Prospective, Double-Blind, Randomized, Placebo-Controlled Comparison of Acetazolamide Versus Ibuprofen for Prophylaxis Against High Altitude Headache: The Headache Evaluation at Altitude Trial (HEAT)
Bibliographic record
Abstract
OBJECTIVE: High altitude headache (HAH) is the most common neurological complaint at altitude and the defining component of acute mountain sickness (AMS). However, there is a paucity of literature concerning its prevention. Toward this end, we initiated a prospective, double-blind, randomized, placebo-controlled trial in the Nepal Himalaya designed to compare the effectiveness of ibuprofen and acetazolamide for the prevention of HAH. METHODS: Three hundred forty-three healthy western trekkers were recruited at altitudes of 4280 m and 4358 m and assigned to receive ibuprofen 600 mg, acetazolamide 85 mg, or placebo 3 times daily before continued ascent to 4928 m. Outcome measures included headache incidence and severity, AMS incidence and severity on the Lake Louise AMS Questionnaire (LLQ), and visual analog scale (VAS). RESULTS: Two hundred sixty-five of 343 subjects completed the trial. HAH incidence was similar when treated with acetazolamide (27.1%) or ibuprofen (27.5%; P = .95), and both agents were significantly more effective than placebo (45.3%; P = .01). AMS incidence was similar when treated with acetazolamide (18.8%) or ibuprofen (13.7%; P = .34), and both agents were significantly more effective than placebo (28.6%; P = .03). In fully compliant participants, moderate or severe headache incidence was similar when treated with acetazolamide (3.8%) or ibuprofen (4.7%; P = .79), and both agents were significantly more effective than placebo (13.5%; P = .03). CONCLUSIONS: Ibuprofen and acetazolamide were similarly effective in preventing HAH. Ibuprofen was similar to acetazolamide in preventing symptoms of AMS, an interesting finding that implies a potentially new approach to prevention of cerebral forms of acute altitude illness.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".