Alpha sleep characteristics in fibromyalgia
Bibliographic record
Abstract
OBJECTIVE: To characterize the patterns of alpha electroencephalographic sleep and their associations with pain and sleep in patients with fibromyalgia. METHODS: Pain and sleep symptoms of 40 female patients with fibromyalgia and 43 healthy control subjects were studied before and after overnight polysomnography. Blinded analyses of alpha activity in non-rapid eye movement (non-REM) sleep were performed using time domain, frequency domain, and visual analysis techniques. RESULTS: Three distinct patterns of alpha sleep activity were detected in fibromyalgia: phasic alpha (simultaneous with delta activity) in 50% of patients, tonic alpha (continuous throughout non-REM sleep) in 20% of patients, and low alpha activity in the remaining 30% of patients. Low alpha activity was exhibited by 83.7% of control subjects (P < 0.01). All fibromyalgia patients who displayed phasic alpha sleep, activity reported worsening of pain after sleep, compared with 58.3% of patients with low alpha activity (P < 0.01) and 25.0% of patients with tonic alpha activity (P < 0.01). Postsleep increase in the number of tender points occurred in 90.0% of patients with phasic alpha activity, 41.7% of patients with low alpha activity, and 25.0% of patients with tonic alpha activity (P < 0.01). Self ratings of poor sleep were reported by all patients with phasic alpha activity, 58.3% of patients with low alpha activity (P < 0.01), and 12.5% of patients with tonic alpha activity (P < 0.01). Patients with phasic alpha activity reported longer duration of pain than patients in other subgroups (P < 0.01). Additionally, patients with phasic alpha sleep activity exhibited less total sleep time than patients in other subgroups (P < 0.05), as well as lower sleep efficiency (P < 0.05) and less slow wave sleep (P < 0.05) than patients with a tonic alpha sleep pattern. CONCLUSION: Alpha intrusion during sleep can be of different patterns. Phasic alpha sleep activity was the pattern that correlated better with clinical manifestations of fibromyalgia.
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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 | 0.001 | 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".