A systems model of training for patients in phase 2 cardiac rehabilitation

Bris, Stéphanie Le; Ledermann, Bertrand; Topin, Nathalie; P, Messner-Pellenc; Gallais, Daniel Le

doi:10.1016/j.ijcard.2005.06.029

Cited by 6 publications

(6 citation statements)

References 24 publications

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“…In the present study, the τ 1 values were comparable to those previously reported during training in healthy sedentary subjects or athletes [1,8,30], suggesting that the proposed exercise represents an effective training stimulus in subjects with reduced mobility. The τ 2 values observed are instead higher than those reported in the mentioned studies but congruent with those calculated in a population of cardiopathic patients [12,13] for a possible slower muscle recovery of fatigue even when walking at low-moderate intensity [35].…”

Section: Discussionsupporting

confidence: 87%

“…Inspired by the interesting objective to foresee these effects, the research of several authors involved in exercise physiology, as magisterially reviewed by Clarke et al [1], has tried to develop mathematical models to predetermine/calculate the adaptive response to training stressors [1,5,6]. This approach, primarily of interest in sports to foster the performance and health of athletes [1,[7][8][9][10][11], was also considered of interest for rehabilitation [4] or for subjects with chronic diseases, such as patients undergoing cardiac rehabilitation [12][13][14], to design effective and sustainable programs. Nevertheless, this approach has been poorly exploited in general [1,12], particularly for patients with peripheral artery disease (PAD), where exercise is a cornerstone of treatment in the intermediate stages when reduced oxygen delivery affects walking capacity, quality of life and cardiovascular health [15].…”

Section: Introductionmentioning

confidence: 99%

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A Fitness-Fatigue Model of Performance in Peripheral Artery Disease: Predicted and Measured Effects of a Pain-Free Exercise Program

Lamberti

Piva

Businaro

et al. 2022

JPM

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Banister impulse-response (IR) model estimates the performance in response to the training impulses (TRIMPs). In 100 patients with peripheral artery disease (PAD), we tested by an IR model the predictability of the effects of a 6-month structured home-based exercise program. The daily TRIMPs obtained from prescribed walking speed, relative intensity and time of exercise determined the fitness-fatigue components of performance. The estimated performance values, calculated from the baseline 6-min and pain-free walking distance (6MWD and PFWD, respectively) were compared with values measured at visits through regression models. Interval pain-free walking at controlled speed prescribed during circa-monthly hospital visits (5 ± 1) was safely performed at home with good adherence (92% of scheduled sessions, 144 ± 25 km walked in 50 ± 8 training hours). The mean TRIMP rose throughout the program from 276 to 601 a.u. The measured 6MWD and PFWD values increased (+33 m and +121 m, respectively) showing a good fit with those estimated by the IR model (6MWD: R2 0.81; PFWD: R2 0.68) and very good correspondence (correlation coefficients: 0.91 to 0.95), without sex differences. The decay of performance without training was estimated at 18 ± 3 weeks. In PAD, an IR model predicted the walking performance following a pain-free exercise program. IR models may contribute to design and verify personalized training programs.

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Section: Discussionsupporting

confidence: 87%

Section: Introductionmentioning

confidence: 99%

A Fitness-Fatigue Model of Performance in Peripheral Artery Disease: Predicted and Measured Effects of a Pain-Free Exercise Program

Lamberti

Piva

Businaro

et al. 2022

JPM

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“…Le Bris and coauthors (63,65) published several studies using the models with cardiovascular rehabilitation patients to predict the loss of functional capacity once the rehabilitation program was ceased or otherwise interrupted. Furthermore, the IR model was used to predict the prolonging of fitness benefits accrued by a training regimen featuring five versus three sessions per week in phase 2 rehabilitation patients (64).…”

Section: Power (W)mentioning

confidence: 99%

Rationale and resources for teaching the mathematical modeling of athletic training and performance

Clarke

Skiba

2013

Advances in Physiology Education

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A number of professions rely on exercise prescription to improve health or athletic performance, including coaching, fitness/personal training, rehabilitation, and exercise physiology. It is therefore advisable that the professionals involved learn the various tools available for designing effective training programs. Mathematical modeling of athletic training and performance, which we henceforth call "performance modeling," is one such tool. Two models, the critical power (CP) model and the Banister impulse-response (IR) model, offer complementary information. The CP model describes the relationship between work rates and the durations for which an individual can sustain them during constant-work-rate or intermittent exercise. The IR model describes the dynamics by which an individual's performance capacity changes over time as a function of training. Both models elegantly abstract the underlying physiology, and both can accurately fit performance data, such that educating exercise practitioners in the science of performance modeling offers both pedagogical and practical benefits. In addition, performance modeling offers an avenue for introducing mathematical modeling skills to exercise physiology researchers. A principal limitation to the adoption of performance modeling is a lack of education. The goal of this report is therefore to encourage educators of exercise physiology practitioners and researchers to incorporate the science of performance modeling in their curricula and to serve as a resource to support this effort. The resources include a comprehensive review of the concepts associated with the development and use of the models, software to enable hands-on computer exercises, and strategies for teaching the models to different audiences.

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“…Moreover, this systematic mathematical procedure of modeling offers the possibility of simulating training effects in order to test different strategies, and it may thus be useful for advocating individualized training programs, which constitute the optimal adaptive stimulus. This type of approach was developed to optimize the training process in athletes [ 18 , 19 ], but, with the animal as an experimental model, it could be extended to those chronic diseases for which exercise presents curative properties as already employed in cardiac rehabilitation [ 20 , 21 ]. It would thus be of interest to extend these strategies of rehabilitation programs to rodent models suffering from other chronic diseases (e.g., ob/ob mice, db/db mice for type 2 diabetes, and the streptozotocin model for type 1 diabetes), as direct testing in patients would not be ethical.…”

Section: Discussionmentioning

confidence: 99%

Modeling the Responses to Resistance Training in an Animal Experiment Study

Philippe

Favier

et al. 2015

BioMed Research International

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The aim of the present study was to test whether systems models of training effects on performance in athletes can be used to explore the responses to resistance training in rats. 11 Wistar Han rats (277 ± 15 g) underwent 4 weeks of resistance training consisting in climbing a ladder with progressive loads. Training amount and performance were computed from total work and mean power during each training session. Three systems models relating performance to cumulated training bouts have been tested: (i) with a single component for adaptation to training, (ii) with two components to distinguish the adaptation and fatigue produced by exercise bouts, and (iii) with an additional component to account for training-related changes in exercise-induced fatigue. Model parameters were fitted using a mixed-effects modeling approach. The model with two components was found to be the most suitable to analyze the training responses (R 2 = 0.53; P < 0.001). In conclusion, the accuracy in quantifying training loads and performance in a rodent experiment makes it possible to model the responses to resistance training. This modeling in rodents could be used in future studies in combination with biological tools for enhancing our understanding of the adaptive processes that occur during physical training.

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A systems model of training for patients in phase 2 cardiac rehabilitation

Cited by 6 publications

References 24 publications

A Fitness-Fatigue Model of Performance in Peripheral Artery Disease: Predicted and Measured Effects of a Pain-Free Exercise Program

A Fitness-Fatigue Model of Performance in Peripheral Artery Disease: Predicted and Measured Effects of a Pain-Free Exercise Program

Rationale and resources for teaching the mathematical modeling of athletic training and performance

Modeling the Responses to Resistance Training in an Animal Experiment Study

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