Effect of Ibuprofen on Muscle, Hematological and Renal Function, Hydric Balance, Pain, and Performance During Intense Long-Distance Running
Bibliographic record
Abstract
de Souza, RF, de Matos, DG, Ferreira, ARP, Chilibeck, P, Barros, NdA, de Oliveira, AS, Cercato, LM, da Silva, DS, and Aidar, FJ. Effect of ibuprofen on muscle, hematological and renal function, hydric balance, pain, and performance during intense long-distance running. J Strength Cond Res 34(7): 2076-2083, 2020-The aim of this study was to investigate the effect of prophylactic use of nonsteroidal anti-inflammatory drugs (i.e., ibuprofen) on physical performance, vertical jump, muscle biomarkers, liver, kidney, acute pain, and hydration status of participants in the 42-km Trail Running Challenge, a long-distance race integrated over mountain routes. The sample consisted of 20 men randomly divided into 2 groups: a control group (CG) and an experimental group (EG), with 12 completing the race (41.1 ± 8.8 years; 75.7 ± 12.1 kg) and included in the final analysis. The EG were administered an ibuprofen capsule (400 mg) 15 minutes before the beginning of the race and again after 5 hours of racing if the route was not yet completed. There were significant time main effects for creatine kinase (p = 0.001; f Cohen = 0.25), lactate dehydrogenase (p < 0.001; f Cohen = 2.05), aspartate aminotransferase (p = 0.002; f Cohen = 1.53), creatinine (p = 0.002; f Cohen = 2.24), urea (p = 0.001; f Cohen = 2.25), heart rate (p < 0.001; f Cohen = 4.88), and pain scores (p < 0.001; f Cohen = 1.93) all of which increased during the race. There was a group × time interaction for squat jump, which significantly decreased only in the CG (p = 0.045; f Cohen = 2.17). This may have been related to increased frequency of pain reported after the race in the gastrocnemius of the CG compared with the EG (p ≤ 0.05). It was concluded that ibuprofen intake did not reduce muscle damage during the competition but maintained leg muscular power performance (i.e., vertical jump), possibly by reducing gastrocnemius muscle pain.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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".