Symptom trajectories in the first 18 months and autism risk in a prospective high‐risk cohort
Bibliographic record
Abstract
BACKGROUND: Although early autism spectrum disorder (ASD) detection strategies tend to focus on differences at a point in time, behavioral symptom trajectories may also be informative. METHODS: Developmental trajectories of early signs of ASD were examined in younger siblings of children diagnosed with ASD (n = 499) and infants with no family history of ASD (n = 177). Participants were assessed using the Autism Observation Scale for Infants (AOSI) from 6 to 18 months. Diagnostic outcomes were determined at age 3 years blind to previous assessments. RESULTS: Semiparametric group-based modeling using AOSI scores identified three distinct trajectories: Group 1 ('Low', n = 435, 64.3%) was characterized by a low level and stable evolution of ASD signs, group 2 ('Intermediate', n = 180, 26.6%) had intermediate and stable levels, and group 3 ('Inclining', n = 61, 9.3%) had higher and progressively elevated levels of ASD signs. Among younger siblings, ASD rates at age 3 varied by trajectory of early signs and were highest in the Inclining group, membership in which was highly specific (94.5%) but poorly sensitive (28.5%) to ASD. Children with ASD assigned to the inclining trajectory had more severe symptoms at age 3, but developmental and adaptive functioning did not differ by trajectory membership. CONCLUSIONS: These prospective data emphasize variable early-onset patterns and the importance of a multipronged approach to early surveillance and screening for ASD.
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 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".