Autism in Toddlers Born Very Preterm
Bibliographic record
Abstract
OBJECTIVE: This study aimed to determine the prevalence of autism spectrum disorder (ASD) by using the Autism Diagnostic Observation Schedule-Generic (ADOS-G) classifications in children born very preterm during their toddler years. METHODS: Two birth cohorts of toddlers (2 and 4 years old) each recruited over 12 months and born at <29 weeks' gestation were administered the Modified Checklist of Autism in Toddlers-Follow-up Interview (M-CHAT-FI) screen, the ADOS-G, and developmental assessments. The ADOS-G was conducted on toddlers with M-CHAT-FI-positive screens. RESULTS: Data were available on 88% (169/192) of children. In total, 22 (13%) toddlers screened positive and 3 (1.8%) were confirmed diagnostically with ASD. These 3 cases reached the highest ADOS-G threshold classification of autism. All but 1 child who scored below the ADOS-G thresholds (11/12) demonstrated some difficulty with social communication. Risk was significantly increased for co-occurring neurodevelopmental problems in 21 of the 22 positive-screen ASD cases. Adaptive behavior (P < .001) was the only co-occurring factor independently predictive of ASD in toddlers. CONCLUSIONS: Children born very preterm are at increased risk of ASD. By using the ADOS-G, we found a lower incidence of ASD in children born at <29 weeks' gestation compared with previous studies. Children who screened positive for ASD on the M-CHAT-FI had developmental delays consistent with subthreshold communication impairment.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 | 0.001 |
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".