Subjective sleep quality and sleep architecture in patients with migraine: a meta-analysis
Bibliographic record
Abstract
Sleep disturbance is often associated with migraine. However, there is a paucity of research investigating objective and subjective measures of sleep in migraine patients. This meta-analysis aims to determine whether there are differences in subjective sleep quality measured using the Pittsburgh Sleep Quality Index (PSQI), and objective sleep physiology measured using polysomnography between adult and pediatric patients, and healthy controls. This review was pre-registered on PROSPERO (CRD42020209325). A systematic search of five databases (Embase, MEDLINE®, Global Health, APA PsycINFO, APA PsycArticles, last searched: 12/17/2020) was conducted to find case-controlled studies that measured polysomnography and/or PSQI in patients with migraine. Pregnant participants and those with other headache disorders were excluded. Effect sizes (Hedges’ g) were entered into a random effects model meta-analysis. Study quality was evaluated with the Newcastle Ottawa Scale and publication bias with Egger’s regression test. 32 studies were eligible, of which 21 measured PSQI and/or MIDAS in adults, 6 measured PSG in adults, and 5 in children. The overall mean study quality score was 5/9, and this did not moderate any of the results, and there was no risk of publication bias. Overall, adults with migraine had higher PSQI scores than healthy controls (g=0.75, p < .001, 95% confidence interval [95% CI]: 0.54 - 0.96). This effect was larger in those with chronic rather than episodic conditions (g=1.03, p < .001, 95% CI: 0.37 - 1.01, g = 0.63, p < .001, 95% CI: 0.38 - 0.88 respectively). For polysomnographic studies, adults and children with migraine displayed a lower percentage of REM sleep (g=-0.22, p = 0.017, 95% CI: -0.41 - -0.04, g = -0.71, p = 0.025, 95% CI: -1.34 - -0.10 respectively) than controls. Pediatric patients displayed less total sleep time (g=-1.37, p = 0.039, 95% CI: -2.66 - -0.10), more wake (g=0.52, p < .001, 95% CI: 0.08 – 0.79) and shorter sleep onset latency (g=-0.37, p < .001, 95% CI: -0.54 - -0.21) than controls. People with migraines have significantly poorer subjective sleep quality and altered sleep physiology compared to healthy individuals. Further longitudinal empirical studies are required to enhance our understanding of this relationship.
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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 | 0.010 | 0.018 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.052 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".