Impact of migraine symptoms on health care use and work loss in Canada in patients randomly assigned in a phase III clinical trial.
Bibliographic record
Abstract
BACKGROUND: Migraine is prevalent and associated with substantial direct and indirect costs that may vary across geographic and national boundaries. The effects of migraine, self-reported by Canadians, on health care resource use as well as paid and unpaid work loss were examined. PATIENTS AND METHODS: The Migraine Background Questionnaire (MBQ) was self-administered during the screening visit of a phase III clinical trial of rizatriptan (a potent, selective 5-hydroxytryptamine(1B/1D)-receptor agonist or 'triptan'). Patients suffering from moderate to severe migraine in the previous six months were offered the opportunity to participate. Migraine frequency was determined and costs were estimated and assigned based on known direct costs of health care resource utilization, and indirect costs of paid and unpaid work and productivity loss. RESULTS: One hundred thirty-four patients completed the MBQ. In the previous year, 89% of those patients reported visiting a clinic, 23% reported visiting an emergency room and 5% reported being hospitalized for migraine. Patients reported an average of 6.5 days absent from work, 44 days working with migraine headache and 10.4 reduced workday equivalents due to ineffectiveness at work with migraine. Based on data obtained from the Ontario, the average overall annual cost due to migraine was estimated to be 3,025 dollars/patient; most of this (87%) due to indirect costs. CONCLUSION: In Canada, patients with moderate to severe migraine, as identified in a phase III clinical trial, reported lost work days and reduced effectiveness while at work, as well as increased health care resource utilization due to migraine. The associated cost was estimated to be substantial.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| 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".