Clinical factors associated with day‐to‐day peak pain severity in individuals with chronic migraine: A cohort study using daily prospective diary data
Bibliographic record
Abstract
OBJECTIVE: To describe the association between day-to-day peak pain severity and clinical factors in individuals with chronic migraine (CM). BACKGROUND: Little is known about how clinical factors relate to day-to-day pain severity in individuals with CM. METHODS: Adults with CM were enrolled into this observational prospective cohort study that collected daily data about headache, associated symptoms, and lifestyle factors using a digital health platform (N1-Headache™) for 90 days. "Migraine days" were defined as days in which a headache occurred that had features described by the International Classification of Headache Disorders criteria. On these days, peak pain severity was recorded on a 4-point scale; on non-headache days peak pain severity was imputed as "0/none". The associations between peak pain severity and 12 clinical factors were modeled and adjusted for sex, age, daily headache, presence of menstrual bleeding, day of the week, and disability. All numerical and Likert scale variables were standardized prior to analysis. RESULTS: Data were available for 392 participants (35,280 tracked days). The sample was predominantly female (90.6%), with a mean (standard deviation) age of 39.9 (12.8) years. In the final multivariable model with random intercept and slopes, higher than typical self-reported levels of standardized stress (odds ratio [OR] 1.07, 95% confidence interval [CI] 1.04-1.11), standardized irritability (OR 1.05, 95% CI 1.02-1.08), standardized sadness (OR 1.05, 95% CI 1.02-1.07), fatigue (OR 1.25, 95% CI 1.15-1.36), eyestrain (OR 1.38, 95% CI 1.26-1.52), neck pain (OR 1.94, 95% CI 1.76-2.13), skin sensitivity (OR 1.61, 95% CI 1.44-1.80), and dehydration (OR 1.29, 95% CI 1.18-1.42) were associated with higher reported peak pain severity levels, while standardized sleep quality (OR 0.96, 95% CI 0.93-0.99) and standardized waking feeling refreshed (OR 0.84, 95% CI 0.81-0.88) were associated with lower reported peak pain severity levels. The inclusion of a random intercept and random slopes improved upon more parsimonious models and illustrated large differences in individuals' reporting of peak severity according to the levels of the associated clinical factors. CONCLUSION: Our data showed that the experience of CM, from a pain severity perspective, is complex, related to multiple clinical variables, and highly individualized. These results suggest that future work should aim to study a personalized approach to both medical and behavioral interventions for CM based on which clinical factors relate to the individual's experience of pain severity.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".