Association of sleep disorders with asthma: a meta-analysis
Bibliographic record
Abstract
Background Animal experiments and clinical trials have revealed a potential relationship between sleep disorders and asthma. However, the associations between these factors remain unclear. Material and methods We searched PubMed, Embase, Web of Science and Cochrane Library databases for eligible studies published before 30 December 2022. Studies investigating the association between sleep disorders (insomnia, poor sleep quality and insufficient sleep time) and asthma were selected. Sleep disorders were assessed using questionnaires, interviews, or medical records. Asthma was diagnosed based on medical history and drug use. The Newcastle-Ottawa Scale and the Agency for Healthcare Research and Quality checklist were employed for quality assessment. We used OR with 95% CI as the effect measures and forest plots to display the results. Heterogeneity was evaluated using I 2 statistics and subgroup analyses were performed for bias analysis. Publication bias was evaluated using the funnel plots and Egger’s test. Results Twenty-three studies were included in the primary analysis, which suggested a positive association between sleep disorders and asthma (OR: 1.38, 95% CI 1.10 to 1.74). Subgroup analyses were conducted according to the study design, age, family history of asthma and type of sleep disorders. We did not find any association between sleep disorders and asthma in children aged ˂12 years (OR: 1.13, 95% CI 0.97 to 1.32). The association was insignificant in studies where the family history of asthma was adjusted for (OR: 1.16, 95% CI 0.94 to 1.42). Funnel plot and Egger’s test indicated a significant publication bias. Conclusion Sleep disorders are associated with an increased prevalence and incidence of asthma. However, the quality of the evidence was low because of potential biases. PROSPERO registration number CRD42023391989.
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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 | 0.019 | 0.036 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.025 | 0.078 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".