Barriers and misconceptions of ex situ heart perfusion in pediatric donation
Bibliographic record
Abstract
BACKGROUND: Despite efforts, pediatric HTx candidates continue to have high waitlist mortality due to limited donor availability. However, there is a significant number of offered hearts not used due to concerns of viability. ESHP is a method for continuous perfusion of the donor heart that allows assessment and extended out-of-body time. It is imperative to understand healthcare stakeholders' perspectives on ESHP for implementation. Therefore, the aims of this qualitative study were to: (1) Explore pediatric stakeholders' perspectives toward ESHP; and (2) Identify barriers to widespread adoption of this technology. METHODS: Virtual focus groups were completed with pediatric HTx healthcare professional stakeholders. Following transcription of audio-recordings, the material was analyzed using content analysis. RESULTS: Four focus groups were completed with 17 participants, representing 12 institutions and three countries. Focus groups revealed varied understanding of both current and potential uses of ESHP. Participants did see the potential benefits of extending out-of-body time for and the ability to evaluate donor heart quality. However, concerns were expressed relating to patient selection, wait-list times, post-HTx outcomes, adverse events, and technical issues. These were felt to be important to understand in order to justify the costs of ESHP and impact on the healthcare system. CONCLUSIONS: This project represents the first qualitative formative evaluation of ESHP in pediatrics. The knowledge gained from stakeholders will form the basis for education initiatives, clinical trial design, and roll-out of new ESHP technologies designed for pediatrics.
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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 | 0.038 | 0.096 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.008 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| 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".