The Association between Combined Hormonal Contraceptive Use and Musculoskeletal Tissue Pathophysiology, Injuries and Conditions: A Systematic Review and Meta-analysis
Bibliographic record
Abstract
Objective: Assess the association between Combined Hormonal Contraceptives (CHC) use and musculoskeletal tissue pathophysiology, injuries, or conditions.Design: Systematic review with semi-quantitative analyses and certainty of evidence assessment, guided by the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach.Data Sources: MEDLINE, EMBASE, CENTRAL, SPORTDiscus, CINAHL searched from inception to 04-2022.Eligibility: Intervention and cohort studies that assessed the association between new or ongoing use of CHC and an outcome of musculoskeletal tissue pathophysiology, injury, or condition in post-pubertal premenopausal females.Results: Across 50 included studies, we assessed the effect of CHC use on 30 unique musculoskeletal outcomes (75% bone-related). Serious risk of bias was judged present in 82% of studies, with 52% adequately adjusting for confounding. Meta-analyses were not possible due to poor outcome reporting and heterogeneity in estimate statistics and comparison conditions. Based on semi-quantitative synthesis, there is low certainty evidence that CHC use was associated with elevated future fracture risk (risk ratio 1.02-1.20) and total knee arthroplasty (risk ratio 1.00-1.36). There is very low certainty evidence of unclear relationships between CHC use and a wide range of bone turnover and bone health outcomes. Evidence about the effect of CHC use on musculoskeletal tissues beyond bone and the influence of CHC use in adolescence versus adulthood is limited.Conclusion: Given a paucity of high-certainty evidence that CHC use is protective against musculoskeletal pathophysiology, injury, or conditions, it is premature and inappropriate to advocate or prescribe CHC for these purposes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.017 | 0.043 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.033 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| 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".