Anahid Hekmat
Clinical Assistant Professor, Psychiatry and Behavioral Sciences - Sleep Medicine
Clinical Focus
- Sleep Medicine
Academic Appointments
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Clinical Assistant Professor, Psychiatry and Behavioral Sciences - Sleep Medicine
Professional Education
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Board Certification: American Board of Psychiatry and Neurology, Sleep Medicine (2015)
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Fellowship: Stanford University Sleep Medicine Fellowship (2014) CA
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Board Certification: American Board of Psychiatry and Neurology, Clinical Neurophysiology (2013)
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Fellowship: Rush University Clinical Neurophysiology Fellowship (2012) IL
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Board Certification: American Board of Psychiatry and Neurology, Neurology (2011)
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Residency: Rush University Medical Center Neurology Residency (2011) IL
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Internship: University of Arkansas Internal Medicine (2009) AR
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Medical Education: Shahid Beheshti University of Medical Sciences (2003) Iran
All Publications
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Ambulatory Detection of Isolated Rapid-Eye-Movement Sleep Behavior Disorder Combining Actigraphy and Questionnaire.
Movement disorders : official journal of the Movement Disorder Society
2022
Abstract
BACKGROUND: Isolated rapid-eye-movement sleep behavior disorder (iRBD) is in most cases a prodrome of neurodegenerative synucleinopathies, affecting 1% to 2% of middle-aged and older adults; however, accurate ambulatory diagnostic methods are not available. Questionnaires lack specificity in nonclinical populations. Wrist actigraphy can detect characteristic features in individuals with RBD; however, high-frequency actigraphy has been rarely used.OBJECTIVE: The aim was to develop a machine learning classifier using high-frequency (1-second resolution) actigraphy and a short patient survey for detecting iRBD with high accuracy and precision.METHODS: The method involved analysis of home actigraphy data (for seven nights and more) and a nine-item questionnaire (RBD Innsbruck inventory and three synucleinopathy prodromes of subjective hyposmia, constipation, and orthostatic dizziness) in a data set comprising 42 patients with iRBD, 21 sleep clinic patients with other sleep disorders, and 21 community controls.RESULTS: The actigraphy classifier achieved 95.2% (95% confidence interval [CI]: 88.3-98.7) sensitivity and 90.9% (95% CI: 82.1-95.8) precision. The questionnaire classifier achieved 90.6% accuracy and 92.7% precision, exceeding the performance of the Innsbruck RBD Inventory and prodromal questionnaire alone. Concordant predictions between actigraphy and questionnaire reached a specificity and precision of 100% (95% CI: 95.7-100.0) with 88.1% sensitivity (95% CI: 79.2-94.1) and outperformed any combination of actigraphy and a single question on RBD or prodromal symptoms.CONCLUSIONS: Actigraphy detected iRBD with high accuracy in a mixed clinical and community cohort. This cost-effective fully remote procedure can be used to diagnose iRBD in specialty outpatient settings and has potential for large-scale screening of iRBD in the general population. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
View details for DOI 10.1002/mds.29249
View details for PubMedID 36258659
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SLEEP-RELATED HICCUPS: A CASE REPORT OF ANTIDEPRESSANT ASSOCIATED HYPNIC JERKS
OXFORD UNIV PRESS INC. 2022: A350
View details for Web of Science ID 000838094800802
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AT-HOME DETECTION OF REM SLEEP BEHAVIOR DISORDER USING A MACHINE LEARNING APPROACH AND WRIST ACTIGRAPHY
OXFORD UNIV PRESS INC. 2022: A243-A244
View details for Web of Science ID 000838094800549
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Five-Minute Awake Snoring Test for Determining CPAP Pressures (Five-Minute CPAP Test): A Pilot Study
Sleep Disorders
2016; 2016: 8
View details for DOI 10.1155/2016/7380874