Bibliographic record
Abstract
Lower coronary event rates in women receiving hormone replacement therapy (HRT) have led to a presumption of benefit. The Heart and Estrogen/Progestin Replacement Study, a large randomized trial, observed a 1.4% first year excess of coronary events, well beyond the plausible play of chance on the expected effect. Over the duration of the study, event totals were similar, but patients treated with HRT experienced them earlier, with a net loss of patient-months of event-free survival. The point at which the lower event rate in hormone-treated patients would fully repay the first year loss, with constant rates, is almost double the trial duration (of 4.1 years). Since patients in the trial were preselected for satisfactory adherence to therapy, the net benefit in practice is likely to be even less. Had the patients in the Heart and Estrogen/Progestin Replacement Study been recruited to an observational study at various intervals over the first 5 years after starting HRT, the apparent risk reduction over 5 years would have been between 21% and 34%. A previous meta-analysis of trials of HRT for other indications also shows net harm. Women with or at high risk of coronary heart disease should not start HRT. There is a risk that women without coronary heart disease might experience even greater net harm from HRT. The late benefit is necessarily limited, as it cannot exceed the event rate. The mechanism of the early loss is unknown; if it were reduced proportionately less than the late benefit, considerable net harm could result. Arch Intern Med. 2000;160:2897-2900
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 | 0.081 | 0.074 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.006 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.005 | 0.011 |
| Insufficient payload (model declined to judge) | 0.006 | 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".