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Record W4413411625 · doi:10.1097/mat.0000000000002530

Clinician Perspectives on Compassionate Deactivation of Pediatric Ventricular Assist Devices

2025· article· en· W4413411625 on OpenAlexaff
Kimberly A. Pyke‐Grimm, Michelle R. Brown, A. Youssef, Seth A. Hollander, Chris Feudtner, Danton Char

Bibliographic record

VenueASAIO Journal · 2025
Typearticle
Languageen
FieldEngineering
TopicMechanical Circulatory Support Devices
Canadian institutionsArtificial Intelligence in Medicine (Canada)
Fundersnot available
KeywordsMedicineDistressPalliative careQualitative researchTollPsychologyNursingMedical emergencyClinical psychology

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.061
Threshold uncertainty score0.433

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.015
GPT teacher head0.269
Teacher spread0.254 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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