Differences in mortality by donor sex and age in heart transplantation: An individual patient data meta-analysis
Bibliographic record
Abstract
Background: Prior studies suggested a recipient sex-dependent association between donor sex and heart transplant survival. We hypothesized that donor age also modifies the association between donor sex and recipient mortality. Methods: = 109,432) recorded in the Scientific Registry of Transplant Recipients (SRTR) and the Collaborative Transplant Study (CTS) were analyzed. We used multivariable Cox regression models to estimate the association between donor sex and mortality, accounting for the modifying effects of recipient sex and donor age. Results from cohort-specific models were combined using individual patient data meta-analysis. Results: Among female recipients, mortality was lower with female than male donors across all donor age groups, though differences were not statistically significant. Among male recipients, female donors aged 13-44 years were associated with higher mortality compared with male donors, although the difference was not statistically significant. In sensitivity analyses, aHR comparing mortality associated with female vs male donors were lower after adjusting for donor-recipient heart size mismatch. Female recipients of female donors aged 18-44 years had significantly lower mortality than recipients of same-aged male donors. Among male recipients of donors aged ≥45 years, mortality was significantly lower with a female than a male donor. Conclusion: Donor age modifies the association between donor sex and survival after heart transplantation. When appropriately size-matched, female donors are associated with similar or lower mortality compared with male donors in both female and male recipients, suggesting a potential survival advantage with female donor hearts.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| 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".