Association Between Asthma and Migraine: A Systematic Review and Meta-Analysis of Observational Studies
Bibliographic record
Abstract
Objectives: The purpose of this study was to determine the association between asthma and migraine and assess the risk for migraine in patients with asthma. Methods: We systematically searched the Cochrane Library, PubMed, Medical Literature Analysis and Retrieval System Online (MEDLINE), and Excerpta Medica dataBASE (EMBASE) databases from inception to September 26, 2021, for indexed observational studies that examined either the odds or risk of migraine in subjects with asthma. The qualities of the included studies were evaluated using the Newcastle–Ottawa Scale. A random-effects meta-analysis was performed to calculate the odds ratio for case-control and cross-sectional studies and the risk ratio for cohort studies. Results: Seven observational studies (four cross-sectional and three cohort studies) with a total of 549,534 study subjects were included in this systematic review and meta-analysis and selected for data extraction. Four articles were considered to be of moderate quality; other studies were considered to be of high quality. Asthma was associated with increased odds (OR, 1.85; 95%CI, 1.39–2.45) and risk of migraine (RR, 1.70; 95%CI, 1.52–1.90). Conclusions: The available evidence that supports the existence of an association between asthma and migraine is limited. Clinicians should be aware that patients with asthma show both increased prevalence and incidence of migraine. Further studies are warranted to further clarify the relationship between asthma and migraine. Systematic Review Registration: https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=185881 , identifier: CRD42020185881.
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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 | 0.020 | 0.051 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.034 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| 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".