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Predicting DSM-5 ASD Diagnosis Using the Autism Mental Status Exam in an Adult Sample

Thursday, 2 May 2013: 09:00-13:00
Banquet Hall (Kursaal Centre)
D. Grodberg1, P. M. Weinger2, D. B. Halpern3, A. Kolevzon1 and J. D. Buxbaum4, (1)Seaver Autism Center for Research and Treatment, Mount Sinai School of Medicine, New York, NY, (2)Yeshiva University, New York, NY, (3)Seaver Autism Center for Research and Treatment, Icahn School of Medicine at Mount Sinai, New York, NY, (4)Psychiatry, Mount Sinai School of Medicine, New York, NY
Background:  The assessment and diagnosis of Autism Spectrum Disorder (ASD) in adults is unreliable due to  the absence  of a brief observational tool that is validated to the gold standard ASD diagnostic assessment. The wider recognition of ASD in adults reflects clinicians’ increased knowledge as well as a growing availability of evidence-based treatments and research protocols. Yet the diagnosis can be challenging in this underserved and under-studied population. The Autism Mental Status Exam (AMSE) was developed to address the lack of standardized observational assessment for ASD in non-academic settings.  The AMSE is an 8-item diagnostic observational tool that structures the way we observe and record social, communicative and behavioral functioning in people with ASD. Each item is scored on a 0 to 2 scale yielding total scores that range from 0 to 16. Initial validation indicates that the AMSE has excellent inter-rater reliability and classification accuracy when compared to the Autism Diagnostic Observation Schedule (ADOS).

Objectives: To determine sensitivity and specificity of AMSE cutoff scores in predicting independent diagnosis of ASD using proposed DSM-5 criteria. 

Methods:  Forty consecutive subjects age 18-44 received comprehensive diagnostic testing as part of the  assessment protocol at the Seaver Autism Center at  Mount Sinai School of Medicine.  All subjects were referred for suspected ASD. Each subject first received a clinical evaluation by a psychiatrist with expertise in ASD diagnosis during which  the AMSE was administered.   The subject was then administered an ADOS in a different exam room by a site reliable psychologist who was blind to the AMSE score or the psychiatrist’s diagnostic impressions.  When feasible, an ADI-R was also administered. Best Estimate Clinical Diagnosis (BECD) was then ascertained by a psychologist at the center who is research reliable on the ADOS.  BECD protocol involved communication with the ADOS and ADI-R examiners. The BECD clinician remained blind to the psychiatrists’ AMSE scores but was provided clinical notes that were limited to review of symptom domains, current medications, and medical history.  The proposed DSM-5 criteria were then used to guide the BECD clinician’s diagnostic formulation of ASD vs. non-ASD.

Results:  Within this high-risk sample, 52.8% of participants met criteria for a diagnosis of Autism Spectrum Disorder based on research diagnostic instruments (ADOS, ADI) and proposed DSM-5 criteria. Diagnostic accuracy was assessed by the nonparametric measure of area under an ROC curve. The ROC curve analysis was used to determine a criterion cut-off score based on AMSE total scores. Area under the ROC curve was 0.99 (95% confidence interval [CI]: 0.96– 1.0). This indicates that the AMSE was able to differentiate between ASD and non-ASD diagnoses. The most effective cut-off score was estimated at a total score of greater than or equal to 5. This cut-off score produced a sensitivity of 100% and a specificity of 95% in this high-risk population. Total AMSE scores for non-ASD participants ranged from 0 to 5 and total AMSE scores for ASD participants ranged from 5 to 8.

Conclusions:   The AMSE holds promise as a brief diagnostic observational assessment for ASD.

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