Using the Childhood Autism Rating Scale to Diagnose Autism Spectrum Disorders

Department of Psychology, University of Connecticut, Storrs, CT 06269-1020, USA.
Journal of Autism and Developmental Disorders (Impact Factor: 3.06). 07/2010; 40(7):787-99. DOI: 10.1007/s10803-009-0926-x
Source: PubMed


This study investigated the childhood autism rating scale (CARS) as a tool for ASD diagnoses for 2-year-old (n = 376) and 4-year-old (n = 230) children referred for possible autism. The cut-off score to distinguish autistic disorder from PDD-NOS was 32 in the 2-year-old sample (consistent with Lord in J Child Psychol Psychiatry Allied Discipl, 36, 1365-1382, 1995), and 30 in the 4-year-old sample, with good sensitivity and specificity at both ages. The cut-off score to distinguish ASD from non-ASD at both ages was 25.5, with good sensitivity and specificity. Results confirm the utility of the CARS in distinguishing autistic disorder from PDD-NOS, and distinguishing ASD from other developmental disorders and typical development and suggest that an ASD cutoff around 25, which is in common clinical use, is valid.

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    • "Another tool used by physicians for the screening of ASD-related symptoms is the childhood autism rating scale (CARS) (Chlebowski et al., 2010). CARS is a behavioral rating scale that serves as a useful tool to differentiate ASD from other developmental disorders such as intellectual disability and PDD–NOS (Chlebowski et al., 2010; Geier et al., 2013). It is also used to quantitatively describe the severity of the disorder of the child based on direct behavioral observation and using specific diagnostic criteria (Geier et al., 2013). "
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    ABSTRACT: Autism spectrum disorder (ASD) is a set of neurodevelopmental disorders that is among the most severe in terms of prevalence, morbidity and impact to the society. It is characterized by complex behavioral phenotype and deficits in both social and cognitive functions. Although the exact cause of ASD is still not known, the main findings emphasize the role of genetic and environmental factors in the development of autistic behavior. Environmental factors are also likely to interact with the genetic profile and cause aberrant changes in brain growth, neuronal development, and functional connectivity. The past few years have seen an increase in the prevalence of ASD, as a result of enhanced clinical tests and diagnostic tools. Despite growing evidence for the involvement of endogenous biomarkers in the pathophysiology of ASD, early detection of this disorder remains a big challenge. This paper describes the main behavioral and cognitive features of ASD, as well as the symptoms that differentiate autism from other developmental disorders. An attempt will be made to integrate all the available evidence which point to reduced brain connectivity, mirror neurons deficits, and inhibition-excitation imbalance in individuals with ASD. Finally, this review discusses the main factors involved in the pathophysiology of ASD, and illustrates some of the most important markers used for the diagnosis of this debilitating disorder. Copyright © 2015. Published by Elsevier Ltd.
    International journal of developmental neuroscience: the official journal of the International Society for Developmental Neuroscience 04/2015; 43. DOI:10.1016/j.ijdevneu.2015.04.003 · 2.58 Impact Factor
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    • "), most of the studies in this metaanalysis measured the receptive and expressive language skills of their participants with ASD while exploring research questions related to: (a) diet (Bent, Bertoglio, Ashwood, Bostrom, & Hendren, 2011; Johnson, Handen, Zimmer, Sacco, & Turner, 2011), (b) training and intervention outcomes (Cardon, 2012; Carson, Moosa, Theurer, & Oram Cardy, 2012; Dawson et al., 2010; Dykstra, Boyd, Watson, Crais, & Baranek, 2012), (c) social development (Johnson, Gillis, & Romanczyk, 2012; Kjellmer, Hedvall, Fernell, Gillberg, & Norrelgen, 2012; Losh, Martin, Klusek, Hogan-Brown, & Sideris, 2012), (d) other aspects of language development (Cleland, Gibbon, Peppé , O'Hare, & Rutherford, 2010; Haebig, McDuffie, & Ellis Weismer, 2013a, 2013b; Manolitsi & Botting, 2011; Park, Yelland, Taffe, & Gray, 2012; Schoen, Paul, & Chawarska, 2011), and (e) a variety of other topics (Adamson, Bakeman, Deckner, & Romski, 2009; Baranek et al., 2013; Bryce & Jahromi, 2013; Burns, King, & Spencer, 2013; Chlebowski, Green, Barton, & Fein, 2010; Davis et al., 2012; Diehl & Paul, 2012; Diehl, Watson, Bennetto, McDonough, & Gunlogson, 2009; Duerden et al., 2012; Hogan-Brown, Losh, Martin, & Mueffelmann, 2013; Jahromi, Bryce, & Swanson, 2013; Jasmin et al., 2009; Keen & Pennell, 2010; Kelley, Naigles, & Fein, 2010; Knaus et al., 2009, 2010; Knaus, Tager-Flusberg, & Foundas, 2012; Krstovska-Guerrero & Jones, 2013; Kuhl et al., 2013; Lane, Paynter, & Sharman, 2013; LeBarton & Iverson, 2013; Lopata et al., 2010; Mayo, Chlebowski, Fein, & Eigsti, 2013; Mayo & Eigsti, 2012; McCleery et al., 2010; McDuffie, Kover, Hagerman, & Abbeduto, 2013; McGregor et al., 2012; McGregor, Rost, Arenas, Farris-Trimble, & Stiles, 2013; Murdock, Ganz, & Crittendon, 2013; Naigles, Kelty, Jaffery, & Fein, 2011; Ozonoff et al., 2011; Petersen, Marinova-Todd, & Mirenda, 2012; Pexman et al., 2011; Pierce et al., 2011; Ray- Subramanian, Huai, & Ellis Weismer, 2011; Ricketts, Jones, Happé , & Charman, 2013; Rozga et al., 2011; Russo, Nicol, Trommer, Zecker, & Kraus, 2009; Schertz, Odom, Baggett, & Sideris, 2013; Shumway et al., 2012; Sullivan, Sharda, Greenson, Dawson, & Singh, 2013; Swanson & Siller, 2013; Thomeer et al., 2012; Veness et al., 2012; Verhoeven et al., 2012; Volden, Coolican, Garon, White, & Bryson, 2009; Watson, Roberts, Baranek, Mandulak, & Dalton, 2012; Yoder & Lieberman, 2010; Zachor & Ben Itzchak, 2010). "
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    ABSTRACT: Clinical anecdotes suggest that children with autism spectrum disorder (ASD) often show an atypical language profile in which expressive language exceeds receptive language competency. However, the few studies to directly explore this language profile have yielded inconsistent findings. This meta-analysis examined 74 studies that reported the receptive and expressive language performances of children and youth with ASD. Four potential predictors (age, language domain, source of language data, method of ASD diagnosis) were separately analyzed for their contribution to the relative receptive and expressive language impairment in ASD. Contrary to popular belief, the current meta-analyses found no evidence that an expressive advantage is common in ASD. Overall, children and youth with ASD showed equally impaired receptive and expressive language skills, both falling roughly 1.5 SD below peers with typical development. No discrepancies were found in receptive and expressive language across developmental stages, cognitive abilities, vocabulary, global language skills, caregiver report measures, clinician-administered measures, mixed method measures, or method of ASD diagnosis. Although some individual children with ASD may have an expressive-better-than-receptive language profile, this profile is not common enough to be a useful marker of ASD.
    Research in Autism Spectrum Disorders 01/2015; 9(1):202-222. DOI:10.1016/j.rasd.2014.10.008 · 2.96 Impact Factor
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    • "Our definition of optimal outcome was similar to that of Helt et al. [16]. We considered a case to have achieved an optimal outcome if he/she met the following criteria at baseline: (1) having a diagnosis of ASD at baseline based on DSM-IV criteria, (2) the presence of language delay (no words by 18 months and no word combinations by 24 months), and (3) total Childhood Autism Rating Scale (CARS) [24, 25] score over 25.5 based on scores reported by Chlebowski et al. [26], as well as these criteria at final assessment: (1) not meeting the criteria for any type of ASD based on DSM-IV, (2) not needing special education for the core symptoms of autism, (3) total score of CARS and Autism Behavior Checklist (ABC) [27, 28] in the nonautistic range, and (4) IQ in the nonretarded range (over 78). "
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    ABSTRACT: Aim. The aim of this study was to describe a group of children who lost a diagnosis of autism following participation in early educational programs. Method. This is a descriptive study reporting the characteristics of children (n: 39) who lost their diagnosis of autism and explaining the educational programs that these children followed. The data were collected by reviewing the participants' files and through examinations. Results. All of the children were placed at regular psychiatric follow-ups. The mean age at referral was 2.39±0.75 years, whereas the mean age at the time of optimal outcome reported was 5.11 ± 1.95 years. Two of the children were in early intensive behavioral intervention (EIBI), and the rest were in a comprehensive naturalistic behavioral program. The childhood autism rating scale (CARS) total scores at baseline and final were 32.75 ± 3.15 and 18.01 ± 1.76, respectively. The mean IQ of the group at final examination was 116.70 ± 18.88. Conclusion. It could be concluded that a group of children with an autism diagnosis could lose the diagnosis of autism upon early intervention. High IQ and the development of communicative and language skills at an early age could be the most powerful factors contributing to an optimal outcome.
    04/2014; 2014(4):472120. DOI:10.1155/2014/472120
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