Do statins lower testosterone and does it matter?
Bibliographic record
Abstract
Drugs are two-sided swords and statins are no exception. Schooling et al. demonstrate that, on average, statins produce small, but statistically significant, decreases in testosterone. They appropriately emphasize that the clinical significance of their observations is unclear but suggest that changes in testosterone might be related to the benefits of therapy as well as the risks, such as the increased chance of diabetes mellitus. Their findings and hypotheses are noteworthy. However, we believe this represents another example of the limitations in the published summaries of drug effects. How do we know all changes induced by drugs are normally distributed? Some may be affected much more than others. Moreover, the confidence intervals of a meta-analysis describe the variance of the mean effect, not the range of effects, and while the mean change characterizes the impact of a drug on a group of patients, the range more fully characterizes its effects on individuals. We treat individuals not groups. Averages do not disclose enough about the risks and benefits of drugs. See related research article here http://www.biomedcentral.com/1741-7015/11/57.
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 | 0.004 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.026 | 0.019 |
| Insufficient payload (model declined to judge) | 0.006 | 0.006 |
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".