Chinook winds and migraine attack onset in children and adolescents: A prospective longitudinal clinical cohort study
Bibliographic record
Abstract
OBJECTIVE: To explore the relationship between migraine attack onset in children and adolescents and Chinooks, which are dry and warm westerly winds that generally occur in the winter and bring about abrupt weather changes to the east of the Rocky Mountains in Southern Alberta, Canada. METHODS: This was a prospective longitudinal clinical cohort study with recruitment from November 2020 to May 2024. Participants were: 8-18 years old, had migraine as per International Classification of Headache Disorders 3rd edition criteria, had 1-15 headache days/month, lived in the geographical location where Chinook winds occur, and had exposure to at least one pre-Chinook or Chinook day during the study period. Chinook days were defined using Nkemdirim's criteria and Environment Canada data were used to categorize day type as either Chinook, pre-Chinook, or non-Chinook. Weather data were merged with data from daily headache diaries, completed for periods of 8-30 days. The primary outcome was attack onset, defined as a day with a new migraine attack of moderate or severe severity, as per the 4-point scale (0 = none, 1 = mild, 2 = moderate, and 3 = severe). Both univariate and adjusted models were used to determine if there was an association between migraine attack onset and day type (i.e., pre-Chinook, Chinook, or non-Chinook) at the aggregate study sample level. The adjusted models controlled for age and sex, and both models included a random intercept. Subsequently, individual n = 1 models were fitted to explore each individual participant's personal odds of migraine attack onset on both pre-Chinook and Chinook days versus non-Chinook days. Pre-Chinook/Chinook sensitivity values were calculated for each individual by dividing the model's regression coefficient by its standard error. Sensitivity values >1.96 suggest a significant association between pre-Chinook/Chinook days and attack onset. RESULTS: Sixty youth with 1253 days of complete data, of which 144 (12%) were attack onset days, participated in the study. There were 158 Chinook (13%), 124 pre-Chinook (10%), and 971 non-Chinook days (77%). There were 39 female participants (39 of 60; 65%), with a median age of 14 years (quartile [Q] 1 = 12, Q3 = 16), and a median headache frequency of 6.2 days/month (Q1 = 4, Q3 = 11). Neither the univariate nor the adjusted models found any significant association between day type and attack onset at an aggregate level (pre-Chinook adjusted odds ratio [OR], 0.98; 95% confidence interval [CI], 0.54-1.78, p = 0.947; Chinook adjusted OR, 1.15; 95% CI, 0.69-1.91, p = 0.596). No individual participants met the threshold for statistically significant pre-Chinook or Chinook sensitivity. CONCLUSION: We did not find a relationship between pre-Chinook and Chinook conditions and migraine attack onset. This may be due to the lack of an association between Chinooks and attack onset in youth with migraine, or due to a lack of statistical power in our study. Future studies with greater statistical power should aim to assess for a potential relationship between Chinooks and attack onset, as it could have important treatment implications.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".