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Heterogeneity in Autism Spectrum Disorder Case-Finding Algorithms in United States Health Administrative Database Analyses / Scott D. GROSSE in Journal of Autism and Developmental Disorders, 52-9 (September 2022)
[article]
Titre : Heterogeneity in Autism Spectrum Disorder Case-Finding Algorithms in United States Health Administrative Database Analyses Type de document : Texte imprimé et/ou numérique Auteurs : Scott D. GROSSE, Auteur ; Phyllis NICHOLS, Auteur ; Kwame NYARKO, Auteur ; Matthew MAENNER, Auteur ; Melissa L. DANIELSON, Auteur ; Lindsay SHEA, Auteur Article en page(s) : p.4150-4163 Langues : Anglais (eng) Mots-clés : Algorithms Autism Spectrum Disorder/diagnosis/epidemiology Databases, Factual Humans Insurance Coverage United States/epidemiology Autism spectrum disorder Case-finding algorithms Claims data Health services research article to disclose. Index. décimale : PER Périodiques Résumé : Strengthening systems of care to meet the needs of individuals with autism spectrum disorder (ASD) is of growing importance. Administrative data provide advantages for research and planning purposes, including large sample sizes and the ability to identify enrollment in insurance coverage and service utilization of individuals with ASD. Researchers have employed varying strategies to identify individuals with ASD in administrative data. Differences in these strategies can limit the comparability of results across studies. This review describes implications of the varying strategies that have been employed to identify individuals with ASD in US claims databases, with consideration of the strengths and limitations of each approach. En ligne : http://dx.doi.org/10.1007/s10803-021-05269-1 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=486
in Journal of Autism and Developmental Disorders > 52-9 (September 2022) . - p.4150-4163[article] Heterogeneity in Autism Spectrum Disorder Case-Finding Algorithms in United States Health Administrative Database Analyses [Texte imprimé et/ou numérique] / Scott D. GROSSE, Auteur ; Phyllis NICHOLS, Auteur ; Kwame NYARKO, Auteur ; Matthew MAENNER, Auteur ; Melissa L. DANIELSON, Auteur ; Lindsay SHEA, Auteur . - p.4150-4163.
Langues : Anglais (eng)
in Journal of Autism and Developmental Disorders > 52-9 (September 2022) . - p.4150-4163
Mots-clés : Algorithms Autism Spectrum Disorder/diagnosis/epidemiology Databases, Factual Humans Insurance Coverage United States/epidemiology Autism spectrum disorder Case-finding algorithms Claims data Health services research article to disclose. Index. décimale : PER Périodiques Résumé : Strengthening systems of care to meet the needs of individuals with autism spectrum disorder (ASD) is of growing importance. Administrative data provide advantages for research and planning purposes, including large sample sizes and the ability to identify enrollment in insurance coverage and service utilization of individuals with ASD. Researchers have employed varying strategies to identify individuals with ASD in administrative data. Differences in these strategies can limit the comparability of results across studies. This review describes implications of the varying strategies that have been employed to identify individuals with ASD in US claims databases, with consideration of the strengths and limitations of each approach. En ligne : http://dx.doi.org/10.1007/s10803-021-05269-1 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=486 Identifying Autism with Head Movement Features by Implementing Machine Learning Algorithms / Zhong ZHAO in Journal of Autism and Developmental Disorders, 52-7 (July 2022)
[article]
Titre : Identifying Autism with Head Movement Features by Implementing Machine Learning Algorithms Type de document : Texte imprimé et/ou numérique Auteurs : Zhong ZHAO, Auteur ; Zhipeng ZHU, Auteur ; Xiaobin ZHANG, Auteur ; Haiming TANG, Auteur ; Jiayi XING, Auteur ; Xinyao HU, Auteur ; Jianping LU, Auteur ; Xingda QU, Auteur Article en page(s) : p.3038-3049 Langues : Anglais (eng) Mots-clés : Algorithms Autism Spectrum Disorder/diagnosis Autistic Disorder Child Head Movements Humans Machine Learning Autism Biomarkers Diagnosis Head movement Index. décimale : PER Périodiques Résumé : Our study investigated the feasibility of using head movement features to identify individuals with autism spectrum disorder (ASD). Children with ASD and typical development (TD) were required to answer ten yes-no questions, and they were encouraged to nod/shake head while doing so. The head rotation range (RR) and the amount of rotation per minute (ARPM) in the pitch (head nodding direction), yaw (head shaking direction) and roll (lateral head inclination) directions were computed, and further fed into machine learning classifiers as the input features. The maximum classification accuracy of 92.11% was achieved with the decision tree classifier with two features (i.e., RR_Pitch and ARPM_Yaw). Our study suggests that head movement dynamics contain objective biomarkers that could identify ASD. En ligne : http://dx.doi.org/10.1007/s10803-021-05179-2 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=477
in Journal of Autism and Developmental Disorders > 52-7 (July 2022) . - p.3038-3049[article] Identifying Autism with Head Movement Features by Implementing Machine Learning Algorithms [Texte imprimé et/ou numérique] / Zhong ZHAO, Auteur ; Zhipeng ZHU, Auteur ; Xiaobin ZHANG, Auteur ; Haiming TANG, Auteur ; Jiayi XING, Auteur ; Xinyao HU, Auteur ; Jianping LU, Auteur ; Xingda QU, Auteur . - p.3038-3049.
Langues : Anglais (eng)
in Journal of Autism and Developmental Disorders > 52-7 (July 2022) . - p.3038-3049
Mots-clés : Algorithms Autism Spectrum Disorder/diagnosis Autistic Disorder Child Head Movements Humans Machine Learning Autism Biomarkers Diagnosis Head movement Index. décimale : PER Périodiques Résumé : Our study investigated the feasibility of using head movement features to identify individuals with autism spectrum disorder (ASD). Children with ASD and typical development (TD) were required to answer ten yes-no questions, and they were encouraged to nod/shake head while doing so. The head rotation range (RR) and the amount of rotation per minute (ARPM) in the pitch (head nodding direction), yaw (head shaking direction) and roll (lateral head inclination) directions were computed, and further fed into machine learning classifiers as the input features. The maximum classification accuracy of 92.11% was achieved with the decision tree classifier with two features (i.e., RR_Pitch and ARPM_Yaw). Our study suggests that head movement dynamics contain objective biomarkers that could identify ASD. En ligne : http://dx.doi.org/10.1007/s10803-021-05179-2 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=477 Separate scoring algorithms for specific identification priorities optimize the screening properties of the Screening Tool for Autism in Toddlers (STAT) / Shana M. ATTAR in Autism Research, 15-11 (November 2022)
[article]
Titre : Separate scoring algorithms for specific identification priorities optimize the screening properties of the Screening Tool for Autism in Toddlers (STAT) Type de document : Texte imprimé et/ou numérique Auteurs : Shana M. ATTAR, Auteur ; Lisa V. IBANEZ, Auteur ; Wendy L. STONE, Auteur Article en page(s) : p.2069-2080 Langues : Anglais (eng) Mots-clés : Child, Preschool Humans Autism Spectrum Disorder/diagnosis Autistic Disorder/diagnosis Mass Screening/methods Algorithms ROC Curve Asd autism community diagnosis novel assessments screening author’s share of royalties from Vanderbilt University for sales. Index. décimale : PER Périodiques Résumé : The Screening Tool for Autism in Toddlers (STAT) is a validated stage-2 autism spectrum disorder (ASD) screening measure that takes 20 minutes to administer and comprises 12 play-based items that are scored according to specific criteria. This study examines an expanded version (STAT-E) that includes the examiner's subjective ratings of children's social engagement (SE) and atypical behaviors (AB) in the scoring algorithm. The sample comprised 238 children who were 24-35 months old. The STAT-E assessors had limited ASD experience to mimic its use by community-based non-specialists, and were trained using a scalable web-based platform. A diagnostic evaluation was completed by clinical experts who were blind to the STAT-E results. Logistic regression, ROC curves, and classification matrices and metrics were used to determine the screening properties of STAT-E when scored using the original STAT scoring algorithm versus a new algorithm that included the SE and AB ratings. Inclusion of the SE and AB ratings improved positive risk classification appreciably, while the specificity declined. These results suggest that the STAT-E using the original STAT scoring algorithm optimizes specificity, while the STAT-E scoring algorithm with the two new ratings optimizes the positive risk classification. Using multiple scoring algorithms on the STAT may provide improved screening accuracy for diverse contexts, and a scalable web-based tutorial may be a pathway for increasing the number of community providers who can administer the STAT and contribute toward increased rates of autism screening. En ligne : http://dx.doi.org/10.1002/aur.2799 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=488
in Autism Research > 15-11 (November 2022) . - p.2069-2080[article] Separate scoring algorithms for specific identification priorities optimize the screening properties of the Screening Tool for Autism in Toddlers (STAT) [Texte imprimé et/ou numérique] / Shana M. ATTAR, Auteur ; Lisa V. IBANEZ, Auteur ; Wendy L. STONE, Auteur . - p.2069-2080.
Langues : Anglais (eng)
in Autism Research > 15-11 (November 2022) . - p.2069-2080
Mots-clés : Child, Preschool Humans Autism Spectrum Disorder/diagnosis Autistic Disorder/diagnosis Mass Screening/methods Algorithms ROC Curve Asd autism community diagnosis novel assessments screening author’s share of royalties from Vanderbilt University for sales. Index. décimale : PER Périodiques Résumé : The Screening Tool for Autism in Toddlers (STAT) is a validated stage-2 autism spectrum disorder (ASD) screening measure that takes 20 minutes to administer and comprises 12 play-based items that are scored according to specific criteria. This study examines an expanded version (STAT-E) that includes the examiner's subjective ratings of children's social engagement (SE) and atypical behaviors (AB) in the scoring algorithm. The sample comprised 238 children who were 24-35 months old. The STAT-E assessors had limited ASD experience to mimic its use by community-based non-specialists, and were trained using a scalable web-based platform. A diagnostic evaluation was completed by clinical experts who were blind to the STAT-E results. Logistic regression, ROC curves, and classification matrices and metrics were used to determine the screening properties of STAT-E when scored using the original STAT scoring algorithm versus a new algorithm that included the SE and AB ratings. Inclusion of the SE and AB ratings improved positive risk classification appreciably, while the specificity declined. These results suggest that the STAT-E using the original STAT scoring algorithm optimizes specificity, while the STAT-E scoring algorithm with the two new ratings optimizes the positive risk classification. Using multiple scoring algorithms on the STAT may provide improved screening accuracy for diverse contexts, and a scalable web-based tutorial may be a pathway for increasing the number of community providers who can administer the STAT and contribute toward increased rates of autism screening. En ligne : http://dx.doi.org/10.1002/aur.2799 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=488 Replication study of ADOS-2 Toddler Module cut-off scores for autism spectrum disorder classification / J. S. HONG in Autism Research, 14-6 (June 2021)
[article]
Titre : Replication study of ADOS-2 Toddler Module cut-off scores for autism spectrum disorder classification Type de document : Texte imprimé et/ou numérique Auteurs : J. S. HONG, Auteur ; V. SINGH, Auteur ; L. KALB, Auteur ; A. ASHKAR, Auteur ; R. LANDA, Auteur Article en page(s) : p.1284-1295 Langues : Anglais (eng) Mots-clés : Algorithms Autism Spectrum Disorder/diagnosis Autistic Disorder Child, Preschool Humans Infant ROC Curve Sensitivity and Specificity autism spectrum disorder classification diagnosis validity Index. décimale : PER Périodiques Résumé : The Autism Diagnostic Observation Schedule, Second Edition (ADOS-2) has been regarded as the gold standard assessment of autism spectrum disorder (ASD). While clinical validity of ADOS-2 Modules 1-4 have been extensively studied, there has been very limited research examining the clinical validity of ADOS-2 Toddler Module. The goal of this study was to examine alignment of the ADOS-2 Toddler Module classification with clinicians' determination of ASD, with assessing cut-off scores for diagnosing ASD in toddlers. A total of 412 toddlers ages 12-30?months who received ADOS-2 Toddler Module as well as a best estimate clinical (BEC) diagnosis, were included in this study. ADOS-2 Toddler Module cut-off scores were determined using the appropriate algorithms (Algorithm 1 for toddlers aged 12-20?months and those aged 21-30?months with <5 words, Algorithm 2 for toddlers aged 21-30?months with 5 words or more). Receiver operating characteristic (ROC) curves were used to assess cut-off scores that optimized sensitivity and specificity when compared against BEC diagnosis. The selected cut-off scores were examined using frequency tables to compare ADOS-2 classification against BEC diagnosis. For Algorithm 1, classification statistics were optimized at the cut-off score of 12 with an area under the curve (AUC) of 0.92. For Algorithm 2, classification statistics were optimized at the cut-off score of 10 with an AUC of 0.96. The ADOS-2 Toddler Module classification is strongly aligned with BEC diagnosis. The optimal cut-off scores identified in the current study reflect the same results configured by the prior study. LAY SUMMARY: ADOS-2 Toddler Module has been widely used for the ASD assessment, but there have been limited research on its clinical validity. This study is the first replication of the ADOS-2 Toddler Module with a large independent sample. We examined alignment of the ADOS-2 Toddler Module classification with clinicians' determination of ASD, with assessing cut-off scores, and confirmed the clinical validity of ADOS-2 Toddler Module. Cut-off scores of ADOS-2 Toddler Module cited in the manual yielded best clinical utility for diagnosing ASD in toddlers. En ligne : http://dx.doi.org/10.1002/aur.2496 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=449
in Autism Research > 14-6 (June 2021) . - p.1284-1295[article] Replication study of ADOS-2 Toddler Module cut-off scores for autism spectrum disorder classification [Texte imprimé et/ou numérique] / J. S. HONG, Auteur ; V. SINGH, Auteur ; L. KALB, Auteur ; A. ASHKAR, Auteur ; R. LANDA, Auteur . - p.1284-1295.
Langues : Anglais (eng)
in Autism Research > 14-6 (June 2021) . - p.1284-1295
Mots-clés : Algorithms Autism Spectrum Disorder/diagnosis Autistic Disorder Child, Preschool Humans Infant ROC Curve Sensitivity and Specificity autism spectrum disorder classification diagnosis validity Index. décimale : PER Périodiques Résumé : The Autism Diagnostic Observation Schedule, Second Edition (ADOS-2) has been regarded as the gold standard assessment of autism spectrum disorder (ASD). While clinical validity of ADOS-2 Modules 1-4 have been extensively studied, there has been very limited research examining the clinical validity of ADOS-2 Toddler Module. The goal of this study was to examine alignment of the ADOS-2 Toddler Module classification with clinicians' determination of ASD, with assessing cut-off scores for diagnosing ASD in toddlers. A total of 412 toddlers ages 12-30?months who received ADOS-2 Toddler Module as well as a best estimate clinical (BEC) diagnosis, were included in this study. ADOS-2 Toddler Module cut-off scores were determined using the appropriate algorithms (Algorithm 1 for toddlers aged 12-20?months and those aged 21-30?months with <5 words, Algorithm 2 for toddlers aged 21-30?months with 5 words or more). Receiver operating characteristic (ROC) curves were used to assess cut-off scores that optimized sensitivity and specificity when compared against BEC diagnosis. The selected cut-off scores were examined using frequency tables to compare ADOS-2 classification against BEC diagnosis. For Algorithm 1, classification statistics were optimized at the cut-off score of 12 with an area under the curve (AUC) of 0.92. For Algorithm 2, classification statistics were optimized at the cut-off score of 10 with an AUC of 0.96. The ADOS-2 Toddler Module classification is strongly aligned with BEC diagnosis. The optimal cut-off scores identified in the current study reflect the same results configured by the prior study. LAY SUMMARY: ADOS-2 Toddler Module has been widely used for the ASD assessment, but there have been limited research on its clinical validity. This study is the first replication of the ADOS-2 Toddler Module with a large independent sample. We examined alignment of the ADOS-2 Toddler Module classification with clinicians' determination of ASD, with assessing cut-off scores, and confirmed the clinical validity of ADOS-2 Toddler Module. Cut-off scores of ADOS-2 Toddler Module cited in the manual yielded best clinical utility for diagnosing ASD in toddlers. En ligne : http://dx.doi.org/10.1002/aur.2496 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=449 Asymmetry of fusiform structure in autism spectrum disorder: trajectory and association with symptom severity / C. C. DOUGHERTY in Molecular Autism, 7 (2016)
[article]
Titre : Asymmetry of fusiform structure in autism spectrum disorder: trajectory and association with symptom severity Type de document : Texte imprimé et/ou numérique Auteurs : C. C. DOUGHERTY, Auteur ; D. W. EVANS, Auteur ; G. J. KATUWAL, Auteur ; A. M. MICHAEL, Auteur Article en page(s) : 28p. Langues : Anglais (eng) Mots-clés : Adolescent Adult Algorithms Autism Spectrum Disorder/diagnostic imaging/pathology Child Cross-Sectional Studies Humans Image Processing, Computer-Assisted Magnetic Resonance Imaging Male Severity of Illness Index Temporal Lobe/anatomy & histology Young Adult Asymmetry Autism spectrum disorder Development Fusiform gyrus Structural imaging Index. décimale : PER Périodiques Résumé : BACKGROUND: While asymmetry in the fusiform gyrus (FFG) has been reported in functional and structural studies in typically developing controls (TDC), few studies have examined FFG asymmetry in autism spectrum disorder (ASD) subjects and those studies are limited by small sample sizes, and confounded by cognitive ability or handedness. No previous work has examined FFG surface area or cortical thickness asymmetry in ASD; nor do we understand the trajectory of FFG asymmetry over time. Finally, it is not known how FFG structural asymmetry relates to ASD symptom severity. METHODS: In this study, we examined FFG volume, surface area, and cortical thickness asymmetry, as well as their cross-sectional trajectories in a large sample of right-handed males aged 7 to 25 years with 128 ASD and 127 TDC subjects using general linear models. In addition, we examined the relationship between FFG asymmetry and ASD severity using the Autism Diagnostic Observation Schedule (ADOS) and Gotham autism severity scores. RESULTS: Findings revealed that while group differences were evident with mean leftward asymmetry in ASD and mean near symmetry in TDC volume and surface area, asymmetry for both groups existed on a spectrum encompassing leftward and rightward asymmetry. In ASD subjects, volume asymmetry was negatively associated with ADOS and autism severity score symptom measures, with a subset of rightward asymmetric patients being most severely affected. We also observed differential trajectory of surface area asymmetry: ASD subjects exhibited a change from leftward asymmetry toward symmetry from age 7 to 25, whereas TDCs exhibited the reverse trend with a change from near symmetry toward leftward symmetry over the observed age range. CONCLUSIONS: Abnormalities in FFG structural asymmetry are related to symptom severity in ASD and show differential developmental trajectory compared to TDC. This study is the first to note these findings. These results may have important implications for understanding the role of FFG asymmetry in ASD. En ligne : http://dx.doi.org/10.1186/s13229-016-0089-5 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=328
in Molecular Autism > 7 (2016) . - 28p.[article] Asymmetry of fusiform structure in autism spectrum disorder: trajectory and association with symptom severity [Texte imprimé et/ou numérique] / C. C. DOUGHERTY, Auteur ; D. W. EVANS, Auteur ; G. J. KATUWAL, Auteur ; A. M. MICHAEL, Auteur . - 28p.
Langues : Anglais (eng)
in Molecular Autism > 7 (2016) . - 28p.
Mots-clés : Adolescent Adult Algorithms Autism Spectrum Disorder/diagnostic imaging/pathology Child Cross-Sectional Studies Humans Image Processing, Computer-Assisted Magnetic Resonance Imaging Male Severity of Illness Index Temporal Lobe/anatomy & histology Young Adult Asymmetry Autism spectrum disorder Development Fusiform gyrus Structural imaging Index. décimale : PER Périodiques Résumé : BACKGROUND: While asymmetry in the fusiform gyrus (FFG) has been reported in functional and structural studies in typically developing controls (TDC), few studies have examined FFG asymmetry in autism spectrum disorder (ASD) subjects and those studies are limited by small sample sizes, and confounded by cognitive ability or handedness. No previous work has examined FFG surface area or cortical thickness asymmetry in ASD; nor do we understand the trajectory of FFG asymmetry over time. Finally, it is not known how FFG structural asymmetry relates to ASD symptom severity. METHODS: In this study, we examined FFG volume, surface area, and cortical thickness asymmetry, as well as their cross-sectional trajectories in a large sample of right-handed males aged 7 to 25 years with 128 ASD and 127 TDC subjects using general linear models. In addition, we examined the relationship between FFG asymmetry and ASD severity using the Autism Diagnostic Observation Schedule (ADOS) and Gotham autism severity scores. RESULTS: Findings revealed that while group differences were evident with mean leftward asymmetry in ASD and mean near symmetry in TDC volume and surface area, asymmetry for both groups existed on a spectrum encompassing leftward and rightward asymmetry. In ASD subjects, volume asymmetry was negatively associated with ADOS and autism severity score symptom measures, with a subset of rightward asymmetric patients being most severely affected. We also observed differential trajectory of surface area asymmetry: ASD subjects exhibited a change from leftward asymmetry toward symmetry from age 7 to 25, whereas TDCs exhibited the reverse trend with a change from near symmetry toward leftward symmetry over the observed age range. CONCLUSIONS: Abnormalities in FFG structural asymmetry are related to symptom severity in ASD and show differential developmental trajectory compared to TDC. This study is the first to note these findings. These results may have important implications for understanding the role of FFG asymmetry in ASD. En ligne : http://dx.doi.org/10.1186/s13229-016-0089-5 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=328 Replication study for ADOS-2 cut-offs to assist evaluation of autism spectrum disorder / Ji Su HONG in Autism Research, 15-11 (November 2022)
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