Prevalence of Pervasive Developmental Disorders among Children at the English Montreal School Board
Bibliographic record
Abstract
OBJECTIVES: The prevalence of pervasive developmental disorders (PDDs) has increased. There has been speculation regarding a role of thimerosal-containing vaccines (TCVs) in this trend. Our objectives were to determine prevalence rates of PDDs among school-aged children, and to evaluate the impact of discontinuation of thimerosal use in 1996 in routine childhood vaccines on PDD rates. METHOD: Children (n = 23 635) attending kindergarten to Grade 11 were surveyed in 71 schools from the English Montreal School Board. For children with PDD, information was obtained about their diagnostic subtype, age, sex, grade, and school. Prevalence rates were calculated for the entire school population and for each grade. Prevalence rates were also compared for children born before or after 1996. RESULTS: Students (n = 187; male to female ratio: 5.4:1) with PDD were identified, corresponding to a prevalence of 79.1/10 000 (95% CI 67.8 to 90.4/10 000). The prevalence was 25.4, 43.6, 9.7, and 0.4 for autistic disorder, PDD not otherwise specified, Asperger syndrome, and childhood disintegrative disorder, respectively. During the study period, there was a significant linear increase in prevalence (OR 1.17 per year; 95% CI 1.12 to 1.23). The trend in prevalence of PDDs was unrelated to the discontinuation of TCVs. CONCLUSION: Our study provides additional evidence that the PDD rate is close to 1%. We estimate that at least 11 500 Canadian children aged 2 to 5 years suffer from a PDD. The reasons for the upward trend in prevalence could not be determined with our methods. Discontinuation of thimerosal use in vaccines did not modify the risk of PDD.
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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".