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Association of Prenatal Diagnosis of Critical Congenital Heart Disease With Postnatal Brain Development and the Risk of Brain Injury

2016· article· en· W2288039448 on OpenAlexafffund
Shabnam Peyvandi, Veronica de Santiago, Ela Chakkarapani, Vann Chau, Andrew Campbell, Kenneth J. Poskitt, Duan Xu, A. James Barkovich, Steven P. Miller, Patrick S. McQuillen

Bibliographic record

VenueJAMA Pediatrics · 2016
Typearticle
Languageen
FieldMedicine
TopicCongenital Heart Disease Studies
Canadian institutionsHospital for Sick ChildrenSickKids FoundationUniversity of TorontoUniversity of British ColumbiaSt. Michael's Hospital
FundersNational Center for Research ResourcesNational Institute of Neurological Disorders and StrokeCanadian Institutes of Health Research
KeywordsMedicineHeart diseaseDiseaseBrain developmentPrenatal diagnosisPregnancyPediatricsInternal medicineFetusCardiologyNeuroscienceGenetics

Abstract

fetched live from OpenAlex

IMPORTANCE: The relationship of prenatal diagnosis of critical congenital heart disease (CHD) with brain injury and brain development is unknown. Given limited improvement of CHD outcomes with prenatal diagnosis, the effect of prenatal diagnosis on brain health may reveal additional benefits. OBJECTIVE: To compare the prevalence of preoperative and postoperative brain injury and the trajectory of brain development in neonates with prenatal vs postnatal diagnosis of CHD. DESIGN, SETTING, AND PARTICIPANTS: Cohort study of term newborns with critical CHD recruited consecutively from 2001 to 2013 at the University of California, San Francisco and the University of British Columbia. Term newborns with critical CHD were studied with brain magnetic resonance imaging preoperatively and postoperatively to determine brain injury severity and microstructural brain development with diffusion tensor imaging by measuring fractional anisotropy and the apparent diffusion coefficient. Comparisons of magnetic resonance imaging findings and clinical variables were made between prenatal and postnatal diagnosis of critical CHD. A total of 153 patients with transposition of the great arteries and single ventricle physiology were included in this analysis. MAIN OUTCOMES AND MEASURES: The presence of brain injury on the preoperative brain magnetic resonance imaging and the trajectory of postnatal brain microstructural development. RESULTS: Among 153 patients (67% male), 96 had transposition of the great arteries and 57 had single ventricle physiology. The presence of brain injury was significantly higher in patients with postnatal diagnosis of critical CHD (41 of 86 [48%]) than in those with prenatal diagnosis (16 of 67 [24%]) (P = .003). Patients with prenatal diagnosis demonstrated faster brain development in white matter fractional anisotropy (rate of increase, 2.2%; 95% CI, 0.1%-4.2%; P = .04) and gray matter apparent diffusion coefficient (rate of decrease, 0.6%; 95% CI, 0.1%-1.2%; P = .02). Patients with prenatal diagnosis had lower birth weight (mean, 3184.5 g; 95% CI, 3050.3-3318.6) than those with postnatal diagnosis (mean, 3397.6 g; 95% CI, 3277.6-3517.6) (P = .02). Those with prenatal diagnosis had an earlier estimated gestational age at delivery (mean, 38.6 weeks; 95% CI, 38.2-38.9) than those with postnatal diagnosis (mean, 39.1 weeks; 95% CI, 38.8-39.5) (P = .03). CONCLUSIONS AND RELEVANCE: Newborns with prenatal diagnosis of single ventricle physiology and transposition of the great arteries demonstrate less preoperative brain injury and more robust microstructural brain development than those with postnatal diagnosis. These results are likely secondary to improved cardiovascular stability. The impact of these findings on neurodevelopmental outcomes warrants further study.

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)0.000
metaresearch head score (Gemma)0.006
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 score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.007
GPT teacher head0.256
Teacher spread0.249 · 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

Citations161
Published2016
Admission routes2
Has abstractyes

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