Pediatrics
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Autistic spectrum disorders (ASD) have variable developmental outcomes, for reasons that are not entirely clear. The objective of this study was to test the clinical observation that initial developmental parameters (degree of atypicality and level of intelligence) are a major predictor of outcome in children with ASD and to develop a statistical method for modeling outcome on the basis of these parameters. ⋯ These data provide preliminary validation of a statistical model for clinical outcome of ASD on the basis of 3 parameters: age, degree of atypicality, and level of intelligence. This model, if replicated in a prospective, population-based sample that is controlled for treatment modalities, will enhance our ability to offer a prognosis for the child with ASD and will provide a benchmark against which to judge the putative benefits of various treatments for ASD. Our model may also be useful in etiologic and epidemiologic studies of ASD, because different causes of ASD are likely to follow different developmental trajectories along these 3 parameters.
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Many autism advocacy groups use the data collected by the US Department of Education (USDE) to show a rapidly increasing prevalence of autism. Closer examination of these data to follow each birth-year cohort reveals anomalies within the USDE data on autism. ⋯ In addition, an unexpected reduction in the rise of autism prevalence occurs in most cohorts at 12 years of age, the age when most children would be entering middle school. These anomalies point to internal problems in the USDE data that make them unsuitable for tracking autism prevalence.