Survival after heart transplantation for Chagas cardiomyopathy using a conventional protocol: A 10‐year experience in a single center
Bibliographic record
Abstract
BACKGROUND: Heart transplant (HT) remains the most frequently indicated therapy for patients with end-stage heart failure that improves prognosis in Chagas cardiomyopathy (CCM). However, the lack of benznidazole therapy and availability of RT-PCR follow-up in many centers is a major limitation to perform this life-saving intervention, as there are concerns related with the risk of reactivation. We aimed to describe the outcomes of a cohort of patients with CCM who underwent HT using a conventional protocol with mycophenolate mofetil, without benznidazole prophylaxis or RT-PCR follow-up. METHODS: Retrospective cohort study. Between 2008 and 2018, 43 patients with CCM underwent HT. A descriptive analysis to characterize outcomes as rejection, infectious and neoplastic complications and a survival analysis was carried out. RESULTS: Median of follow-up was 4.3 (IR 4.28) years. Survival at 1 month, 1 year, and 5 years was 95%, 85%, and 75%, respectively, infections being the main cause of death (60%). Reactivations occurred in only three patients (7.34%) and were not related to mortality. CONCLUSION: This cohort showed a favorable survival and a low reactivation rate without an impact on mortality. Our results suggest that performing HT in patients with CCM following conventional guidelines and recommendations for other etiologies is a safe approach.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".