Cardiac Magnetic Resonance Imaging in Individuals With Prenatal Alcohol Exposure
Bibliographic record
Abstract
Background: Prenatal alcohol exposure (PAE) has teratogenic effects on numerous body systems including the heart. However, research magnetic resonance imaging (MRI) studies in humans with PAE have thus far been limited to the brain. This study aims to use MRI to examine heart structure and function, brain volumes, and body composition in children and adolescents with PAE. Methods: Heart, brain, and abdominal 3T MRI of 17 children, adolescents, and young adults with PAE and 53 unexposed controls was acquired to measure: (1) left ventricular ejection fraction, end-diastolic volume, end-systolic volume, stroke volume, cardiac output, longitudinal strain, circumferential strain, and heart mass; (2) total brain, cerebellum, white matter, grey matter, caudate, thalamus, putamen, and globus pallidus volumes; and (3) subcutaneous fat, visceral fat, muscle fat, and muscle (body composition). Results: Cardiac MRI revealed no abnormalities in the PAE group on evaluation by a paediatric cardiologist and by statistical comparison with a control group. Cardiac parameters in both groups were in line with previous reports, including expected sex- and age-related differences. Cerebellum, caudate, and globus pallidus volumes were all smaller. Body mass index and subcutaneous fat percent were higher in females with PAE relative to control females, but lower in males with PAE relative to control males. Conclusions: Children with PAE did not have abnormalities in MRI-derived measures of cardiac structure or function despite smaller brain volumes and sex-specific differences in body composition relative to healthy controls.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".