Incidence of prenatal alcohol exposure in Prince Edward Island: a population-based descriptive study
Bibliographic record
Abstract
BACKGROUND: Fetal alcohol spectrum disorder (FASD) is a leading preventable cause of neurodevelopmental disability in North America. The stigma associated with alcohol use and abuse during pregnancy makes it difficult to obtain information on prenatal alcohol use through self-reporting. We assessed the incidence of prenatal alcohol exposure in Prince Edward Island to facilitate future public health initiatives addressing FASD. METHODS: Prenatal alcohol exposure was examined via population-based collection of meconium and analysis of fatty acid ethyl esters (FAEEs). Fatty acid ethyl esters are nonoxidative metabolites of ethanol that are produced in the fetus. Meconium FAEE concentrations of 2.0 nmol/g or greater are indicative of frequent prenatal alcohol exposure during the last 2 trimesters of pregnancy. Samples were collected from 1307 neonates between Nov. 8, 2010, and Nov. 8, 2011, in hospitals in PEI, or from those born to mothers who resided in PEI but gave birth in Halifax, Nova Scotia. Samples were frozen and shipped for analysis. Fatty acid ethyl esters were analyzed by gas chromatography-mass spectrometry and quantified by means of deuterated internal standards. RESULTS: Of the 1307 samples collected, 1271 samples were successfully analyzed. Positive results for FAEEs were obtained in 3.1% (n = 39) of samples collected within the first 24 hours after birth. INTERPRETATION: Not all neonates exposed to heavy prenatal alcohol in utero will exhibit FASD; based on current estimates of predictive value for disease by exposure, our findings suggest that 1.3% of neonates born in PEI during this 1-year period will have FASD. In its application to an entire provincial birth cohort, this study successfully implemented a public health-centred approach for evaluating population-based risk of FASD, with implications for practice across Canada.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".