The Ritvo Autism Asperger Diagnostic Scale-Revised (RAADS-R): a scale to assist the diagnosis of Autism Spectrum Disorder in adults: an international validation study.
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ABSTRACT:
SUBMITTER: Ritvo RA
PROVIDER: S-EPMC3134766 | biostudies-other | 2011 Aug
REPOSITORIES: biostudies-other
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Project description:ObjectivesWe examined the agreement between the Autism Diagnostic Observation Schedule (ADOS) and the Childhood Autism Rating Scale (CARS) in the diagnosis of autism spectrum disorder.MethodsThe ADOS and CARS scores of 78 children were retrospectively collected from a chart review. A correlation analysis was performed to examine the concurrent validity between the two measures. Using the receiver operating characteristic (ROC) curve, we determined the optimal cut-off score of the CARS for identifying autism spectrum disorder.ResultsThe CARS score was significantly correlated with the ADOS score (r=0.808, p<0.001). Taking ADOS as the ideal standard, the optimal cut-off scores of CARS for identifying autism and autism spectrum were 30 and 24.5, respectively.ConclusionWe determined the optimal cut-off scores of CARS for screening and diagnosing autism spectrum disorder.
| S-EPMC7289466 | biostudies-literature
Project description:The Thai Diagnostic Autism Scale (TDAS) was developed to diagnose autism spectrum disorder (ASD) under the context and characteristics of the Thai population. Although the tool has an excellent agreement, the interpretation of diagnostic results needs to rely on the optimal cut-off point to maximize efficiency and clarity. This study aims to find an optimal cut-off point for TDAS in the diagnosis of ASD and to compare its agreement with the DSM-5 ASD criteria. This study was conducted on 156 children aged 12-48 months old who were suspected of having ASD and had enrolled from hospitals in the four regions of Thailand in 2017-2018. The optimal cut-off point for TDAS was considered by using receiver operating characteristic (ROC) curves according to the DSM-5 ASD criteria. The areas under the curve (AUCs) for TDAS and ADOS-2 were also compared. Multivariable logistic regression was performed to create a predictive model for the probability of ASD. The AUC of TDAS was significantly higher than that of ADOS-2 (0.8748 vs. 0.7993; p = 0.033). The optimal cut-off point for TDAS was ≥20 points (accuracy = 82.05%, sensitivity = 82.86%, and specificity = 80.93%). Our findings show that TDAS with a cut-off point can yield higher diagnostic accuracy than ADOS-2 and TDAS domain. Diagnosis by using this cut-off point could be useful in practical assessments.
| S-EPMC9602004 | biostudies-literature
Project description:ImportanceAutism spectrum disorder (ASD) affects 1 in 44 children. The Autism Diagnostic Observation Schedule (ADOS) is a semi-structured observation developed for use in research but is considered a component of gold standard clinical diagnosis. The ADOS adds time and cost to diagnostic assessments.ObjectiveTo evaluate consistency between clinical diagnosis (index ASD diagnosis) and diagnosis incorporating the ADOS (reference standard ASD diagnosis) and to examine clinician and child factors that predict consistency between index diagnoses and reference standard diagnoses.Design, setting, and participantsThis prospective diagnostic study was conducted between May 2019 and February 2020. Developmental-behavioral pediatricians (DBPs) made a diagnosis based on clinical assessment (index ASD diagnosis). The ADOS was then administered, after which the DBP made a second diagnosis (reference standard ASD diagnosis). DBPs self-reported diagnostic certainty at the time of the index diagnoses and reference standard diagnoses. The study took place at 8 sites (7 US and 1 European) that provided subspecialty assessments for children with concerns for ASD. Participants included children aged 18 months to 5 years, 11 months, without a prior ASD diagnosis, consecutively referred for possible ASD. Among 648 eligible children, 23 refused, 376 enrolled, and 349 completed the study. All 40 eligible DBPs participated.ExposuresADOS administered to all child participants.Main outcomes and measuresIndex diagnoses and reference standard diagnoses of ASD (yes/no).ResultsAmong the 349 children (279 [79.7%] male; mean [SD] age, 39.9 [13.4] months), index diagnoses and reference standard diagnoses were consistent for 314 (90%) (ASD = 250; not ASD = 64) and changed for 35. Clinician diagnostic certainty was the most sensitive and specific predictor of diagnostic consistency (area under curve = 0.860; P < .001). In a multilevel logistic regression, no child or clinician factors improved prediction of diagnostic consistency based solely on clinician diagnostic certainty at time of index diagnosis.Conclusions and relevanceIn this prospective diagnostic study, clinical diagnoses of ASD by DBPs with vs without the ADOS were consistent in 90.0% of cases. Clinician diagnostic certainty predicted consistency of index diagnoses and reference standard diagnoses. This study suggests that the ADOS is generally not required for diagnosis of ASD in young children by DBPs and that DBPs can identify children for whom the ADOS may be needed.
| S-EPMC9577880 | biostudies-literature
Project description:Diagnostic and Statistical Manual of mental disorder-IV (DSM-IV) TR based INCLEN Diagnostic Tool for Autism Spectrum Disorder (INDT-ASD) is an established instrument for the diagnosis of ASD in Indian subcontinent and low-middle income countries (LMIC). The introduction of DSM-5 necessitated revision of existing INDT-ASD tool to incorporate the DSM-5 related changes. This study was undertaken to develop and validate the DSM-5 based All India Institute of Medical Sciences (AIIMS)-Modified-INDT-ASD Tool. The modifications were done using Delphi method and included: (a) rearrangement of questions from the previous tool; and (b) addition of new questions on sensory symptoms. The modified tool was validated against DSM-5 diagnostic criteria. In addition, receiver operating characteristic (ROC) curves were used to determine the cut-off for total score as compared to Childhood Autism Rating Scale (CARS) score to grade the severity of ASD. Two-hundred-twenty-five children (159 boys, median age = 47months) were enrolled. The modified tool demonstrated sensitivity of 98.4% and specificity of 91.7% to diagnose ASD. A score ≥14 on the tool was suggestive of severe ASD (CARS>36.5) with a sensitivity and specificity of 80% and 80.7% respectively [Area under the curve = 0.89]. AIIMS-Modified-INDT-ASD Tool is a simple and structured instrument based on DSM-5 criteria which can facilitate diagnosis of ASD with acceptable diagnostic accuracy.
| S-EPMC6415840 | biostudies-literature
Project description:This article presents the revised consensus criteria for the diagnosis of frontotemporal dysfunction in amyotrophic lateral sclerosis (ALS) based on an international research workshop on frontotemporal dementia (FTD) and ALS held in London, Canada in June 2015. Since the publication of the Strong criteria, there have been considerable advances in the understanding of the neuropsychological profile of patients with ALS. Not only is the breadth and depth of neuropsychological findings broader than previously recognised - - including deficits in social cognition and language - but mixed deficits may also occur. Evidence now shows that the neuropsychological deficits in ALS are extremely heterogeneous, affecting over 50% of persons with ALS. When present, these deficits significantly and adversely impact patient survival. It is the recognition of this clinical heterogeneity in association with neuroimaging, genetic and neuropathological advances that has led to the current re-conceptualisation that neuropsychological deficits in ALS fall along a spectrum. These revised consensus criteria expand upon those of 2009 and embrace the concept of the frontotemporal spectrum disorder of ALS (ALS-FTSD).
| S-EPMC7409990 | biostudies-literature
Project description:Heterogeneity in phenotypic presentation of Autism spectrum disorders has been cited as one explanation for the difficulty in pinpointing specific genes involved in autism. Recent studies have attempted to reduce the "noise" in genetic and other biological data by reducing the phenotypic heterogeneity of the sample population. The current study employs multiple clustering algorithms on 123 item scores from the Autism Diagnostic Interview-Revised (ADI-R) diagnostic instrument of nearly 2,000 autistic individuals to identify subgroups of autistic probands with clinically relevant behavioral phenotypes in order to isolate more homogeneous groups of subjects for gene expression analyses. Our combined cluster analyses suggest optimal division of the autistic probands into four phenotypic clusters based on similarity of symptom severity across the 123 selected item scores. One cluster is characterized by severe language deficits, while another exhibits milder symptoms across the domains. A third group possesses a higher frequency of savant skills while the fourth group exhibited intermediate severity across all domains. Grouping autistic individuals by multivariate cluster analysis of ADI-R scores reveals meaningful phenotypes of subgroups within the autistic spectrum, which we show, in a related (accompanying) study, to be associated with distinct gene expression profiles.
| S-EPMC2737479 | biostudies-literature
Project description:Background:The aim of this paper was to provide an initial validation of a newly developed parent questionnaire-the Stanford Social Dimensions Scale (SSDS), designed to capture individual differences across several key social dimensions including social motivation in children and adolescents with and without psychiatric disorders. Methods:The initial validation sample was comprised of parents of 175 individuals with autism spectrum disorder (ASD) (35 females, 140 males; M age = 7.19 years, SD age = 3.96) and the replication sample consisted of 624 parents of children who were either typically developing or presented with a range of neurodevelopmental and neuropsychiatric disorders (302 females, 322 males; M age = 11.49 years, SDage = 4.48). Parents from both samples completed the SSDS and the Social Responsiveness Scale (SRS-2). Results:Exploratory Structural Equation Modeling indicated that a 5-factor model provided adequate to excellent fit to the data in the initial ASD sample (comparative fit index [CFI] = .940, Tucker-Lewis Index [TLI] = .919, root mean square error of approximation [RMSEA] = .048, standardized root mean square residual [SRMR] = .038). The identified factors were interpreted as Social Motivation, Social Affiliation, Expressive Social Communication, Social Recognition, and Unusual Approach. This factor structure was further confirmed in Sample 2 (CFI = 946, TLI = .930, RMSEA = .044, SRMR = .026). Internal consistency for all subscales was in the good to excellent range across both samples as indicated by Composite Reliability scores of ≥ .72. Convergent and divergent validity was strong as indexed by the pattern of correlations with relevant SRS-2 and Child Behavior Checklist domains and with verbal and non-verbal intellectual functioning scores in Sample 1 and with the Need to Belong Scale and Child Social Preference Scale scores in Sample 2. Across both samples, females had higher social motivation and expressive social communication scores. Discriminant validity was strong given that across all SSDS subscales, the ASD sample had significantly higher impairment than both the typically developing group and the group with other clinical conditions, which in turn, had significantly higher impairment than the typically developing group. Conclusions:Our findings provide initial validation of a new scale designed to comprehensively capture individual differences in social motivation and other key social dimensions in ASD.
| S-EPMC6921422 | biostudies-literature
Project description:Few clinically validated biomarkers of ASD exist which can rapidly, accurately, and objectively identify autism during the first years of life and be used to support optimized treatment outcomes and advances in precision medicine. As such, the goal of the present study was to leverage both simple and computationally-advanced approaches to validate an eye-tracking measure of social attention preference, the GeoPref Test, among 1,863 ASD, delayed, or typical toddlers (12-48 months) referred from the community or general population via a primary care universal screening program. Toddlers participated in diagnostic and psychometric evaluations and the GeoPref Test: a 1-min movie containing side-by-side dynamic social and geometric images. Following testing, diagnosis was denoted as ASD, ASD features, LD, GDD, Other, typical sibling of ASD proband, or typical. Relative to other diagnostic groups, ASD toddlers exhibited the highest levels of visual attention towards geometric images and those with especially high fixation levels exhibited poor clinical profiles. Using the 69% fixation threshold, the GeoPref Test had 98% specificity, 17% sensitivity, 81% PPV, and 65% NPV. Sensitivity increased to 33% when saccades were included, with comparable validity across sex, ethnicity, or race. The GeoPref Test was also highly reliable up to 24 months following the initial test. Finally, fixation levels among twins concordant for ASD were significantly correlated, indicating that GeoPref Test performance may be genetically driven. As the GeoPref Test yields few false positives (~ 2%) and is equally valid across demographic categories, the current findings highlight the ability of the GeoPref Test to rapidly and accurately detect autism before the 2nd birthday in a subset of children and serve as a biomarker for a unique ASD subtype in clinical trials.
| S-EPMC8917231 | biostudies-literature
Project description:BACKGROUND: Introduction of proposed criteria for DSM-5 Autism Spectrum Disorder (ASD) has raised concerns that some individuals currently meeting diagnostic criteria for Pervasive Developmental Disorder (PDD; DSM-IV-TR/ICD-10) will not qualify for a diagnosis under the proposed changes. To date, reports of sensitivity and specificity of the new criteria have been inconsistent across studies. No study has yet considered how changes at the 'sub domain' level might affect overall sensitivity and specificity, and few have included individuals of different ages and ability levels. METHODS: A set of DSM-5 ASD algorithms were developed using items from the Diagnostic Interview for Social and Communication Disorders (DISCO). The number of items required for each DSM-5 subdomain was defined either according to criteria specified by DSM-5 (Initial Algorithm), a statistical approach (Youden J Algorithm), or to minimise the number of false positives while maximising sensitivity (Modified Algorithm). The algorithms were designed, tested and compared in two independent samples (Sample 1, N = 82; Sample 2, N = 115), while sensitivity was assessed across age and ability levels in an additional dataset of individuals with an ICD-10 PDD diagnosis (Sample 3, N = 190). RESULTS: Sensitivity was highest in the Initial Algorithm, which had the poorest specificity. Although Youden J had excellent specificity, sensitivity was significantly lower than in the Modified Algorithm, which had both good sensitivity and specificity. Relaxing the domain A rules improved sensitivity of the Youden J Algorithm, but it remained less sensitive than the Modified Algorithm. Moreover, this was the only algorithm with variable sensitivity across age. All versions of the algorithm performed well across ability level. CONCLUSIONS: This study demonstrates that good levels of both sensitivity and specificity can be achieved for a diagnostic algorithm adhering to the DSM-5 criteria that is suitable across age and ability level.
| S-EPMC4098079 | biostudies-other
Project description:The reported prevalence of autism spectrum disorder (ASD) has been increasing rapidly in many parts of the world. However, data on its prevalence in China are largely missing. Here, we assessed the suitability of the modified Chinese version of a newly-developed ASD screening tool, the Modified Chinese Autism Spectrum Rating Scales (MC-ASRS) in screening for ASD in Chinese children aged 6-12 years, through comparison with the Social Responsiveness Scale (SRS) that has been widely used for ASD screening. We recruited the parents/caregivers of 1588 typically-developing children and 190 children with ASD aged 6-12 years to complete the MC-ASRS and SRS, and evaluated the validity of both scales in discriminating children with ASD from those developing typically. The results showed that MC-ASRS performed as well as SRS in sensitivity, specificity, and area-under-the-curve (both >0.95) in receiver operating characteristic analysis, with a fair false-negative rate. These results suggest that MC-ASRS is a promising tool for screening for children with ASD in the general Chinese population.
| S-EPMC5360843 | biostudies-other