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Heart Rate Variability At Rest And Recovery After Short-term, High-intensity Exercise In Adolescents

2005· article· en· W4253315862 on OpenAlexaff
Styliani Goulopoulou, Kevin S. Heffernan, Bo Fernhall, Greg Yates, Adam Baxter‐Jones, Viswanath B. Unnithan

Bibliographic record

VenueMedicine & Science in Sports & Exercise · 2005
Typearticle
Languageen
FieldMedicine
TopicHeart Rate Variability and Autonomic Control
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsMedicineHeart rate variabilityHeart rateAutonomic nervous systemInternal medicineCardiologyPhysical therapyBlood pressure

Abstract

fetched live from OpenAlex

Developmental changes that occur in the autonomic nervous system (ANS) from childhood to adulthood might be responsible for the age-related differences in resting and recovery heart rate (HR) after exercise noted between children and adults. The adolescence period is characterized by dynamic physiological changes. There are inconclusive findings with regard to the exact changes that occur in the sympathetic (SNS) and parasympathetic (PNS) nervous systems throughout this period. Moreover, the effect of maturation on ANS function remains unclear. PURPOSE To evaluate the effect of maturity status on ANS function pre-exercise and during recovery after short-term, high-intensity exercise in males aged 12–16 yrs. METHODS Maturity status was evaluated in 27 adolescent males by calculating years from peak height velocity (PHV) using a multiple regression equation. Subjects were divided into 2 groups based on their maturity status [late maturers: pre-PHV group (years from PHV ≤ 0.49), n=14, mean age=12.29 yrs ± 0.91], [advanced maturers: post-PHV (years from PHV ≥ 0.5, n=13, mean age=15.12 yrs ± 0.76]. Heart rate variability (HRV) was used to evaluate ANS function. ECG tracings were collected during 5 min of paced breathing at rest and recovery after a Wingate test and were analyzed in the frequency domain [low-frequency (LF), high-frequency (HF), LF/HF, total power (TP)] using an autoregressive model. RESULTS Changes in HR from HRpeak during exercise to HR measured at 4th min after exercise (ΔHR4) were significantly higher in the pre-PHV group (84.31 bpm +17.58) compared to the post-PHV group (69.42 bpm ± 17.63). There were no significant differences in HRV pre-exercise between pre-PHV and post-PHV groups (p > 0.05). Post-exercise HRV was significantly lower compared to the resting values for both groups (p < 0.05). Significant group-by-time interactions were found for LFLN (ms2) and TPLN (ms2) measured during recovery (p < 0.05). Post- hoc t tests showed that the pre-PHV group had significantly higher post-exercise LFLN[(5.02±0.97) vs. (4.19±0.79)] and TPLN[(6.36±1.02) vs. (5.62±0.65)] compared to the post-PHV group. When post-exercise LFLN (ms2) was normalized for TPLN (ms2), there were no significant differences between groups (p > 0.05). CONCLUSIONS Our data suggests that maturity status significantly affects TP of HRV indicating that the maturation process throughout the adolescent period Influences PNS activity during recovery after high-intensity exercise. Late maturers might recover faster after high- intensity exercise than advanced maturers due to higher vagal modulation.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.012
GPT teacher head0.259
Teacher spread0.247 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations1
Published2005
Admission routes1
Has abstractyes

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