scholarly journals Validity of Autism Behavior Checklist (ABC): preliminary study

2005 ◽  
Vol 27 (4) ◽  
pp. 295-301 ◽  
Author(s):  
Márcia Regina Fumagalli Marteleto ◽  
Márcia Regina Marcondes Pedromônico
Keyword(s):  
Roc Curve ◽  
Criterion Validity ◽  
Cutoff Score ◽  
Autistic Children ◽  
Autism Behavior Checklist ◽  
Dsm Iv ◽  
The Mean ◽  
Preliminary Study ◽  
Autistic Disorders ◽  
Autism Behavior

OBJECTIVE: To examine the concurrent and criterion validity of the Autism Behavior Checklist (ABC). METHODS: Three groups, comprising 38 mothers of children previously diagnosed with autism (DSM IV-TR, 2002), 43 mothers of children with language disorders other than autism, and 52 mothers of children who had no linguistic or behavioral complaints, were interviewed. In order to minimize the effect of maternal level of education, the questionnaire was completed by the researcher. To determine the concurrent validation, ANOVA and discriminant analysis were used. The ROC curve was used to establish the cutoff score of the sample and to examine the criterion validity. RESULTS: The mean total score was significantly higher in the group of mothers of autistic children than in the other groups. The ABC correctly identified 81.6% of the autistic children. The ROC curve cutoff score was 49, and the sensitivity was 92.1%, higher than the 57.89% found when a cutoff score of 68 was used. The specificity was 92.6%, similar to the 94.73% obtained with a cutoff score of 68. CONCLUSIONS: The ABC shows promise as an instrument for identifying children with autistic disorders, both in clinical and educational contexts, especially when a cutoff score of 49 is used.

A Comparison of DSM-IV and international expert consensus diagnostic criteria for N.M.S

2017 ◽  
Vol 41 (S1) ◽  
pp. S754-S754 ◽  
Author(s):  
R. Gurrera ◽  
G. Mortillaro ◽  
V. Velamoor ◽  
S. Caroff
Keyword(s):  
Diagnostic Criteria ◽  
Roc Curve ◽  
Expert Consensus ◽  
Original Form ◽  
Cutoff Score ◽  
Reference Standard ◽  
International Expert ◽  
Roc Curve Analysis ◽  
Point Score ◽  
Dsm Iv

IntroductionNeuroleptic malignant syndrome (NMS) requires prompt recognition for effective management, but there are no established diagnostic criteria.ObjectivesTo validate the recently published international expert consensus (IEC) diagnostic criteria for NMS, which assign priority points based on the relative importance of each criterion for diagnosing NMS.AimsDetermine optimal diagnostic cutoff for priority point score.MethodsData were extracted from 221 archived telephone contact reports of clinician-initiated calls to a national telephone consultation service from 1997–2009; each case was given a total priority point score based on the IEC criteria. DSM-IV-TR research criteria, in original form and modified to accept less than ‘severe’ rigidity, served as the primary diagnostic reference standard. Consultants’ diagnoses served as an additional reference standard. The optimal priority point cutoff score was determined using receiver operating characteristic (ROC) curve analysis.ResultsArea under the ROC curve ranged from 0.715 (95% CI = 0.645–0.785, P < 0.001) for consultant diagnoses to 0.857 (95% CI = 0.808–0.907, P < 0.001) for modified DSM-IV-TR criteria. The latter was associated with 69.6% sensitivity and 90.7% specificity.ConclusionsAgreement was best between IEC criteria with a cutoff score of 74 and modified DSM-IV-TR criteria (sensitivity 69.6%, specificity 90.7%); this cutoff score demonstrated the highest agreement in all comparisons. Consultant diagnoses showed much better agreement with modified, compared to original, DSM-IV-TR criteria, suggesting that the DSM-IV-TR criterion of “severe” rigidity may be more restrictive than what most knowledgeable clinicians use in practice.Disclosure of interestThe authors have not supplied their declaration of competing interest.

Sensitivity of the Autism Behavior Checklist in Indian Autistic Children

2010 ◽  
Vol 31 (1) ◽  
pp. 48-49 ◽  
Author(s):  
Monica Juneja ◽  
Suvasini Sharma ◽  
Sharmila Banerjee Mukherjee
Keyword(s):  
Autistic Children ◽  
Autism Behavior Checklist ◽  
Autism Behavior

scholarly journals A Preliminary Study on Machine Learning-Based Evaluation of Static and Dynamic FET-PET for the Detection of Pseudoprogression in Patients with IDH-Wildtype Glioblastoma

Cancers ◽  
2020 ◽  
Vol 12 (11) ◽  
pp. 3080
Author(s):  
Sied Kebir ◽  
Teresa Schmidt ◽  
Matthias Weber ◽  
Lazaros Lazaridis ◽  
Norbert Galldiks ◽  
...  
Keyword(s):  
Machine Learning ◽  
Roc Curve ◽  
Response Assessment ◽  
Linear Discriminant ◽  
Fet Pet ◽  
Contrast Enhanced ◽  
The Mean ◽  
Preliminary Study ◽  
Validation Set ◽  
Dynamic Fet Pet

Pseudoprogression (PSP) detection in glioblastoma remains challenging and has important clinical implications. We investigated the potential of machine learning (ML) in improving the performance of PET using O-(2-[18F]-fluoroethyl)-L-tyrosine (FET) for differentiation of tumor progression from PSP in IDH-wildtype glioblastoma. We retrospectively evaluated the PET data of patients with newly diagnosed IDH-wildtype glioblastoma following chemoradiation. Contrast-enhanced MRI suspected PSP/TP and all patients underwent subsequently an additional dynamic FET-PET scan. The modified Response Assessment in Neuro-Oncology (RANO) criteria served to diagnose PSP. We trained a Linear Discriminant Analysis (LDA)-based classifier using FET-PET derived features on a hold-out validation set. The results of the ML model were compared with a conventional FET-PET analysis using the receiver-operating-characteristic (ROC) curve. Of the 44 patients included in this preliminary study, 14 patients were diagnosed with PSP. The mean (TBRmean) and maximum tumor-to-brain ratios (TBRmax) were significantly higher in the TP group as compared to the PSP group (p = 0.014 and p = 0.033, respectively). The area under the ROC curve (AUC) for TBRmax and TBRmean was 0.68 and 0.74, respectively. Using the LDA-based algorithm, the AUC (0.93) was significantly higher than the AUC for TBRmax. This preliminary study shows that in IDH-wildtype glioblastoma, ML-based PSP detection leads to better diagnostic performance.

scholarly journals Combination of Salivary Gland Ultrasonography and Virtual Touch Quantification for Diagnosis of Sjögren’s Syndrome: A Preliminary Study

2016 ◽  
Vol 2016 ◽  
pp. 1-6 ◽  
Author(s):  
Shaoqi Chen ◽  
Yukai Wang ◽  
Guohong Zhang ◽  
Shigao Chen
Keyword(s):  
Salivary Gland ◽  
Healthy Volunteers ◽  
Roc Curve ◽  
Classification Tree ◽  
Sicca Syndrome ◽  
Parotid Glands ◽  
Submandibular Glands ◽  
Promising Tool ◽  
The Mean ◽  
Preliminary Study

A total of 136 subjects (51 SS patients, 35 sicca syndrome patients without SS, and 50 healthy volunteers) were enrolled in this study. The mean SWV value for salivary glands of SS patients was statistically higher than that of controls (2.81 ± 0.66 m/s versus 1.85 ± 0.28 m/s for parotid glands and 2.29 ± 0.34 m/s versus 1.82 ± 0.25 m/s for submandibular glands, resp.). Combining SWV values of parotid and submandibular glands gives a sensitivity of 88.2% (95% CI: 76.1–95.6%) and specificity of 96.0% (95% CI: 86.3–99.5%) at the cutoff point of 2.19 m/s, with an AUROC of 0.954 (95% CI: 0.893–0.986). In addition, combining SGUS score and SWV value yields a sensitivity of 98.0% (95% CI: 89.6–100%), specificity of 90.0% (95% CI: 78.2–96.7%), and AUROC of 0.962 (95% CI: 0.904–0.990). Classification tree considering the sequential use of SGUS score and SWV value achieved 92.1% accuracy for diagnosis of SS. Similarly, the ROC curve of combined SGUS scores and SWV values yields an AUROC of 0.954 (95% CI: 0.885–0.987), sensitivity of 97.1% (95% CI: 85.1–99.9%), and specificity of 92.2% (95% CI: 81.1–97.8%) for separating sicca syndrome patients (without SS) from SS patients. Combining SGUS and VTQ provides a promising tool for diagnosis of SS.

Adapted Autism Behavior Checklist

2019 ◽  
Author(s):  
Onur Özdemir ◽  
Ibrahim Halil Diken
Keyword(s):  
Autism Behavior Checklist ◽  
Autism Behavior

Is Speed of Onset of Anti-anxiety Efficacy with Pregabalin Influenced by Starting Dose?

2009 ◽  
Vol 24 (S1) ◽  
pp. 1-1
Author(s):  
B. Herman ◽  
F. Mandel
Keyword(s):  
Dose Response ◽  
Change Score ◽  
Early Improvement ◽  
Response Effect ◽  
Starting Dose ◽  
Dsm Iv ◽  
The Mean ◽  
Dose Response Effect ◽  
Titration Schedule ◽  
Speed Of Onset

Objective:There appears to be no dose-response effect for pregabalin at doses of 300-600 mg, and a modest dose-response effect in the range of 150-300 mg. The goal of the current investigation was to determine the effect of the starting dose on the speed of onset of anxiolytic efficacy.Methods:Data were analyzed from 7 trials of outpatients with DSM-IV GAD and a HAM-A total score ≥18. Starting doses of pregabalin ranged from 100 mg (N=301) or 150 mg (N=104), to 200 mg (N=167) and 300 mg (N=388). Assessment of early improvement included the HAM-A total score and CGI-Severity and Improvement scores.Results:The mean Week 1 HAM-A change score was similar for a starting dose of 200 mg/d with no titration (-8.24) when compared to patients who started on 200 mg/d and then titrated up to 400 mg/d on Day 4 (-8.64). The mean Week 1 HAM-A change score was somewhat higher for patients started on 300 mg/d, and then titrated to 450 mg/d on Day 4/5 (-8.84) when compared to patients started on a lower (100/150 mg/d) dose and titrated on Day 5 to 400/450 mg/d (-7.32). Starting on a dose of 300 mg/d with no titration resulted in an intermediate Week 1 change score (-7.87). The interaction of starting dose and titration schedule with baseline anxiety severity will be summarized in detail.Conclusion:The initial dose of pregabalin appears to have only a weak effect on the speed of onset of anxiolytic improvement.

scholarly journals Comparação dos instrumentos Childhood Autism Rating Scale e Autism Behavior Checklist na identificação e caracterização de indivíduos com distúrbios do espectro autístico

2012 ◽  
Vol 24 (1) ◽  
pp. 104-106 ◽  
Author(s):  
Thaís Helena Ferreira Santos ◽  
Milene Rossi Pereira Barbosa ◽  
Ana Gabriela Lopes Pimentel ◽  
Camila Andrioli Lacerda ◽  
Juliana Izidro Balestro ◽  
...  
Keyword(s):  
Rating Scale ◽  
Childhood Autism ◽  
Childhood Autism Rating Scale ◽  
Autism Behavior Checklist ◽  
Autism Behavior

OBJETIVO: Comparar as respostas dos instrumentos Childhood Autism Rating Scale e Autism Behavior Checklist na identificação e caracterização de indivíduos com Distúrbios do Espectro Autístico. MÉTODOS: Participaram 28 indivíduos que estavam em atendimento fonoaudiológico e possuíam diagnósticos inseridos no Espectro do Autismo. Todos foram avaliados por meio dos instrumentos Autism Behavior Checklist e Childhood Autism Rating Scale a partir de informações obtidas, respectivamente, com pais e terapeutas. Os dados foram analisados estatisticamente em relação à concordância das respostas obtidas. Foram considerados concordantes os resultados de alta ou moderada probabilidade para autismo no Autism Behavior Checklist e com autismo leve-moderado ou grave na Childhood Autism Rating Scale, e respostas de baixa probabilidade no Autism Behavior Checklist e sem autismo na Childhood Autism Rating Scale. RESULTADOS: Houve concordância na maior parte das respostas obtidas. Casos em que houve discordância entre os resultados obtidos a partir dos protocolos corroboram dados da literatura, evidenciando que os instrumentos podem não ser suficientes, quando aplicados isoladamente para a definição do diagnóstico. CONCLUSÃO: Enquanto a Childhood Autism Rating Scale pode não diagnosticar crianças efetivamente autistas, o Autism Behavior Checklist pode incluir como autistas, crianças com outros distúrbios. Portanto, recomenda-se o uso complementar dos dois instrumentos.

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