Adolescent combined hormonal contraceptives and surgical repair of anterior cruciate tears: a risky recommendation based on an unproven causal relationship
Bibliographic record
Abstract
A recent cross-sectional national USA registry of surgery to repair anterior cruciate ligament tears found that fewer adolescent women who reported using combined hormonal contraceptives (CHC) had the surgery. They reviewed a complex literature on ovarian steroidal relationships with connective tissues biology, physiology and clinical issues. They concluded, based on their data and that evidence shows the greatest gender imbalance for women's ACL injury during adolescence, that all adolescent athletic women should be treated with CHC to prevent ACL injury. We caution that this admonition is using association to imply causation, implies we understand the ovarian hormonal relationships with connective tissues while that remains unclear, the directive to use CHC in adolescent ignores the recent meta-analytic evidence that its use is associated with failure to achieve peak bone mass and that these authors have used erroneous inferential reasoning and ignored the other variables besides sex and age related to ACL injury and the convincing evidence that training strategies can prevent tears.
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 | 0.003 | 0.034 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.018 | 0.016 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".