Overload blunts baroreflex only in overreached athletes

Bourdillon, Nicolas; Yazdani, Sasan; Nilchian, Masih; Mariano, Alessio; Vesin, Jean‐Marc; Millet, Grégoire P.

doi:10.1016/j.jsams.2018.01.008

Cited by 9 publications

(30 citation statements)

References 35 publications

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“…Out of 15 studies included in the qualitative synthesis, 12 (80%) measured resting vagalrelated HRV indices, of which, four (33%) reported RMSSD 23,25,51,52 and two (17%) reported HF, 24,53 while five (42%) reported RMSSD and HF 9,54-57 and one (8%) reported RMSSD, HF, and SD 1 . 12 Out of eight studies which reported HF, four (50%) determined power spectral density by FFT, 12,[53][54][55] three (38%) used other methods (auto-regressive, wavelet decomposition, or Goertz algorithms) 9,24,57 and one (12%) did not report this information. 55 Ten studies (83%) recorded the R-R interval with a HR monitor 9,12,[23][24][25][51][52][53]55,57 and two (17%) used an electrocardiogram.…”

Section: Assessment Characteristicsmentioning

confidence: 99%

“…12 Out of eight studies which reported HF, four (50%) determined power spectral density by FFT, 12,[53][54][55] three (38%) used other methods (auto-regressive, wavelet decomposition, or Goertz algorithms) 9,24,57 and one (12%) did not report this information. 55 Ten studies (83%) recorded the R-R interval with a HR monitor 9,12,[23][24][25][51][52][53]55,57 and two (17%) used an electrocardiogram. 54,56 Authors of 10 studies (83%) explicitly stated that data processing to identify and remove artifacts and ectopic beats was performed before carrying out HRV analyses, of which, six studies (60%) performed data processing by interpolation algorithms, 12,24,[53][54][55]57 three (30%) by filtering, 9,25,51 and one (10%) did not report this information.…”

Section: Assessment Characteristicsmentioning

confidence: 99%

“…55 Ten studies (83%) recorded the R-R interval with a HR monitor 9,12,[23][24][25][51][52][53]55,57 and two (17%) used an electrocardiogram. 54,56 Authors of 10 studies (83%) explicitly stated that data processing to identify and remove artifacts and ectopic beats was performed before carrying out HRV analyses, of which, six studies (60%) performed data processing by interpolation algorithms, 12,24,[53][54][55]57 three (30%) by filtering, 9,25,51 and one (10%) did not report this information. 55 Three studies (25%) performed nocturnal assessments while athletes slept to obtain HRV indices, 12,53,57 five (42%) carried out laboratory-based measures 23,24,52,54,56 and four (33%) performed daily morning waking assessments, 9,25,51,55 using a 7-day averaged HRV value (henceforth, weekly averaged HRV value).…”

Section: Assessment Characteristicsmentioning

confidence: 99%

“…12 Out of nine studies that performed laboratory-based or daily morning waking assessments, three (33%) carried out assessments in the supine position, 52,54,56 one (11%) in the standing position, 25 three (33%) performed measures in supine and standing positions, 9,51,55 and two (22%) used other positions. 23,24 Four studies (44%) allowed the athletes to breathe spontaneously throughout HRV assessment, 9,23,55,56 one (11%) controlled the breathing rate 24 and four (44%) did not explicitly report this information. 25,51,52,58 The recording length of laboratory-based and daily waking measures ranged from 5 to 30 min and from 2 to 6 min, respectively.…”

Section: Assessment Characteristicsmentioning

confidence: 99%

“…25,51,52,58 The recording length of laboratory-based and daily waking measures ranged from 5 to 30 min and from 2 to 6 min, respectively. Four studies (33%) reported their findings based on averaged HRV values, 25,51,55,57 seven (58%) used isolated HRV values 12,23,24,[52][53][54]56 and one (8%) reported averaged and isolated HRV values. 9…”

Section: Assessment Characteristicsmentioning

confidence: 99%

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Heart rate‐based indices to detect parasympathetic hyperactivity in functionally overreached athletes. A meta‐analysis

Manresa‐Rocamora

Flatt

Casanova-Lizón

et al. 2021

Scandinavian Med Sci Sports

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Investigations into the sensitivity of heart rate-(HR) derived indices for tracking parasympathetic nervous system (PNS) changes in functionally overreached (F-OR) endurance-trained athletes have produced equivocal findings. Lack of clarity may be a result of methodological inconsistencies. Therefore, the aims of this systematic review and meta-analysis were (a) to determine the sensitivity of resting and post-exercise vagal-related HR variability (HRV) and HR recovery (HRR) indices to detect PNS modulation in F-OR and non-overreached (non-OR) athletes, and (b) to investigate the influence of methodological factors on the sensitivity of HR-based indices to detect PNS hyperactivity in F-OR athletes. We searched CENTRAL, Scopus, PubMed, Embase, and Web of Science up to May 2020 for the following terms: male and female endurance-trained athletes, controlled and uncontrolled studies that carried out an overload training period, and PNS modulation measured in resting and post-exercise, pre-and post-overload training period. A random-effects model of standardized mean difference (SMD) was estimated for each outcome measure based on the training-induced fatigue status (F-OR vs non-OR athletes), and the influence of methodological issues to detect PNS hyperactivity in F-OR was assessed by subgroup analyses. Pooled analysis showed that resting vagal-related HRV indices did not detect PNS hyperactivity in F-OR athletes (SMD + = −0.01; 95% confidence interval [CI] = −0.51, 0.50), and no statistical difference (P = .600) was found with non-OR athletes (SMD + = 0.15; 95% CI = −0.14, 0.45). However, subgroup analysis based on HRV parameter showed a moderate statistical increase in weekly averaged HRV in F-OR athletes (SMD + = 0.81; 95% CI = 0.35, 1.26), while isolated HRV values did not reach statistical significance (SMD + = −0.45; 95% CI = −0.96, 0.06).We observed a moderate and statistically significant increase in HRR indices among F-OR athletes (SMD + = 0.65; 95% CI = 0.44, 0.87), no changes for non-OR athletes (SMD + = 0.10; 95% CI = −0.15, 0.34), and statistically significant differences between F-OR and non-OR athletes (P < .001). Insufficient data prevented metaanalysis for post-exercise vagal-related HRV indices. Our findings show that when methodological factors are considered, HR-based indices are sensitive to increased PNS modulation in F-OR.

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Section: Assessment Characteristicsmentioning

confidence: 99%

Section: Assessment Characteristicsmentioning

confidence: 99%

Section: Assessment Characteristicsmentioning

confidence: 99%

Section: Assessment Characteristicsmentioning

confidence: 99%

Section: Assessment Characteristicsmentioning

confidence: 99%

See 3 more Smart Citations

Heart rate‐based indices to detect parasympathetic hyperactivity in functionally overreached athletes. A meta‐analysis

Manresa‐Rocamora

Flatt

Casanova-Lizón

et al. 2021

Scandinavian Med Sci Sports

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Monitoring fatigue state with heart rate‐based and subjective methods during intensified training in recreational runners

Nuuttila,

Uusitalo,

Kokkonen

et al. 2024

European Journal of Sport Science

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The purpose of this study was firstly to examine the sensitivity of heart rate (HR)‐based and subjective monitoring markers to intensified endurance training; and secondly, to investigate the validity of these markers to distinguish individuals in different fatigue states. A total of 24 recreational runners performed a 3‐week baseline period, a 2‐week overload period, and a 1‐week recovery period. Performance was assessed before and after each period with a 3000m running test. Recovery was monitored with daily orthostatic tests, nocturnal HR recordings, questionnaires, and exercise data. The participants were divided into subgroups (overreached/OR, n = 8; responders/RESP, n = 12) based on the changes in performance and subjective recovery. The responses to the second week of the overload period were compared between the subgroups. RESP improved their baseline 3000 m time (p < 0.001) after the overload period (−2.5 ± 1.0%), and the change differed (p < 0.001) from OR (0.6 ± 1.2%). The changes in nocturnal HR (OR 3.2 ± 3.1%; RESP −2.8 ± 3.7%, p = 0.002) and HR variability (OR −0.7 ± 1.8%; RESP 2.1 ± 1.6%, p = 0.011) differed between the subgroups. In addition, the decrease in subjective readiness to train (p = 0.009) and increase in soreness of the legs (p = 0.04) were greater in OR compared to RESP. Nocturnal HR, readiness to train, and exercise‐derived HR‐running power index had ≥85% positive and negative predictive values in the discrimination between OR and RESP individuals. In conclusion, exercise tolerance can vary substantially in recreational runners. The results supported the usefulness of nocturnal HR and subjective recovery assessments in recognizing fatigue states.

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Functional Overreaching in Endurance Athletes: A Necessity or Cause for Concern?

Bellinger

2020

Sports Med

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There are variable responses to short-term periods of increased training load in endurance athletes, whereby some athletes improve without deleterious effects on performance, while others show diminished exercise performance for a period of days to months. The time course of the decrement in performance and subsequent restoration, or super compensation, has been used to distinguish between the different stages of the fitness-fatigue adaptive continuum termed functional overreaching (FOR), non-functional overreaching (NFOR) or overtraining syndrome. The short-term transient training-induced decrements in performance elicited by increases in training load (i.e., FOR) is thought be a sufficient and necessary component of a training program and is often deliberately induced in training in order to promote meaningful physiological adaptations and performance super-compensation. Despite the supposition that deliberately inducing FOR in athletes may be necessary in order to achieve performance supercompensation, FOR has been associated with various negative cardiovascular, hormonal and metabolic consequences. Furthermore, recent studies have demonstrated dampened training and performance adaptations in FOR athletes compared to non-overreached athletes who completed the same training program or the same relative increase in training load. However, this is not always the case and a number of studies have also demonstrated substantial performance super-compensation in athletes who were classified as being FOR. It is possible that there are a number of contextual factors that may influence the metabolic consequences associated with FOR and classifying this training-induced state of fatigue based purely on adecrement in performance may be an oversimplification. Here, the most recent research on FOR in endurance athletes will be critically evaluated to determine: i) if there is sufficient evidence to indicate that inducing a state of FOR is necessary and required in order to induce a performance super-compensation; ii) the metabolic consequences that are associated with FOR, and; iii) strategies that may prevent the negative consequences of overreaching.

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Overload blunts baroreflex only in overreached athletes

Cited by 9 publications

References 35 publications

Heart rate‐based indices to detect parasympathetic hyperactivity in functionally overreached athletes. A meta‐analysis

Heart rate‐based indices to detect parasympathetic hyperactivity in functionally overreached athletes. A meta‐analysis

Monitoring fatigue state with heart rate‐based and subjective methods during intensified training in recreational runners

Functional Overreaching in Endurance Athletes: A Necessity or Cause for Concern?

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