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Record W4388645633 · doi:10.1111/petr.14635

Reducing donor acceptance practice variation – Learnings from a discussion forum

2023· review· en· W4388645633 on OpenAlexaff
Neha Bansal, Aamir Jeewa, Kae Watanabe, Marc E. Richmond, Anaam Alzubi, Nikita D'Souza, Maria Bano, Angela Lorts, David N. Rosenthal, Katie Taylor, Catherine O’Shea, Lauren Smyth, Devin Koehl, Hong Zhao, Seth A. Hollander

Bibliographic record

VenuePediatric Transplantation · 2023
Typereview
Languageen
FieldMedicine
TopicTransplantation: Methods and Outcomes
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsMedicineSession (web analytics)Variation (astronomy)Family medicineDecision aidsMedical educationAlternative medicine

Abstract

fetched live from OpenAlex

PURPOSE: Although waitlist mortality is unacceptably high, nearly half of donor heart offers are rejected by pediatric heart transplant centers. The Advanced Cardiac Therapy Improving Outcome Network (ACTION) and Pediatric Heart Transplant Society (PHTS) convened a multi-institutional donor decision discussion forum (DDDF) aimed at assessing donor acceptance practices and reducing practice variation. METHODS: A 1-h-long virtual DDDF for providers across North America, the United Kingdom, and Brazil was held monthly. Each session typically included two case presentations posing a real-world donor decision challenge. Attendees were polled before the presenting center's decision was revealed. Group discussion followed, including a review of relevant literature and PHTS data. Metrics of participation, participant agreement with presenting center decisions, and impact on future decision-making were collected and analyzed. RESULTS: Over 2 years, 41 cases were discussed. Approximately 50 clinicians attended each call. Risk factors influencing decision-making included donor quality (10), size discrepancy (8), and COVID-19 (8). Donor characteristics influenced 63% of decisions, recipient factors 35%. Participants agreed with the decision made by the presenting center only 49% of the time. Post-presentation discussion resulted in 25% of participants changing their original decision. Survey conducted reported that 50% respondents changed their donor acceptance practices. CONCLUSION: DDDF identified significant variation in pediatric donor decision-making among centers. DDDF may be an effective format to reduce practice variation, provide education to decision-makers, and ultimately increase donor utilization.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.938
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.001
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 head0.057
GPT teacher head0.390
Teacher spread0.334 · 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.

Study designOther design
Domainnot available
GenreReview

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

Citations1
Published2023
Admission routes1
Has abstractyes

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