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Record W2128107763 · doi:10.1111/petr.12130

Outcomes of fetal listed patients awaiting heart transplantation

2013· article· en· W2128107763 on OpenAlexaff
Jennifer Conway, Maryanne Chrisant, Lori J. West, Rebecca Ameduri, Juan Alejos, Jacqueline M. Lamour, Bibhuti B. Das, Deborah Gilbert, Margaret Tresler, David C. Naftel, Shelley D. Miyamoto

Bibliographic record

VenuePediatric Transplantation · 2013
Typearticle
Languageen
FieldMedicine
TopicTransplantation: Methods and Outcomes
Canadian institutionsUniversity of AlbertaHospital for Sick Children
Fundersnot available
KeywordsMedicineTransplantationHeart transplantationFetusIntensive care medicineInternal medicinePregnancy

Abstract

fetched live from OpenAlex

HTx in neonates is mainstay therapy for those with severe cardiomyopathies and congenital heart disease. Fetal listing for HTx has been proposed as a way to increase the potential window for a donor with outcomes predicted to be similar to the neonatal population. Data from the PHTS, a prospective multicenter study, were used to examine the outcomes of fetuses listed between 1993 and 2009. Four thousand three hundred and sixty-five children were listed for HTx during this period. Fetuses comprised 1% and neonates 19.8% of listed patients. In those patients listed as fetus and transplanted, the median wait time from listing to HTx was 55 days (range 4-255), with a median of 25 days (range 0-233) after birth. By six months post-listing, a higher proportion of fetal listed patients had undergone HTx with a lower waitlist mortality when compared with neonate. There was no significant difference in survival following HTx between the two group (p = 0.4). While the results of this study may be less applicable to current practice due to changes in referrals for fetal listing, they do indicate that fetal listing can be a reasonable option. These results are of particular interest at the present time given the ongoing public discourse on the proposed elimination of fetal listing within UNOS.

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 score0.010
Threshold uncertainty score0.910

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 head0.281
Teacher spread0.266 · 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

Citations5
Published2013
Admission routes1
Has abstractyes

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