Rate of first recorded diagnosis of autism and other pervasive developmental disorders in United Kingdom general practice, 1988 to 2001
Bibliographic record
Abstract
BACKGROUND: There has been concern that the incidence of autism and other pervasive developmental disorders (PDDs) is increasing. Previous studies have been smaller, restricted to autism (excluding other pervasive developmental disorders such as Asperger's syndrome), included boys only, or have not been based on a national sample. We investigated time trends in the rates of diagnosis of pervasive developmental disorders. METHODS: We analysed the rates of first diagnosis of pervasive developmental disorders among people registered with a practice contributing to the United Kingdom General Practice Research Database during the period 1988 to 2001. We included 1410 cases from over 14 million person-years of observation. The main outcome measures were rates of diagnosis of pervasive developmental disorders by year of diagnosis, year of birth, gender and geographical region. RESULTS: The rate increased progressively from 0.40/10,000 person-years (95% CI 0.30 to 0.54) in 1991 to 2.98/10,000 (95% CI 2.56 to 3.47) in 2001. A similar change occurred in the age standardised incidence ratios, from 35 (95% CI: 26-47) in 1991 to 365 (95% CI: 314-425) in 2001. The temporal increase was not limited to children born during specific years nor to children diagnosed in a specific time period. The rate of diagnosis of PDDs other than autism rose from zero for the period 1988-1992 to 1.06/10,000 person-years in 2001. The rate of diagnosis of autism also increased but to a lesser extent. There was marked geographical variation in rates, with standardised incidence ratios varying from 66 for Wales to 141 for the South East of England. CONCLUSIONS: Better ascertainment of diagnosis is likely to have contributed to the observed temporal increase in rates of diagnosis of PDD, but we cannot exclude a real increase.
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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 | 0.001 | 0.005 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".