Extracorporeal Membrane Oxygenation as a Bridge to Pediatric Heart Transplantation
Bibliographic record
Abstract
BACKGROUND: Current organ allocation algorithms direct hearts to the sickest recipients to mitigate death while waiting. This may result in lower post-transplant (Tx) survival for high-risk candidates mandating close examination to determine the appropriateness of different technologies as a bridge to Tx. METHODS AND RESULTS: We analyzed all patients (<18 years old) from the Pediatric Heart Transplant Study (PHTS) database listed for heart Tx (1993-2013) to determine the effect of extracorporeal membrane oxygenation (ECMO) support at the time of listing and the time of Tx on waitlist mortality and post-Tx outcomes. Eight percent of patients were listed on ECMO, and within 12 months, 49% had undergone Tx, 35% were deceased, and 16% were alive waiting. Survival at 12 months after listing (censored at Tx) was worse in patients on ECMO at listing (50%) compared with ventricular assist device at listing (76%) or not on ECMO or ventricular assist device at listing (76%; P<0.0001). Two hundred three (5%) patients underwent Tx from ECMO; 135 (67%) had been on ECMO since listing, and 67 (33%) had deteriorated to ECMO support while waiting. Survival after Tx was worse in patients who underwent Tx from ECMO (3 years: 64%) versus on ventricular assist device at Tx (3 years: 84%) or not on ECMO/ventricular assist device at Tx (3 years: 85%; P<0.0001). Patients transplanted from ECMO at age <1 year had the worst survival. CONCLUSIONS: Pediatric patients requiring ECMO support before heart Tx have poor outcomes. Prioritization of donor hearts to children waitlisted on ECMO warrants careful consideration because of ECMO's high pre- and post-Tx mortality.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".