ASPIRE trial: study protocol for a double-blind randomised controlled trial of aspirin for overheating during exercise in multiple sclerosis
Bibliographic record
Abstract
INTRODUCTION: The many benefits of exercise for persons with multiple sclerosis (MS) are well established, yet patients often refrain from exercise due to overheating and exhaustion. The present randomised controlled trial tests aspirin (acetylsalicylic acid (ASA)) as a convenient method to prevent overheating and improve exercise performance in persons with MS. The effects of ASA are compared with those of acetaminophen (APAP) and placebo. METHODS AND ANALYSIS: Participants are seen for a laboratory maximal exercise test on 3 separate days separated by at least 1 week. At each session, body temperature is measured before oral administration of a standard adult dose (650 mg) of ASA, APAP or placebo. One hour after drug administration, participants perform a maximal ramp test on a cycle ergometer. Primary outcomes are (a) time to exhaustion (that is, time spent cycling to peak exertion) and (b) body temperature change. Crossover analyses will include tests for effects of treatment, period, treatment-period interaction (carryover effect) and sequence. ETHICS AND DISSEMINATION: Ethical approval was granted by the institutional review board at Columbia University Irving Medical Center (reference: AAAS2529). Results of the trial will be published in peer-reviewed scientific journals and presented at national and international conferences. Neurologists, physiatrists, primary care physicians and physiotherapists are important stakeholders and will be targeted during dissemination. Positive trial results have the potential to promote aspirin therapy, an inexpensive and readily available treatment, to reduce overheating and allow more persons with MS to benefit from exercise. TRIAL REGISTRATION NUMBER: NCT03824938.
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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 | 0.036 | 0.033 |
| Meta-epidemiology (narrow) | 0.008 | 0.003 |
| Meta-epidemiology (broad) | 0.015 | 0.005 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.007 | 0.010 |
| Insufficient payload (model declined to judge) | 0.128 | 0.028 |
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".