Case report: Biphasic autonomic response in decompression sickness: HRV and sinoatrial findings
Bibliographic record
Abstract
Background: Decompression sickness (DCS) may involve neurological and cardiovascular systems, but cardiac autonomic dysfunction is rarely documented. Heart rate variability (HRV) can provide insight into autonomic modulation in such cases, particularly when incorporating advanced nonlinear and dynamic techniques. Case: We present a 35-year-old recreational diver who developed neurological DCS and persistent bradycardia following multiple consecutive dives. Neurological symptoms resolved with hyperbaric oxygen therapy (HBOT), but bradyarrhythmias persisted, prompting continuous monitoring. Methods: HRV was assessed using time-domain, frequency-domain, nonlinear, and dynamic analyses during HBOT and over two 24-h Holter recordings. Principal Dynamic Mode (PDM) analysis was employed to characterize autonomic control dynamics beyond conventional spectral markers. Results: during HBOT), SD1/SD2 ratio declined from 0.52 to 0.12, suggesting selective vagal withdrawal. PDM analysis showed a low PDM2/PDM1 ratio (0.42), consistent with preserved beat-to-beat vagal responsiveness but impaired long-range autonomic integration. Conclusion: This case illustrates a biphasic autonomic pattern in DCS-initial parasympathetic dominance followed by sympathetic tilt and desynchronization. Advanced nonlinear and dynamic HRV analysis revealed regulatory disturbances not captured by traditional methods, supporting its role in post-dive assessment and autonomic monitoring.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".