Patterns of Use and Reasons for Discontinuation of Prophylactic Medications for Episodic Migraine and Chronic Migraine: Results From the Second International Burden of Migraine Study ( <scp>IBMS‐II</scp> )
Bibliographic record
Abstract
OBJECTIVE: Our objective was to characterize patterns of preventive medication use in persons with episodic migraine (EM) and chronic migraine (CM). BACKGROUND: Several classes of medications are used both on- and off-label for the prevention of migraine, including β-blockers (eg, propranolol, timolol), tricyclic antidepressants (eg, amitriptyline), anti-epileptic drugs (eg, topiramate, valproic acid), and neurotoxins (eg, onabotulinumtoxinA). METHODS: Preventive medication use and reasons for discontinuation were collected in an international, Web-based, cross-sectional survey of adults with migraine during 2010. Descriptive analyses were conducted on demographics and headache-related disability as measured by the Migraine Disability Assessment Scale, stratified by use of preventive medication, and EM or CM. Univariate and multivariate logistic regression models were constructed to assess predictors of preventive medication use. RESULTS: One thousand one hundred and sixty-five respondents completed the survey. Only 28.3% of EM and 44.8% of CM respondents were currently using preventive medication; any use of prophylaxis (prior or current) was reported by 43.4% of those with EM and 65.9% with CM. The mean number of prophylactic medications ever used was 2.92 for EM and 3.94 for CM. Antidepressants were used most frequently (EM 60.9%; CM 54.7%), followed by β-blockers (EM 35.4%; CM 36.8%) and anti-epileptics (EM 28.6%; CM 36.3%). Odds of preventive medication use were higher among CM than EM, adjusting for age, gender, race, years of daily headache, and country (odds ratio 2.72; 95% confidence interval 2.15 to 3.57). Greater headache-related disability and older age were also associated with greater odds of ever having used prophylaxis, regardless of headache frequency. CONCLUSIONS: Less than half the persons with EM and CM were currently using preventive medication for migraine, with treatment rates being higher for CM, as expected. Those with CM tried more medications than those with EM, possibly reflecting higher levels of treatment need.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".