Tramadol and the risk of seizure: nested case-control study of US patients with employer-sponsored health benefits
Bibliographic record
Abstract
OBJECTIVES: Tramadol is a widely prescribed analgesic that influences both opioid and monoamine neurotransmission. While seizures have been reported with its use, the risk in clinical practice has not been well characterised. We examined risk of seizure with tramadol relative to codeine, a comparable opioid analgesic. DESIGN: Retrospective nested case-control study. For each case, we identified up to 10 controls matched on age, sex, US state of residence and date of cohort entry (±365 days). We calculated ORs to determine the association between seizure and exposure to tramadol, codeine (≥15 mg), both or neither, in the preceding 30 days. SETTING: Cohort of patients, who had continuous health coverage and resided in the same state for≥3 years, identified from linked administrative health data in US MarketScan databases from 2009 to 2012. PARTICIPANTS: We identified 96 753 patients with seizure and 888 540 matched controls. PRIMARY AND SECONDARY OUTCOME MEASURES: In the primary analysis, we defined cases using a broad definition of seizure (based on either an outpatient physician claim for seizure disorder or a seizure-related emergency department visit or hospitalisation). In a secondary analysis, we used a more specific definition of seizure restricted to a hospital visit with a principal diagnosis of seizure. RESULTS: In the primary analysis, we found no association between risk of seizure and exposure to tramadol compared with codeine (OR 1.03, 95% CI 0.93 to 1.15). However, in the secondary analysis (using a more specific definition of seizure), this association was statistically significant (OR 1.41, 95% CI 1.11 to 1.79). CONCLUSIONS: Tramadol was not associated with an increased risk of seizure defined by inpatient and outpatient diagnoses. However, this finding was sensitive to the outcome definition used and requires further study.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".