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Record W2060826065 · doi:10.1002/uog.6309

Extracardiac lesions and chromosomal abnormalities associated with major fetal heart defects: comparison of intrauterine, postnatal and postmortem diagnoses

2009· article· en· W2060826065 on OpenAlexaffabout
Mingqing Song, Amanda Hu, U. Dyhamenahali, D. Chitayat, E.J.T. Winsor, Gillian A. Ryan, J. Smallhorn, Jon Barrett, Shi‐Joon Yoo, Lisa K. Hornberger

Post-publication record

NatureCorrection
ReasonError by Journal/Publisher;Error in Text;
Date3/4/2010 0:00
Flagged by OpenAlex?No. Retraction Watch records this, and OpenAlex does not flag it.

Source: Retraction Watch, joined by DOI. OpenAlex records retraction as is_retracted, a boolean over a state space with at least four values, so it cannot express an expression of concern, a correction or a reinstatement; it reports them as false, which reads as “fine”.

Bibliographic record

VenueUltrasound in Obstetrics and Gynecology · 2009
Typearticle
Languageen
FieldMedicine
TopicCongenital Heart Disease Studies
Canadian institutionsMount Sinai HospitalSickKids FoundationHospital for Sick ChildrenWomen's College HospitalUniversity of Toronto
Fundersnot available
KeywordsMedicineAutopsyHypoplastic left heart syndromeTetralogy of FallotFetusPrenatal diagnosisIncidence (geometry)Pulmonary atresiaHeart diseaseGenitourinary systemPathologyPregnancyInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVES: The clinical outcome of prenatally diagnosed congenital heart defects (CHD) continues to be affected significantly by associated extracardiac and chromosomal abnormalities. We sought to: determine the frequency and type of major extracardiac abnormalities (with impact on quality of life) and chromosomal abnormalities associated with fetal CHD; and compare the extracardiac abnormalities detected prenatally to the postnatal and autopsy findings in affected fetuses, to find the incidence of extracardiac abnormalities missed on prenatal ultrasound. METHODS: We reviewed the computerized database of the Division of Cardiology of the Hospital for Sick Children in Toronto to identify all cases of major CHD detected prenatally from 1990 to 2002. Medical records, fetal echocardiograms and ultrasound, cytogenetic and autopsy reports were reviewed. The types of CHD detected were grouped into categories and the frequencies of major extracardiac and chromosomal abnormalities in these categories were noted. Prenatal ultrasound findings were compared with those at autopsy or postnatal examination. RESULTS: Of 491 fetuses with major structural CHD, complete data were obtained for 382. Of these, there were 141 (36.9%) with major extracardiac abnormalities at autopsy or postnatal exam, of which 46 had chromosomal abnormalities and 95 did not. In the absence of chromosomal abnormalities, the organ systems most affected were urogenital (12.2%) and gastrointestinal (11.6%). CHDs with the highest incidence of extracardiac abnormalities (>25%) included: heterotaxy, single left ventricle and tricuspid atresia, hypoplastic left heart syndrome and tetralogy of Fallot. Ninety-four of 334 (28.1%) fetuses tested had chromosomal abnormalities. The most common chromosomal abnormalities were trisomies 21 (43.6%), 18 (19.1%) and 13 (9.6%), monosomy X (7.4%) and 22q11.2 deletion (7.4%). Of 289 extracardiac abnormalities from the complete series, 134 (46.4%) were not identified prenatally. Of the missed extracardiac abnormalities, 65 were considered not detectable at prenatal ultrasound, so 23.9% (69/289) of detectable extracardiac abnormalities were missed prenatally. CONCLUSIONS: Major extracardiac and chromosomal abnormalities are common in fetuses with major fetal CHD. Many important associated extracardiac abnormalities may be missed prenatally, which should be taken into consideration in the prenatal counseling for fetal CHD.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.013
GPT teacher head0.273
Teacher spread0.260 · 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 source (direct Gemma or distilled Codex), 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

Citations127
Published2009
Admission routes2
Has abstractyes

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