Validation of the diagnosis of autism in general practitioner records
Bibliographic record
Abstract
BACKGROUND: We report on the validity of the computerized diagnoses of autism in a large case-control study investigating the possible association between autism and the measles, mumps and rubella vaccine in the UK using the General Practitioner Research Database (GPRD). We examined anonymized copies of all relevant available clinical reports, including general practitioners' (GP) notes, consultant, speech therapy and educational psychologists reports, on 318 subjects born between 1973 and 1997 with a diagnosis of autism or a related disorder recorded in their electronic general practice record. METHODS: Data were abstracted to a case validation form allowing for the identification of developmental symptoms relevant to the diagnosis of pervasive developmental disorders (PDDs). Information on other background clinical and familial features was also abstracted. A subset of 50 notes was coded independently by 2 raters to derive reliability estimates for key clinical characteristics. RESULTS: For 294 subjects (92.5%) the diagnosis of PDD was confirmed after review of the records. Of these, 180 subjects (61.2%) fulfilled criteria for autistic disorder. The mean age at first recording of a PDD diagnosis in the GPRD database was 6.3 years (SD = 4.6). Consistent with previous estimates, the proportion of subjects experiencing regression in the course of their development was 19%. Inter-rater reliability for the presence of a PDD diagnosis was good (kappa =.73), and agreement on clinical features such as regression, age of parental recognition of first symptoms, language delay and presence of epilepsy was also good (kappas ranging from.56 to 1.0). CONCLUSIONS: This study provides evidence that the positive predictive value of a diagnosis of autism recorded in the GPRD is high.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".