Higher exercise intensity delays postexercise recovery of impedance-derived cardiac sympathetic activity
Bibliographic record
Abstract
Systolic time intervals (STIs) provide noninvasive insights into cardiac sympathetic neural activity (cSNA). As the effect of exercise intensity on postexercise STI recovery is unclear, this study investigated the STI recovery profile after different exercise intensities. Eleven healthy males cycled for 8 min at 3 separate intensities: LOW (40%-45%), MOD (75%-80%), and HIGH (90%-95%) of heart-rate (HR) reserve. Bio-impedance cardiography was used to assess STIs - primarily pre-ejection period (PEP; inversely correlated with cSNA), as well as left ventricular ejection time (LVET) and PEP:LVET - during 10 min seated recovery immediately postexercise. Heart-rate variability (HRV), i.e., natural-logarithm of root mean square of successive differences (Ln-RMSSD), was calculated as an index of cardiac parasympathetic neural activity (cPNA). Higher preceding exercise intensity elicited a slower recovery of HR and Ln-RMSSD (p < 0.001), and these measures did not return to baseline by 10 min following any intensity (p ≤ 0.009). Recovery of STIs was also slower following higher intensity exercise (p ≤ 0.002). By 30 s postexercise, higher preceding intensity resulted in a lower PEP (98 ± 14 ms, 75 ± 6 ms, 66 ± 5 ms for LOW, MOD, and HIGH, respectively, p < 0.001). PEP recovered to baseline (143 ± 11 ms) by 5 min following LOW (139 ± 13 ms, p = 0.590) and by 10 min following MOD (145 ± 17 ms, p = 0.602), but was still suppressed at 10 min following HIGH (123 ± 21 ms, p = 0.012). Higher preceding exercise intensity attenuated the recovery of indices for cSNA (from STIs) and cPNA (from HRV) in a graded dose-response fashion. While exercise intensity must be considered, acute recovery may be a valuable period during which to concurrently monitor these noninvasive indices, to identify potentially abnormal cardiac autonomic responses.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".