athletes: Evaluating the agreement with accepted recommendations. J. Sports Sci. Med. 2014, 13, 535–541. [Google Scholar] [PubMed]
- Flatt, A.A.; Esco, M.R. Validity of the ithlete™ Smart Phone Application for Determining Ultra-Short-Term Heart Rate Variability. J. Hum. Kinet. 2013, 39, 85–92. [Google Scholar] [CrossRef] [Green Version]
- Catai, A.M.; Pastre, C.M.; de Godoy, M.F.; da Silva, E.; de Medeiros Takahashi, A.C.; Vanderlei, L.C.M. Heart rate variability: Are you using it properly? Standardisation checklist of procedures. Braz. J. Phys. Ther. 2019, 24, 91–102. [Google Scholar] [CrossRef]
- Perrotta, A.S.; Jeklin, A.T.; Hives, B.A.; Meanwell, L.E.; Warburton, D.E. Validity of the elite HRV smartphone application for examining heart rate variability in a field-based setting. J. Strength Cond. Res. 2017, 31, 2296–2302. [Google Scholar] [CrossRef]
- Sun, X.-G.; Hansen, J.E.; Stringer, W.W. Oxygen uptake efficiency plateau best predicts early death in heart failure. Chest 2012, 141, 1284–1294. [Google Scholar] [CrossRef] [Green Version]
- Albouaini, K.; Egred, M.; Alahmar, A.; Wright, D.J. Cardiopulmonary exercise testing and its application. Heart 2007, 93, 1285–1292. [Google Scholar] [CrossRef]
- Arena, R.; Myers, J.; Williams, M.A.; Gulati, M.; Kligfield, P.; Balady, G.J.; Collins, E.; Fletcher, G. Assessment of functional capacity in clinical and research settings: A scientific statement from the American Heart Association Committee on Exercise, Rehabilitation, and Prevention of the Council on Clinical Cardiology and the Council on Cardiovascular Nursing. Circulation 2007, 116, 329–343. [Google Scholar]
- Gaskill, S.E.; Ruby, B.C.; Walker, A.J.; Sanchez, O.A.; Serfass, R.C.; Leon, A.S. Validity and reliability of combining three methods to determine ventilatory threshold. Med. Sci. Sports Exerc. 2001, 33, 1841–1848. [Google Scholar] [CrossRef]
- Buchheit, M. Monitoring training status with HR measures: Do all roads lead to Rome? Front. Physiol. 2014, 5, 73. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Plews, D.J.; Laursen, P.B.; Kilding, A.E.; Buchheit, M. Heart rate variability in elite triathletes, is variation in variability the key to effective training? A case comparison. Eur. J. Appl. Physiol. 2012, 112, 3729–3741. [Google Scholar] [CrossRef] [PubMed]
- Vesterinen, V.; Nummela, A.; Heikura, I.; Laine, T.; Hynynen, E.; Botella, J.; Häkkinen, K. Individual endurance training prescription with heart rate variability. Med. Sci. Sports Exerc. 2016, 48, 1347–1354. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Boutcher, S.H.; Park, Y.; Dunn, S.L.; Boutcher, Y.N. The relationship between cardiac autonomic function and maximal oxygen uptake response to high-intensity intermittent-exercise training. J. Sports Sci. 2013, 31, 1024–1029. [Google Scholar] [CrossRef] [PubMed]
- Campbell, M.J.; Gardner, M.J. Calculating confidence intervals for some non-parametric analyses. Br. Med. J. (Clin. Res. Ed.) 1988, 296, 1454–1456. [Google Scholar] [CrossRef] [Green Version]
- Goldberger, J.J.; Ahmed, M.W.; Parker, M.A.; Kadish, A.H. Dissociation of heart rate variability from parasympathetic tone. Am. J. Physiol. 1994, 266, H2152–H2157. [Google Scholar] [CrossRef]
- Sato, R.; Mizuno, M.; Miura, T.; Kato, Y.; Watanabe, S.; Fuwa, D.; Ogiyama, Y.; Tomonari, T.; Ota, K.; Ichikawa, T.; et al. Angiotensin receptor blockers regulate the synchronization of circadian rhythms in heart rate and blood pressure. J. Hypertens. 2013, 31, 1233–1238. [Google Scholar] [CrossRef]
- Saboul, D.; Pialoux, V.; Hautier, C. The impact of breathing on HRV measurements: Implications for the longitudinal follow-up of athletes. Eur. J. Sport Sci. 2013, 13, 534–542. [Google Scholar] [CrossRef]
- Le Meur, Y.; Pichon, A.; Schaal, K.; Schmitt, L.; Louis, J.; Gueneron, J.; Vidal, P.P.; Hausswirth, C. Evidence of parasympathetic hyperactivity in functionally overreached athletes. Med. Sci. Sports Exerc. 2013, 45, 2061–2071. [Google Scholar] [CrossRef]
- Arai, Y.; Saul, J.P.; Albrecht, P.; Hartley, L.H.; Lilly, L.S.; Cohen, R.J.; Colucci, W.S. Modulation of cardiac autonomic activity during and immediately after exercise. Am. J. Physiol. 1989, 256, H132–H141. [Google Scholar] [CrossRef]
- Carter, R., 3rd; Watenpaugh, D.E.; Wasmund, W.L.; Wasmund, S.L.; Smith, M.L. Muscle pump and central command during recovery from exercise in humans. J. Appl. Physiol. 1999, 87, 1463–1469. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Shibasaki, M.; Sakai, M.; Oda, M.; Crandall, C.G. Muscle mechanoreceptor modulation of sweat rate during recovery from moderate exercise. J. Appl. Physiol. 2004, 96, 2115–2119. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Wang, L.W.; Ou, S.H.; Tsai, C.S.; Chang, Y.C.; Kao, C.W. Multimedia Exercise Training Program Improves Distance Walked, Heart Rate Recovery, and Self-efficacy in Cardiac Surgery Patients. J. Cardiovasc. Nurs. 2016, 31, 343–349. [Google Scholar] [CrossRef] [PubMed]
- Peçanha, T.; Silva-Júnior, N.D.; Forjaz, C.L. Heart rate recovery: Autonomic determinants, methods of assessment and association with mortality and cardiovascular diseases. Clin. Physiol. Funct. Imaging 2014, 34, 327–339. [Google Scholar] [CrossRef] [PubMed]
- Lipinski, M.J.; Vetrovec, G.W.; Froelicher, V.F. Importance of the first two minutes of heart rate recovery after exercise treadmill testing in predicting mortality and the presence of coronary artery disease in men. Am. J. Cardiol. 2004, 93, 445–449. [Google Scholar] [CrossRef] [PubMed]
- Jose, A.D.; Taylor, R.R. Autonomic blockade by propranolol and atropine to study intrinsic myocardial function in man. J. Clin. Investig. 1969, 48, 2019–2031. [Google Scholar] [CrossRef]
- Düking, P.; Zinner, C.; Reed, J.L.; Holmberg, H.C.; Sperlich, B. Predefined vs data-guided training prescription based on autonomic nervous system variation: A systematic review. Scand. J. Med. Sci. Sports 2020, 30, 2291–2304. [Google Scholar] [CrossRef]
- Medellín Ruiz, J.P.; Rubio-Arias, J.A.; Clemente-Suarez, V.J.; Ramos-Campo, D.J. Effectiveness of training prescription guided by heart rate variability versus predefined training for physiological and aerobic performance improvements: A systematic review and meta-analysis. Appl. Sci. 2020, 10, 8532. [Google Scholar] [CrossRef]
- Rees, K.; Taylor, R.S.; Singh, S.; Coats, A.J.; Ebrahim, S. Exercise based rehabilitation for heart failure. Cochrane Database Syst. Rev. 2004, Cd003331. [Google Scholar]
- Kraal, J.J.; Vromen, T.; Spee, R.; Kemps, H.M.C.; Peek, N. The influence of training characteristics on the effect of exercise training in patients with coronary artery disease: Systematic review and meta-regression analysis. Int. J. Cardiol. 2017, 245, 52–58. [Google Scholar] [CrossRef] [Green Version]
- Marfell-Jones, M.J.; RhoStewartme, A.D.; De Ridder, J.H. International Standards for Anthropometric Assessment. 2012. Available online: https://www.researchgate.net/publication/236891109_International_Standards_for_Anthropometric_Assessment (accessed on 1 July 2022).
- Durnin, J.V.; Womersley, J. Body fat assessed from total body density and its estimation from skinfold thickness: Measurements on 481 men and women aged from 16 to 72 years. Br. J. Nutr. 1974, 32, 77–97. [Google Scholar]
- Martin, A. Anthropometric assessment of bone mineral. In Anthropometric Assessment of Nutritional Status; Wiley-Liss: New York, NY, USA, 1991; pp. 185–196. [Google Scholar]
- Lee, R.C.; Wang, Z.; Spee, R.; Heo, M.; Ross, R.; Janssen, I.; Heymsfield, S.B. Total-body skeletal muscle mass: Development and cross-validation of anthropometric prediction models. Am. J. Clin. Nutr. 2000, 72, 796–803. [Google Scholar]
- Höfer, S.; Lim, L.; Guyatt, G.; Oldridge, N. The MacNew Heart Disease health-related quality of life instrument: A summary. Health Qual. Life Outcomes 2004, 2, 3. [Google Scholar]
- Chiavaroli, L.; Nishi, S.K.; Khan, T.A.; Braunstein, C.R.; Glenn, A.J.; Mejia, S.B.; Rahelić, D.; Kahleová, H.; Salas-Salvadó, J.; Jenkins, D.J.A.; et al. Portfolio Dietary Pattern and Cardiovascular Disease: A Systematic Review and Meta-analysis of Controlled Trials. Prog. Cardiovasc. Dis. 2018, 61, 43–53. [Google Scholar]
- Gargallo Fernández, M.; Basulto Marset, J.; Breton Lesmes, I.; Quiles Izquierdo, J.; Formiguera Sala, X.; Salas-Salvadó, J. Evidence-based nutritional recommendations for the prevention and treatment of overweight and obesity in adults (FESNAD-SEEDO consensus document). Methodology and executive summary (I/III). Nutr. Hosp. 2012, 27, 789–799. [Google Scholar]
PRED-G (n = 11) | HRV-G (n = 10) | p | |
---|---|---|---|
Age (years) | 59.2 ± 6.9 | 56.9 ± 5.6 | 0.418 |
Sex (male) | 10 (90.9) | 9 (90.0) | 0.999 |
Body weight (kg) | 78.2 ± 7.7 | 77.1 ± 15.5 | 0.852 |
Body mass index (kg/m2) | 29.1 (27.7, 29.7) | 26.8 (26.0, 30.6) | 0.569 |
Wait time (days) | 215.4 ± 84.9 | 169.2 ± 57.8 | 0.166 |
No. of infarcted patients | 7 (63.6) | 7 (70.0) | 0.999 |
Site of infarction (anterior) | 7 (63.6) | 5 (50.0) | 0.670 |
No. of vessels involved (1 vessel) | 8 (72.7) | 7 (70.0) | 0.999 |
No. of events (first) | 10 (90.9) | 9 (90.0) | 0.999 |
No. PTCA intervention surgery | 10 (90.9) | 9 (90.0) | 0.999 |
Diabetes mellitus | 5 (45.5) | 0 (0.0) | 0.035 * |
Hypertension | 5 (45.5) | 3 (30.0) | 0.659 |
Smoker | 5 (45.5) | 4 (40.0) | 0.999 |
Hyperlipidemia | 6 (54.5) | 5 (50.0) | 0.999 |
Overweight/obesity | 3 (27.3) | 1 (10.0) | 0.586 |
Family history | 2 (18.2) | 3 (30.0) | 0.635 |
Personal history | 2 (18.2) | 1 (10.0) | 0.999 |
b-Blockers | 9 (81.8) | 9 (90.0) | 0.999 |
ACE inhibitors | 4 (36.4) | 5 (50.0) | 0.670 |
Antiplatelets | 11 (100) | 9 (90.0) | 0.476 |
Diuretics | 4 (36.4) | 1 (10.0) | 0.311 |
Nitrates | 11 (100) | 10 (100) | N/A |
ARBs | 6 (54.5) | 2 (20.0) | 0.183 |
Calcium-channel blockers | 3 (27.3) | 0 (0.0) | 0.214 |
Lipid-lowering drugs | 11 (100) | 10 (100) | N/A |
Based on the Training Group (PRED-G, n = 11; HRV-G, n = 10) | All Patients (n = 21) | |||||||||
---|---|---|---|---|---|---|---|---|---|---|
Variable | Group | Pre | Post | p A | Change (95% CI) | p B | Pre | Post | p A | Change (95% CI) |
Isolated RMSSD (ms) | PRED-G | 28.4 ± 11.8 | 29.4 ± 10.2 | 0.774 | 1.07 (−7.12–9.26) −2.79 (−9.90–4.32) | 0.431 | 35.1 ± 25.7 | 34.3 ± 21.8 | 0.721 | −0.86 (−5.83–4.11) |
HRV-G | 41.9 ± 34.0 | 39.1 ± 29.1 | 0.398 | |||||||
Isolated HF (ms2) | PRED-G | 272.0 (151.3, 663.0) | 480.5 (188.5, 670.3) | 0.846 | −27.0 # (−225.2–425.4) −111.5 # (−892.3–43.8) | 0.143 | 374.0 (175.3, 745.0) | 357.5 (207.5, 649.8) | 0.202 | −66.00 # (−236.59–53.53) |
HRV-G | 649.5 (190.3, 1269.0) | 353.5 (197.5, 627.0) | 0.065 | |||||||
Isolated SD1 (ms) | PRED-G | 20.1 ± 8.3 | 20.7 ± 7.1 | 0.824 | 0.61 (−5.42–6.64) −2.16 (−7.07–2.75) | 0.430 | 24.9 ± 18.2 | 24.1 ± 15.4 | 0.654 | −0.78 (−4.34–2.79) |
HRV-G | 29.7 ± 24.1 | 27.5 ± 20.7 | 0.346 | |||||||
Weekly averaged RMSSD (ms) | PRED-G | 57.6 ± 20.0 | 54.8 ± 19.8 | 0.416 | −2.79 (−10.13–4.55) | 0.034 * | NA | NA | NA | NA |
HRV-G | 49.7 ± 16.0 | 57.3 ± 18.3 | 0.039 * | 7.57 (0.48–14.64) | ||||||
Resting HR (bpm) | PRED-G | 64.7 ± 5.0 | 62.2 ± 7.3 | 0.068 | −2.55 (−5.32–0.23) −5.80 (−9.74–−1.86) | 0.140 | 63.9 ± 7.1 | 59.8 ± 9.1 | 0.001 * | −4.10 (−6.37–−1.82) |
HRV-G | 63.0 ± 9.1 | 57.2 ± 10.6 | 0.009 * | |||||||
HRR 1 min (bpm) | PRED-G | 17.6 ± 6.8 | 19.1 ± 5.7 | 0.108 | 1.45 (−0.38–3.29) 0.10 (−1.53–1.73) | 0.235 | 20.0 ± 9.9 | 20.9 ± 9.1 | 0.163 | 0.81 (−0.36–1.98) |
HRV-G | 22.7 ± 12.3 | 22.8 ± 11.8 | 0.893 | |||||||
HRR 2 min (bpm) | PRED-G | 28.4 ± 9.2 | 34.4 ± 7.3 | 0.014 * | 6.00 (1.19–10.51) 1.00 (−2.35–7.38) | 0.263 | 32.0 ± 12.6 | 36.3 ± 10.9 | 0.010 * | 4.33 (1.15–7.52) |
HRV-G | 36.0 ± 15.0 | 38.5 ± 14.0 | 0.300 | |||||||
VO2 max (mL·kg−1·min−1) | PRED-G | 25.0 ± 5.7 | 28.1 ± 6.0 | 0.005 * | 3.16 (1.21–5.11) | 0.851 | 24.9 ± 5.4 | 28.0 ± 6.0 | <0.001 * | 3.04 (1.70–4.37) |
HRV-G | 24.9 ± 5.3 | 28.0 ± 6.4 | 0.017 * | 2.91 (0.67–5.15) |
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Manresa-Rocamora, A.; Sarabia, J.M.; Guillen-Garcia, S.; Pérez-Berbel, P.; Miralles-Vicedo, B.; Roche, E.; Vicente-Salar, N.; Moya-Ramón, M. Heart Rate Variability-Guided Training for Improving Mortality Predictors in Patients with Coronary Artery Disease. Int. J. Environ. Res. Public Health 2022, 19, 10463. https://doi.org/10.3390/ijerph191710463
Manresa-Rocamora A, Sarabia JM, Guillen-Garcia S, Pérez-Berbel P, Miralles-Vicedo B, Roche E, Vicente-Salar N, Moya-Ramón M. Heart Rate Variability-Guided Training for Improving Mortality Predictors in Patients with Coronary Artery Disease. International Journal of Environmental Research and Public Health. 2022; 19(17):10463. https://doi.org/10.3390/ijerph191710463
Chicago/Turabian StyleManresa-Rocamora, Agustín, José Manuel Sarabia, Silvia Guillen-Garcia, Patricio Pérez-Berbel, Beatriz Miralles-Vicedo, Enrique Roche, Néstor Vicente-Salar, and Manuel Moya-Ramón. 2022. "Heart Rate Variability-Guided Training for Improving Mortality Predictors in Patients with Coronary Artery Disease" International Journal of Environmental Research and Public Health 19, no. 17: 10463. https://doi.org/10.3390/ijerph191710463