Tolerability of pharmacological agents in the treatment of headache following brain injury: a scoping review
Bibliographic record
Abstract
BACKGROUND: While systematic reviews have examined medication effectiveness for post-traumatic headache (PTH), they have not assessed tolerability. OBJECTIVE: To conduct a scoping review to characterize the adverse effects of pharmacotherapy for PTH. METHODS: CINAHL, CMA Infobase, Cochrane Library, Embase, Epistemonikos, MEDLINE, PEDro, PsycInfo, Scopus, SportDiscus, TRIP and the University of York Center for Reviews and Dissemination were searched. Studies meeting these criteria were included 1) English language, 2) involved humans with traumatic brain injury (TBI), 3) a medication for PTH was administered and 4) reported tolerability outcomes. Author(s), publication year, country of origin, study design, sample demographics, medication type, comparator, dose, treatment duration, adverse effect type and rate, discontinuation rate, and effectiveness outcomes were extracted. RESULTS: The search yielded 2941 records; 11 studies were included (n = 324 subjects). All subjects had mild TBI except for one with moderate TBI. The following therapies were examined 1) abortive (dihydroergotamine N = 1; metoclopramide N = 1; indomethacin N = 3), 2) prophylactic (divalproex sodium N = 1; amantadine N = 1; erenumab N = 2; amitriptyline N = 2). No serious adverse effects occurred. Observed adverse effects overlap with common symptoms of TBI. CONCLUSION: The unique needs of people with TBI must be considered when instituting pharmacotherapy. More studies specifically evaluating medication tolerability in PTH are needed.
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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 | 0.015 | 0.061 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.012 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".