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A Two-Stage Questionnaire and Actigraphy Screening for iRBD in a Multicenter Retrospective Cohort
Caleb A Massimi1, Giorgio Ricciardiello Mejia1, Andre Metzger1
1Department of Neurology, Icahn School of Medicine, New York, New York, USA.
Objective:
Isolated rapid-eye-movement sleep behavior disorder is a prodromal marker of synucleinopathies. However, most cases remain undiagnosed due to the insufficient predictive value of questionnaires and limited access to confirmatory video-polysomnography. We assessed a two-stage screening strategy combining a brief questionnaire on rapid-eye-movement sleep behavior disorder symptoms and other prodromes with wrist actigraphy across multiple case-control cohorts.
Methods:
Participants aged 40-80 without neurodegenerative disease were recruited from five cohorts; all cases were confirmed by video-polysomnography. The questionnaire was administered to 289 participants, and 236 underwent ≥ 14 nights of home wrist actigraphy. The wearable-based algorithm was built on four movement features (mean motor activity, activity index, short or long immobile bouts, twitch activity). Models were trained with nested cross-validation using XGBoost.
Results:
The full retrospective cohort included 396 participants (99 cases, 297 controls; mean age 64 ± 11; 55% male). The dream enactment question alone achieved an area under the curve of 0.85, which improved to 0.86 using the four-item questionnaire. Actigraphy alone achieved 82% sensitivity and 84% specificity. In the subgroup completing both assessments (75 cases, 54 controls), the two-stage protocol-questionnaire followed by actigraphy-yielded 68% sensitivity and 100% specificity using the dream enactment question alone, and 73% sensitivity and 100% specificity using the four-item questionnaire.
Interpretation:
A two-stage protocol combining questionnaire and actigraphy demonstrated high specificity and good sensitivity for detecting isolated rapid-eye-movement sleep behavior disorder in this multicenter cohort. This low-cost, scalable strategy is compatible with widely used wearable devices and warrants validation in community-based populations.

