Changes in Cardiac Variability after REM Sleep Deprivation in Recurrent Nightmares
Bibliographic record
Abstract
STUDY OBJECTIVES: To assess whether dysfunctional autonomic regulation during REM sleep as indexed by heart rate variability (HRV) is a pathophysiological factor in frequent nightmares (NMs). DESIGN: Monitoring with polysomnography (PSG) and electrocardiography (ECG) for 3 consecutive nights: Night 1 (N1), adaptation night; N2, administration of partial REM sleep deprivation; N3, recovery night. Differences between NM and control (CTL) groups assessed for ECG measures drawn from wakefulness, REM sleep, and Stage 2 sleep on both N1 and N3. SETTING: Hospital-based sleep laboratory. PARTICIPANTS: Sixteen subjects with frequent NMs (> or = 1 NM/week; mean age = 26.1 +/- 8.7 years) but no other medical or psychiatric disorders and 11 healthy comparison subjects ( < 1 NM/month; mean age = 27.1+/- 5.6 years). RESULTS: NM and CTL groups differed on 2 REM sleep measures only on N1; the NM group had longer REM latencies and REM/NREM cycle durations than did the CTL group. No differences were found on time domain and absolute frequency domain ECG measures for either N1 or N3. However, altered HRV for the NM group was suggested by significantly higher LFnu, lower HFnu, and higher LF/HF ratio than for the CTL group. CONCLUSIONS: Results are consistent with a higher than normal sympathetic drive among NM subjects which is unmasked by high REM sleep propensity. Results also support a growing literature linking anxiety disorders of several types (panic disorder, posttraumatic stress disorder (PTSD), generalized anxiety disorder) to altered HR variability.
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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".