Clinician Perspectives on Compassionate Deactivation of Pediatric Ventricular Assist Devices
Bibliographic record
Abstract
Following ventricular assist device (VAD) placement, families and clinicians often have differing perspectives. When adverse events reduce patients' quality of life, families and clinicians question the desirability of continuing VAD support. Given the increasing use of VAD in pediatrics, pediatric-specific guidelines for the process of compassionate deactivation (CD) of VAD are needed, based in part on the perspectives of pediatric heart failure clinicians. In this qualitative study, we used a semi-structured interview guide focused on CD. Twenty-one clinicians participated. The central theme characterizing the process of CD-VAD is Making the Decision to CD-VAD . Five categories emerged: 1) communication strategies, 2) relationships and trust, 3) importance of time, 4) emotional toll, and 5) redirecting care. Consensus in decision-making was achieved through collective discussions among staff and care team meetings, including families. Clinicians reported experiencing moral and emotional distress, primarily due to witnessing patient suffering, triggered by close relationships with patients and families, and discord around CD decisions. This study clarifies challenges posed by CD-VAD. Understanding these challenges is a necessary first step in the development of guidance to provide cardiac care integrated with pediatric palliative care (PPC) for children with implanted VAD, and to respond appropriately to circumstances where CD may be warranted.
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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 | 0.023 | 0.060 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.008 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".