Heart Rate Variability of Recently Concussed Athletes at Rest and Exercise
Bibliographic record
Abstract
PURPOSE: The objective of this study was to assess the neuroautonomic cardiovascular regulation in recently concussed athletes at rest and in response to low-moderate steady-state exercise, using heart rate variability (HRV). METHODS: A 5-min ECG sample was taken at rest from the 14 concussed athletes at 1.8 (+/- 0.2) days postinjury and again at 5 d later. Once asymptomatic at rest, the concussed athletes and their matched controls (N = 14) participated in an exercise protocol. The protocol consisted of a 2-min warm-up with a pedaling frequency between 50 and 60 rpm against a load of 40 W. After the warm-up, the athletes engaged in a low-moderate intensity steady state 10-min exercise bout where the pedaling frequency and load increased to 80-90 rpm and 1.5 W x kg(-1) body weight, respectively. The protocol was repeated 5 d later. A 5-min ECG sample from minutes 4 to 9 of the low-moderate intensity steady state exercise bout was used to assess HRV during exercise. Mixed model ANOVA were used to analyze the data. RESULTS: No difference at rest was detected between the concussed athletes and their matched controls in any of the HRV variables measured. However, across both exercise tests, the concussed group demonstrated a significant decrease in the mean RR interval, and low- and high-frequency power (P < 0.05) in relation to their matched controls. CONCLUSION: Low-moderate steady-state exercise elicits a neuroautonomic cardiovascular dysfunction in concussed athletes that is not present in a rested state. This dysfunction alludes to an exercise induced uncoupling between the autonomic and cardiovascular systems.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".