Heart transplantation as a rescue strategy for patients with refractory electrical storm
Bibliographic record
Abstract
AIMS: Heart transplantation (HT) can be proposed as a therapeutic strategy for patients with severe refractory electrical storm (ES). Data in the literature are scarce and based on case reports. We aimed at determining the characteristics and survival of patients transplanted for refractory ES. METHODS AND RESULTS: Patients registered on HT waiting list during the following days after ES and eventually transplanted, from 2010 to 2021, were retrospectively included in 11 French centres. The primary endpoint was in-hospital mortality. Forty-five patients were included [82% men; 55.0 (47.8-59.3) years old; 42.2% and 26.7% non-ischaemic dilated or ischaemic cardiomyopathies, respectively]. Among them, 42 (93.3%) received amiodarone, 29 received (64.4%) beta blockers, 19 (42.2%) required deep sedation, 22 had (48.9%) mechanical circulatory support, and 9 (20.0%) had radiofrequency catheter ablation. Twenty-two patients (62%) were in cardiogenic shock. Inscription on wait list and transplantation occurred 3.0 (1.0-5.0) days and 9.0 (4.0-14.0) days after ES onset, respectively. After transplantation, 20 patients (44.4%) needed immediate haemodynamic support by extracorporeal membrane oxygenation (ECMO). In-hospital mortality rate was 28.9%. Predictors of in-hospital mortality were serum creatinine/urea levels, need for immediate post-operative ECMO support, post-operative complications, and surgical re-interventions. One-year survival was 68.9%. CONCLUSION: Electrical storm is a rare indication of HT but may be lifesaving in those patients presenting intractable arrhythmias despite usual care. Most patients can be safely discharged from hospital, although post-operative mortality remains substantial in this context of emergency transplantation. Larger studies are warranted to precisely determine those patients at higher risk of in-hospital mortality.
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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 | 0.001 |
| 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".