Testosterone Deficiency Independently Predicts Mortality in Women with HFrEF: Insights from the T.O.S.CA. Registry
Bibliographic record
Abstract
AIMS: Testosterone deficiency (TD) is associated with increased morbidity and mortality in heart failure with reduced ejection fraction (HFrEF). However, data in women are scanty. The aim of this study was to investigate the prognostic impact of TD on women with HFrEF. METHODS: Among 480 patients prospectively enrolled in the T.O.S.CA. (Terapia Ormonale Scompenso CArdiaco) registry, a prospective, multicentre, nationwide, observational study, 94 women were included in the current analysis. The TD was defined as serum testosterone levels lower than 25 ng/dl. Data regarding clinical status, echocardiography, exercise performance, cardiovascular hospitalization, and survival after an average follow-up of 36 months were analysed. RESULTS: peak) (P = 0.03) and estimated glomerular filtration rate (P < 0.001). TD was an independent predictor of the combined endpoint of all-cause mortality/cardiovascular hospitalization (HR: 10.45; 95% CI: 3.54-17.01; P = 0.001), all-cause mortality (HR: 8.33; 95%: 5.36-15.11; P = 0.039), and cardiovascular hospitalization (HR: 2.41; 95% CI: 1.13-4.50; P = 0.02). CONCLUSIONS: One-third of women with HFrEF displays TD that impacts remarkably on their morbidity and mortality. TD is associated with a worse clinical profile including exercise capacity, right ventricular-pulmonary arterial coupling, and renal function. These findings lend support to an accurate profiling of women with HF, a problem often overlooked in clinical trials.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".