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Title: Quantification of exercise training dose in phase III cardiac rehabilitation : a UK perspective
Author: Khushhal, Alaa
ISNI:       0000 0004 8504 3180
Awarding Body: University of Hull
Current Institution: University of Hull
Date of Award: 2019
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The Apple watch was a new technology first introduced in 2015. At that time, its validity and reliability for measuring stepping frequency and heart rate monitoring during exercise was unknown. Current evidence indicates that the effectiveness of cardiac rehabilitation (CR) programmes for improving patient outcomes may be questionable in the United Kingdom (UK). We postulated that the exercise dose that patients receive during Phase III CR may not be a high enough stimulus to invoke a positive physiological adaptation. Therefore, this thesis aims to examine the validity and reliability of the Apple watch for measuring heart rate and step frequency. We then planned, based on our initial findings, to apply this technology to patients undertaking Phase III CR in order to monitor and quantify exercise dose and training progression to determine the fidelity of the intervention. The aim of the first study was to examine the validity and variability of the Apple watch for measuring step count. On two occasions, 21 males completed treadmill exercise while wearing two Apple watches (left and right wrists) and an ActivPAL (criterion). Exercise involved 5 min bouts of walking, jogging, and running at speeds of 4 km.h⁻¹, 7 km.h⁻¹, and 10 km.h⁻¹, followed by 11 min of rest between each bout. There was a small under-estimation in step count during walking but large and very large over-estimations during jogging and running. There were poor to very poor correlations during walking, jogging and running. The inter-device variability showed good to nearly perfect intraclass correlations and small to moderate standardised typical errors. Intra-device variability was large to very large for all exercise intensities. The Apple watch has adequate validity for measuring step count during walking, but very poor validity during jogging and running. On this basis, we concluded that quantifying stepping frequency during Phase III CR using the Apple watch should not be pursued. The aim of the second study was to examine the validity and reliability of the Apple watch heart rate sensor during and in recovery from exercise. Twenty-one males completed treadmill exercise while wearing two Apple watches (left and right wrists) and a Polar S810i monitor (criterion). Exercise involved 5 min bouts of walking, jogging, and running at speeds of 4 km.h⁻¹, 7 km.h⁻¹, and 10 km.h⁻¹, followed by 11 min of rest between bouts. At all exercise intensities the mean bias was trivial. There were very good correlations with the criterion during walking (L: r = 0.97; R: r = 0.97), and good (L: r = 0.93; R: r = 0.92) but poor/good (L: r = 0.81; R: r = 0.86) correlations during jogging and running. Standardised typical error of the estimate was small, moderate, and moderate to large. There were good correlations following walking, but poor correlations following jogging and running. The percentage of heart rates recorded reduced with increasing intensity but increased over time. Intra-device standardised typical errors decreased with intensity. Inter-device standardised typical errors were small to moderate with very good to nearly perfect intraclass correlations. The Apple watch heart rate sensor has very good validity during walking but validity decreases with increasing intensity. On this basis, we chose to introduce the Apple watch to a Phase III CR programme for monitoring individual exercise dose via heart rate. The aim of the third study was to investigate the fidelity of a structured Phase III cardiac rehabilitation (CR) programme in the United Kingdom (UK), by monitoring and quantifying exercise training intensity. We compared the mean % heart rate reserve (%HRR) achieved during the cardiovascular training component (%HRR-CV) of a circuit-based programme, with the %HRR during the active recovery phases (%HRR-AR) in a randomly selected cohort of patients attending standard CR. We then compared the mean %HRR-CV achieved with the minimal exercise intensity threshold during supervised exercise (40% HRR) recommended by national governing bodies. The programme comprised 16 sessions over 8 weeks, where patients undertook an interval, circuit training approach within national guidelines for exercise prescription (40-70% heart rate reserve [HRR]). All patients wore an Apple watch (Series 0 or 2, Watch OS2.0.1, Apple Inc., California, USA). Thirty cardiac patients (83% male; mean age [SD] 67 [10] years; BMI 28.3 [4.6] kg∙m-2) were recruited. We captured 332 individual training sessions. The mean %HRR-CV and %HRR-AR were 37 (10) %, and 31 (13) %, respectively. There was weak evidence to support the alternative hypothesis of a difference between the %HRR-CV and 40% HRR. There was very strong evidence to accept the alternative hypothesis that the mean %HRR-AR was lower than the mean %HRR-CV (median standardised effect size 1.1 (95%CI: 0.563 to 1.669) with a moderate to large effect. Mean exercise training intensity was below the lower limit of the minimal training intensity guidelines for a Phase III CR programme. These findings may be in part responsible for previous reports highlighting the significant variability in effectiveness of UK CR services and poor CRF improvements observed from several prior investigations. The aim of the final study was to characterise the weekly progression of exercise training dose/load over an 8-week Phase III cardiac rehabilitation (CR) programme based in the United Kingdom (UK). Patients with a history of cardiovascular (CV) disease were recruited to an 8-week CR programme (16 sessions in total). During each training session, patients wore an Apple Watch (Series 0 or 2, Watch OS2.0.1, Apple Inc., California, USA) and we quantified the weekly progression of exercise training dose/load for % heart rate reserve (%HRR) during the CV training component (%HRR-CV), CV training duration, estimated changes in cardiorespiratory fitness (change in estimated METS), session rating of perceived exertion (sRPE), sRPE training load (sRPE-TL), and training impulse (TRIMP). Thirty cardiac patients [83% male; age (SD) 67.0 (10.0) years; body mass index (SD) 28.3 (4.6) kg∙m⁻²] were recruited to the Phase III CR programme. Overall our analysis is based on 332 individual training sessions. Bayesian repeated-measures ANOVA resulted in a BF₁₀ of 1.1 to 3.1, indicating weak to moderate evidence for the alternative hypothesis of an effect of time on %HRR-CV, sRPE, and change in estimated METs. Conversely, Bayesian repeated-measures ANOVA resulted in a BF10 of between 103,977 to 1,018,000, indicating extremely strong evidence for the alternative hypothesis of an effect of time on CV training duration, TRIMP, and sRPE-TL. The training principle of progressive overload is being applied consistently in CR. However, the increases observed in exercise training dose were mostly the result of increases in the duration of CV training rather than increases in exercise training intensity (%HRR-CV and sRPE). Therefore, allied health professionals must ensure that weekly increases in exercise intensity are consistently applied in order to optimise exercise training prescription and improve patient outcomes. We can conclude from the studies within this PhD thesis that allied health professionals involved in CR should undertake more advanced training in exercise training, programming and prescription to ensure that principles of training including progressive overload are understood and implemented correctly. Allied health professionals should also have a greater understanding of the benefits of exercise and physical activity, and this knowledge should be passed on to patients in the hope that they adopt a more active lifestyle beyond Phase III CR. The increased use of digital/wearable technology should be actively encouraged which will help support allied health professionals monitor, track, and up-titrate exercise dose over the course of a CR programme. Predictive heart rate training zones should be re-calculated regularly, as resting heart should be re-checked before the start of each training session. We also recommend using more cohort-specific predictive equations such as the Brawner equation which accounts for use of beta-blockers. We recommend to allied health professionals the Apple watch for monitoring heart rate throughout each training session, our studies show that at lower intensities of exercise the Apple watch is a valid and reliable tool. One downside to using the Apple watch is their excessive cost in relation to other activity trackers. Cost needs to weighed against the accuracy of the data provided.
Supervisor: Ingle, Lee ; Abt, Grant ; Carroll, Sean Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Sports science