The clinic of autistic disorders at an early age
Bibliographic record
Abstract
Objective. To study disorders of mental development and psychopathological symptoms in young children with autistic disorders of various origins. Material and methods. Two hundred and sixty-five children, aged 9 months to 4 years, (201 boys, 64 girls) with symptoms of autistic disorder were examined. The patients were divided into two age groups — the 1st group consisted of 36 children, aged 9 months to 2 years, the 2nd group consisted of 229 children from 2 years to 4 years. Psychopathological, neurological and clinical-dynamic methods were used, taking into account the results of consultations with a speech therapist, defectologist, psychologist. Results. The number of visits to a psychiatrist by parents of children older than two years becomes significantly higher — 13.6% (n=36) and 86.4% (n=112), respectively (p≤0.05), as well as the diagnosis of autistic disorder — 8.3% (n=3) and 16.2% (n=37) respectively, p≤0.05). In both age groups, the diagnosis of «Other general developmental disorders» (F84.8) was most often established, with a significant predominance in the younger group — 80.5% and 72%, respectively (p≤0.05). Characteristic symptoms-markers of autism for both age groups are highlighted. It is shown that the diagnoses of childhood autism, Kanner syndrome, exposed at the first treatment, were preserved in all patients after three years. By the age of four, it was possible to clarify the diagnosis in 32% of cases. At the same time, 68% of patients, aged 4 years, retained a clinically undifferentiated diagnosis of F84.8. Conclusion. The study showed an increase in the diagnosis of autistic disorder during the first years of life. The necessity of increasing the knowledge of early-age psychiatry among specialists and the organization of a system of early detection, timely treatment and rehabilitation of autistic disorders in children of the first years of life in children’s polyclinics is noted.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".