Continuity of trajectories of autism symptom severity from infancy to childhood
Bibliographic record
Abstract
BACKGROUND: Behavioral symptom trajectories are informative of the development of young children at increased likelihood for autism spectrum disorder (ASD). METHODS: Developmental trajectories of early signs were examined in a cohort of siblings of children diagnosed with ASD (n = 502) from 6 to 18 months using the Autism Observation Scale for Infants (AOSI), and from 18 months to 5-7 years using the Autism Diagnostic Observation Schedule (ADOS). Diagnostic outcomes for ASD at age 3 confirmed diagnosis for 137 children. We further analyzed the conditional probability of a switch from a trajectory measured with the AOSI to a trajectory measured with the ADOS as well as predictors from age 6 months. RESULTS: We derived three early trajectories of behavioral signs ("Low," "Intermediate," and "Increasing") from 6 to 18 months using the AOSI. We then derived three similar, distinct trajectories for the evolution of symptom severity between 18 and 60-84 months of age (Low, Intermediate, Increasing) using the ADOS. Globally, the Low trajectory included children showing fewer ASD signs or symptoms and the Increasing trajectory included children showing more severe symptoms. We also found that most children in the Low AOSI trajectory stayed in the corresponding ADOS trajectory, whereas children in an Increasing AOSI trajectory tended to transition to an Intermediate or Increasing ADOS trajectory. Developmental measures taken at 6 months (early signs of ASD, Fine Motor, and Visual Reception skills) were predictive of trajectory membership. CONCLUSIONS: Results confirm substantial heterogeneity in the early emergence of ASD signs in children at increased likelihood for ASD. Moreover, we showed that the way those early behavioral signs emerge in infants is predictive of later symptomatology. Results yield clear clinical implications, supporting the need to repeatedly assess infants at increased likelihood for ASD as this can be highly indicative of their later development and behavior.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".