Impact of primary diagnosis on survival after heart transplant in female recipients of childbearing age: an analysis of the International Society for Heart and Lung Transplantation (ISHLT) Registry
Bibliographic record
Abstract
Abstract Background Women undergoing heart transplantation (HT) for peripartum cardiomyopathy (PPCM) have been reported to have inferior post-transplant survival. Specific data on the impact of pre-transplant diagnosis on survival in female HT recipients of childbearing age are lacking, but important for pre-conception counseling of women considering a pregnancy. Methods Retrospective data analysis was conducted using the ISHLT Registry. The primary aim was to study the impact of pre-transplant diagnosis and alloimmunisation on post-transplant survival in women aged 15–45 yrs at time of HT. Secondary outcomes included the impact of primary diagnosis on conditional survival at 5, 10 and 15-yrs post HT. Results Of 121,501 HT recipients (Jan 1992–June 2018), 30,179 (24.8%) were women. 9,229 (7.6%) were 15–45 yrs at time of HT. Peripartum cardiomyopathy (PPCM) and congenital heart diseases (CHD) was the primary diagnosis in 8.9% and 9.3%, respectively. Overall median post-transplant survival was 15.2 yrs. Female with PPCM were associated with higher alloimmunisation (Figure 1). PPCM was associated with lower survival (median survival in PPCM vs CHD vs other: 9.1 years vs 15.2 years vs 15.5 years respectively, p<0.05). This was not entirely explained by higher alloimmunisation in this group (Figure 2A). Five-year conditional survival of recipients of childbearing age was significantly affected by primary diagnosis of PPCM, and by pediatric status at HT, defined as age <18-yrs (PPCM vs other diagnosis p<0.05; pediatric vs non-pediatric p 0.003), whilst 10- and 15-year conditional survival was not. The difference in 5-year conditional outcome between PPCM and other diagnosis, was not significant however when female recipients were grouped according to their level of alloimmunisation (Figure 2B). Conclusion PPCM as the primary indication for HT is associated with a worse post HT survival. Our data suggest that this is not entirely explained by alloimmunisation. The impact of previous PPCM appears to be greatest in the first 5 yrs post HT. Further research is needed to fully elucidate the mechanisms associated with worse survival in this group and help inform pre-conception counseling in those HT recipients considering a subsequent pregnancy. Funding Acknowledgement Type of funding sources: None.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".