E valuation of M aintained Physic A l Ca P acity 1-yr After Coronary Patient Cardiac Rehabilitation (EMAP) : A FRENCH MULTICENTER STUDY.

PURPOSE: Data are scarce concerning the sustainable effects of cardiac rehabilitation (CR), on cardiorespiratory fitness (CRF) of patients with coronary artery disease (CAD). This study, carried out using data from a French multicenter study, aimed to clarify the evolution of the CRF of patients with CAD 1 yr after the end of a CR stay. METHODS: Patients were included after an acute coronary syndrome (77%) and/or coronary revascularization, occurring <3 mo beforehand. All underwent a CR program with CRF evaluation by exercise testing (ET) on a cycle ergometer at the beginning of CR (ET1), at its end (ET2), and 1 yr later (ET3)-all ETs were performed with medication. RESULTS: Two hundred fifty-nine patients were included (age 60 ± 10 yr, 89% male) in 16 French CR centers. Left ventricular ejection fraction was 55.3 ± 9%. Revascularization was complete (82%). Maximal workloads were 110 ± 37 (ET1), 139 ± 43 (ET2), and 144 ± 46 W (ET3) ( P < .001). The estimated metabolic equivalents of the task (METs) were respectively 5.3 ± 1.4, 6.4 ± 1.6 ( P < .001), and 6.6 ± 1.7 ( P < .002). One year later, 163 patients (63%) improved or maintained their CRF (ET3 ≥ ET2), 73 (28%) decreased (ET1 < ET3 < ET2), and 23 (9%) lost the benefit of CR (ET3 ≤ ET1). CONCLUSION: Among completers who agreed to enroll in this study, most patients with CAD seem to maintain their CRF 1 yr after CR.

Cardiac Events in World-Class Athletes: An Internet-Based Study.

PURPOSE: This study aimed at assessing the prevalence of adverse cardiac events, as identified in the media, in world-class athletes according to their sex and sports discipline. METHODS: All female and male athletes from 30 individual Olympic sports who ranked in the international yearly top 10 between 2006 and 2018 were included. The name of each of them was associated in a Google search with selected key terms related to heart disease and/or acute cardiac events after their inclusion date. Global and sex-specific adverse cardiac event hazard function λ were calculated for each sport. Global and sex-specific prevalences of cardiac events were calculated, then compared (Fisher's exact test) between all sports. RESULTS: From the 2471 athletes included, 15 cases of cardiac events (prevalence of 0.61%) were reported; 2 sudden cardiac deaths (0.08%) occurred in male athletes. The other events were related to arrhythmic events ( n = 13), mainly supraventricular arrhythmias ( n = 9). All surviving athletes were able to continue their career, mostly after ablation procedure. Male endurance athletes accounted for seven events, among which three events occurred among short-distance triathletes. Events among women were comparatively rare ( n = 4), and all were observed among short-distance triathletes. CONCLUSIONS: A relatively unexpected high prevalence of cardiac events in endurance elite athletes was observed as compared with other sports, mainly, in short-distance male and female triathletes. This raises the question of particular cardiovascular constraints in this discipline and underlines the urge of international longitudinal follow-up studies in these kinds of athletes.

Modeling Stress-Recovery Status Through Heart Rate Changes Along a Cycling Grand Tour.

BACKGROUND: Heart rate (HR) and HR variability (HRV) indices are established tools to detect abnormal recovery status in athletes. A low HR and vagally mediated HRV index change between supine and standing positions reflected a maladaptive training stress-recovery status. OBJECTIVES: Our study was focused on a female multistage cycling event. Its overall aim was twofold: (1) quantify the correlation between (a) the change in HR and HRV indices during an active orthostatic test and (b) subjective/objective fatigue, physical load, and training level indicators; and (2) formulate a model predicting the stress-recovery status as indexed by Δ â¢ R ⁢ R ¯ and ΔLnRMSSD (defined as the difference between standing and supine mean RR intervals and LnRMSSD, respectively), based on subjective/objective fatigue indicators, physical load, and training levels. METHODS: Ten female cyclists traveled the route of the 2017 Tour de France, comprising 21 stages of 200 km on average. From 4 days before the beginning of the event itself, and until 1 day after its completion, every morning, each cyclist was subjected to HR and HRV measurements, first at rest in a supine position and then in a standing position. The correlation between HR and HRV indices and subjective/objective fatigue, physical load, and training level indicators was then computed. Finally, several multivariable linear models were tested to analyze the relationships between HR and HRV indices, fatigue, workload, and training level indicators. RESULTS: HR changes appeared as a reliable indicator of stress-recovery status. Fatigue, training level, and Δ â¢ R ⁢ R ¯ displayed a linear relationship. Among a large number of linear models tested, the best one to predict stress-recovery status was the following: Δ â¢ R ⁢ R ¯ = 1,249.37+12.32V̇O2 max + 0.36 km⋅week-1-8.83 HR max -5.8 RPE-28.41 perceived fatigue with an adjusted R 2 = 0.322. CONCLUSION: The proposed model can help to directly assess the adaptation status of an athlete from RR measurements and thus to anticipate a decrease in performance due to fatigue, particularly during a multistage endurance event.

Rugby game performances and weekly workload: Using of data mining process to enter in the complexity.

This study aimed to i) identify key performance indicators of professional rugby matches, ii) define synthetic indicators of performance and iii) analyze how weekly workload (2WL) influences match performance throughout an entire season at different time-points (considering WL of up to 8 weeks prior to competition). This study uses abundant sports data and data mining techniques to assess player performance and to determine the influence of 2WL on performance. WL, locomotor activity and rugby specific actions were collected on 14 professional players (26.9 ± 1.9 years) during training and official matches. In order to highlight key performance indicators, a mixed-linear model was used to compare the players' activity relatively to competition results. This analysis showed that defensive skills represent a fundamental factor of team performance. Furthermore, a principal component analysis demonstrated that 88% of locomotor activity could be highlighted by 2 dimensions including total distance, high-speed/metabolic efforts and the number of sprints and accelerations. The final purpose of this study was to analyze the influence that WL has on match performance. To verify this, 2 different statistical models were used. A threshold-based model, from data mining processes, identified the positive influence (p<0.05) that chronic body impacts has on the ability to win offensive 1 on 1 duels during competition. This study highlights practical implications necessary for developing a better understanding of rugby match performance through the use of data mining processes.