Ventricular assist device implantation in children with a mechanical valve: An ACTION registry analysis
Bibliographic record
Abstract
Background Patients with congenital heart disease (CHD) frequently have had valve interventions, including replacement with a mechanical valve (mechV). The impact of a mechV on clinical outcomes in patients undergoing ventricular assist device (VAD) implantation is not well characterized. Objectives This study assessed VAD outcomes in patients with CHD and a mechV. Methods All patients with a history of CHD ( n = 433) in the Advanced Cardiac Therapies Improving Outcomes Network database were included in the study (January 2012-January 2023). Patient characteristics and outcomes were assessed among patients with a mechV and without a mechV. Results Twenty-seven (6%) patients with CHD had a mechV at VAD implantation. Fourteen (52%) of the patients with mechV had univentricular anatomy and 13 (48%) had biventricular anatomy. Patients with mechV were older (4.9 vs 1.9 years, p = 0.02), smaller (14.9 vs 10.6 kg, p = 0.02), and had a higher interagency registry for mechanically assisted circulatory support profile ( p = 0.01). Three (11%) patients with mechV experienced a valve-related complication. There was no difference in survival ( p = 0.4) or ischemic stroke frequency (11% vs 13%, p = 1) between patients with mechV and non-mechV. Patients with mechV had higher frequency of hemorrhagic stroke (18% vs 4.7%, p = 0.01) and major bleeding (44% vs 26%, p = 0.04). Conclusions Patients with CHD with a mechV have similar survival to patients with non-mechV; however, there is higher risk of bleeding including hemorrhagic stroke.
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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 | 0.000 | 0.000 |
| 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 | 0.001 |
| 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".