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This study evaluated the phenomenon of autistic regression using population-based data. The sample comprised 285 children who met the autism spectrum disorder (ASD) case definition within an ongoing surveillance program. Results indicated that children with a previously documented ASD diagnosis had higher rates of autistic regression than children who met the ASD surveillance definition but did not have a clearly documented ASD diagnosis in their records (17-26 percent of surveillance cases). Most children regressed around 24 months of age and boys were more likely to have documented regression than girls. Half of the children with regression had developmental concerns noted prior to the loss of skills. Moreover, children with autistic regression were more likely to show certain associated features, including cognitive impairment.These data indicate that some children with ASD experience a loss of skills in the first few years of life and may have a unique symptom profile. (Contains 2 tables.)

The Study to Explore Early Development (SEED) is a multi-site case-control study designed to explore the relationship between autism spectrum disorder (ASD) phenotypes and etiologies. The goals of this paper are to (1) describe the SEED algorithm that uses the Autism Diagnostic Interview-Revised (ADI-R) and Autism Diagnostic Observation Schedule (ADOS) to classify children with ASD, (2) examine psychometric properties of different ASD classification methods, including the SEED method that incorporates rules for resolving ADI-R and ADOS discordance, and (3) determine whether restricted interests and repetitive behaviors were noted for children who had instrument discordance resolved using ADI-R social and communication scores. Results support the utility of SEED criteria when well-defined groups of children are an important clinical or research outcome. [ABSTRACT FROM AUTHOR]

We conducted the first study that estimates the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of a population-based autism spectrum disorders (ASD) surveillance system developed at the Centers for Disease Control and Prevention. The system employs a records-review methodology that yields ASD classification (case versus non-ASD case) and was compared with classification based on clinical examination. The study enrolled 177 children. Estimated specificity (0.96, [CI = 0.94, 0.99]), PPV (0.79 [CI = 0.66, 0.93]), and NPV (0.91 [CI = 0.87, 0.96]) were high. Sensitivity was lower (0.60 [CI = 0.45, 0.75]). Given diagnostic heterogeneity, and the broad array of ASD in the population, identifying children with ASD is challenging. Records-based surveillance yields a population-based estimate of ASD that is likely conservative. [ABSTRACT FROM AUTHOR]

This study examined the prevalence and characteristics of autism spectrum disorder (ASD), cerebral palsy (CP), hearing loss (HL), intellectual disability (ID), and vision impairment (VI) over a 15-20 year time period, with specific focus on concurrent changes in ASD and ID prevalence. We used data from a population-based developmental disabilities surveillance program for 8-year-olds in metropolitan Atlanta. From 1991-2010, prevalence estimates of ID and HL were stable with slight increases in VI prevalence. CP prevalence was constant from 1993-2010. The average annual increase in ASD prevalence was 9.3% per year from 1996-2010, with a 269% increase from 4.2 per 1,000 in 1996 to 15.5 per 1,000 in 2010. From 2000-2010, the prevalence of ID without ASD was stable; during the same time, the prevalence of ASD with and without co-occurring ID increased by an average of 6.6% and 9.6% per year, respectively. ASD prevalence increases were found among both males and females, and among nearly all racial/ethnic subgroups and levels of intellectual ability. Average annual prevalence estimates from 1991-2010 underscore the significant community resources needed to provide early intervention and ongoing supports for children with ID (13.0 per 1,000), CP, (3.5 per 1,000), HL (1.4 per 1,000) and VI (1.3 in 1,000), with a growing urgency for children with ASD.

Early identification of young children with an autism spectrum disorder (ASD) can lead to earlier entry into intervention programs that support improved developmental outcomes. The purpose of the present study was to examine identification and diagnostic patterns of children with ASD who live in a large metropolitan area. One hundred fifteen 8-year-old children diagnosed with ASD were identified from a population-based surveillance system at the Centers for Disease Control and Prevention. Primary variables of interest included earliest age of evaluation and earliest age of diagnosis identified from surveillance records, type of initial ASD diagnosis, evaluation sources that documented first ASD diagnosis, characteristics of professionals assigning first ASD diagnosis, and diagnostic tools used to aid the diagnostic process. We found that children with ASD identified by the surveillance system were initially evaluated at a mean of 48 months but were not diagnosed with ASD until a mean age of 61 months. There were no differences in timing of diagnosis based on sex or racial/ethnic classification, although degree of impairment associated with ASD predicted mean age at first evaluation and mean age at first ASD diagnosis. Most children were identified at non-school sources, such as hospitals and clinics; 24% of the sample did not receive a documented ASD diagnosis until entering school. Most practitioners (70%) did not use a diagnostic instrument when assigning the first ASD diagnosis. Implications for early identification of ASD are discussed.

Context: Concern has been raised about possible increases in the prevalence of autism. However, few population-based studies have been conducted in the United States., Objectives: To determine the prevalence of autism among children in a major US metropolitan area and to describe characteristics of the study population., Design, Setting, and Population: Study of the prevalence of autism among children aged 3 to 10 years in the 5 counties of metropolitan Atlanta, Ga, in 1996. Cases were identified through screening and abstracting records at multiple medical and educational sources, with case status determined by expert review., Main Outcome Measures: Autism prevalence by demographic factors, levels of cognitive functioning, previous autism diagnoses, special education eligibility categories, and sources of identification., Results: A total of 987 children displayed behaviors consistent with Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition criteria for autistic disorder, pervasive developmental disorder-not otherwise specified, or Asperger disorder. The prevalence for autism was 3.4 per 1000 (95% confidence interval [CI], 3.2-3.6) (male-female ratio, 4:1). Overall, the prevalence was comparable for black and white children (black, 3.4 per 1000 [95% CI, 3.0-3.7] and white, 3.4 per 1000 [95% CI, 3.2-3.7]). Sixty-eight percent of children with IQ or developmental test results (N = 880) had cognitive impairment. As severity of cognitive impairment increased from mild to profound, the male-female ratio decreased from 4.4 to 1.3. Forty percent of children with autism were identified only at educational sources. Schools were the most important source for information on black children, children of younger mothers, and children of mothers with less than 12 years of education., Conclusion: The rate of autism found in this study was higher than the rates from studies conducted in the United States during the 1980s and early 1990s, but it was consistent with those of more recent studies.