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Waiting Before Birth: Outcomes After Fetal Listing for Heart Transplantation

2008· article· en· W1559319426 on OpenAlexafffund
Stacey M. Pollock‐BarZiv, Brian W. McCrindle, Lori J. West, Anne I. Dipchand

Bibliographic record

VenueAmerican Journal of Transplantation · 2008
Typearticle
Languageen
FieldMedicine
TopicTransplantation: Methods and Outcomes
Canadian institutionsUniversity of AlbertaHospital for Sick ChildrenUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsMedicineListing (finance)Heart transplantationTransplantationFetusObstetricsIntensive care medicinePregnancyInternal medicineFinance

Abstract

fetched live from OpenAlex

Following fetal diagnosis of a profound heart defect, transplantation (HTx) is an alternative to pregnancy termination or neonatal surgical palliation. Retrospective review of the cardiac and transplant databases of fetal listings for HTx between 1990 and July 2006 was undertaken to describe outcomes after listing. We identified 26 fetal listings (of 269 total listings). Diagnoses included congenital heart disease (n = 24) and cardiomyopathy (n = 2). Seven patients were delisted after birth: in five cases parents opted for surgical palliation, two clinically improved. One patient died wait-listed (stillborn). Time wait-listed as a fetus ranged from 1-41 days (median 19 days). Eighteen patients underwent HTx (median weight 2.8 kg, range 2.1-10.9 kg); median days wait-listed after birth was 22 (4 h-123 days). Two fetuses were surgically delivered at 36 weeks gestation when a donor organ became available; 11 were transplanted as neonates (<30 days). The median age at HTx was 1 month (4 h-2.6 months). Fetal listing for HTx increases the potential window of opportunity for a donor organ to become available; patients had low wait-list mortality and a fair intermediate-term outcome. Well-defined criteria for eligibility for fetal listing and priority allocation to infants over fetuses seem rational approaches for centers that offer fetal listing.

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 score0.038
Threshold uncertainty score0.774

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.023
GPT teacher head0.316
Teacher spread0.293 · 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

Citations16
Published2008
Admission routes2
Has abstractyes

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