Effects of low-dose ibuprofen supplementation and resistance training on bone and muscle in postmenopausal women: A randomized controlled trial
Bibliographic record
Abstract
PURPOSE: To compare the effects of nine months of exercise training and ibuprofen supplementation (given immeditately after exercise sessions) on bone and muscle in postmenopausal women. METHODS: In a double-blind randomized trial, participants (females: n = 90, mean age 64.8, SD 4.3 years) were assigned (computer generated, double blind) to receive supervised resistance training or stretching 3 days/week, and ibuprofen (400 mg, post-exercise) or placebo (i.e. 4 groups) for 9 months. In this proof-of-concept study the sample size was halved from required 200 identified via 90% power calculation. Baseline and post-intervention testing included: Dual energy x-ray absorptiometry (DXA) for lumbar spine, femoral neck, and total body areal bone mineral density (aBMD); geometry of proximal femur; total body lean tissue and fat mass; predicted 1-repetition maximum muscle strength testing (1RM; biceps curl, hack squat). RESULTS: Exercise training or ibuprofen supplementation had no effects on aBMD of the lumbar spine, femoral neck, and total body. There was a significant exercise × supplement × time interaction for aBMD of Ward's region of the femoral neck (p = 0.015) with post hoc comparison showing a 6% decrease for stretching with placebo vs. a 3% increase for stretching with ibuprofen (p = 0.017). Resistance training increased biceps curl and hack squat strength vs. stretching (22% vs. 4% and 114% vs. 12%, respectively) (p < 0.01) and decreased percent body fat compared to stretching (2% vs. 0%) (p < 0.05). CONCLUSIONS: Ibuprofen supplementation provided some benefits to bone when taken independent of exercise training in postmenopausal women. This study provides evidence towards a novel, easily accessible stimulus for enhancing bone health [i.e. ibuprofen].
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".