Digoxin increased risk of death in women, but not men, with heart failure
Bibliographic record
Abstract
Rathore SS, Wang Y, Krumholz HM. Sex-based differences in the effect of digoxin for the treatment of heart failure. N Engl J Med2002 ; 347 : 1403 –11 [OpenUrl][1][CrossRef][2][PubMed][3][Web of Science][4] QUESTION: Does the effect of digoxin therapy differ in men and women with heart failure (HF) and depressed left ventricular systolic function? Randomised {allocation concealed}*, blinded ({participants, healthcare providers,}† and data collectors), placebo controlled trial with up to 48 months of follow up. 302 clinical centres in the US and Canada. 5281 men (median age 64 y, 87% white, 30% New York Heart Association [NYHA] class ≥III) and 1519 women (median age 66 y, 81% white, 40.6% NYHA class ≥III) who had clinically confirmed HF (ie, current or past clinical symptoms or signs or radiographic evidence of pulmonary congestion) and an ejection fraction … [1]: {openurl}?query=rft.jtitle%253DNew%2BEngland%2BJournal%2Bof%2BMedicine%26rft.stitle%253DNEJM%26rft.aulast%253DRathore%26rft.auinit1%253DS.%2BS.%26rft.volume%253D347%26rft.issue%253D18%26rft.spage%253D1403%26rft.epage%253D1411%26rft.atitle%253DSex-Based%2BDifferences%2Bin%2Bthe%2BEffect%2Bof%2BDigoxin%2Bfor%2Bthe%2BTreatment%2Bof%2BHeart%2BFailure%26rft_id%253Dinfo%253Adoi%252F10.1056%252FNEJMoa021266%26rft_id%253Dinfo%253Apmid%252F12409542%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [2]: /lookup/external-ref?access_num=10.1056/NEJMoa021266&link_type=DOI [3]: /lookup/external-ref?access_num=12409542&link_type=MED&atom=%2Febnurs%2F6%2F3%2F80.atom [4]: /lookup/external-ref?access_num=000178888400003&link_type=ISI
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".