Survival Outcomes After Heart Transplantation
Bibliographic record
Abstract
Background: Currently, women represent <25% of heart transplant recipients. Reasons for this female underrepresentation have been attributed to selection and referral bias and potentially poorer outcomes in female recipients. The aim of this study was to compare long-term posttransplant survival between men and women, when matched for recipient and donor characteristics. Methods and Results: Using the International Society for Heart and Lung Transplantation Registry, we performed descriptive analyses and estimated overall freedom from posttransplant death stratified by sex using Kaplan-Meier survival methods. Male and female recipients were matched according to the Index for Mortality Prediction After Cardiac Transplantation and Donor Risk Index score using 1:1 propensity score matching. The study cohort comprised 34 198 heart transplant recipients (76.3% men, 23.7% women) between 2004 and 2014. Compared with men, women were more likely younger (51 [39–59] versus 55 [46–61] years; P <0.001) and had a different distribution of heart failure etiology ( P <0.001). In general, the prevalence of comorbidities was lower in women than in men. Women were less likely to have diabetes mellitus (19.1% versus 26.2%; P <0.001), hypertension (40.7% versus 47.9%; P <0.001), peripheral vascular disease (2.4% versus 3.3%; P =0.002), tobacco use (36.5% versus 52.3%; P <0.001), and prior cardiovascular surgery (38.6% versus 50.7%; P <0.001). Women were more likely to have a history of malignancy (10.5% versus 5.3%; P <0.001), require intravenous inotropes (41.4% versus 37.2%; P <0.001), and were less likely supported by an intra-aortic balloon pump (3.3% versus 3.8%; P =0.03) or durable ventricular assist device (22% versus 31.5%; P <0.001). Transplanted male recipients had a higher Index for Mortality Prediction After Cardiac Transplantation score (5 [2–7] versus 4 [1–6]; P <0.001). When male and female heart transplant recipients were matched for recipient and donor characteristics, there was no significant survival difference ( P =0.57). Conclusions: Overall survival does not differ between men and women after cardiac transplantation. Women who survive to heart transplantation appear to have lower risk features than male recipients but receive hearts from higher risk donors.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".