Evaluation of a structured screening assessment to detect patients with isolated REM Sleep Behavior Disorder
Seger, A.; Ophey, A.; Heitzmann, W.; Doppler, C. E.; Lindner, M.-S.; Brune, C.; Kickart, J.; Dafsari, H. S.; Oertel, W. H.; Fink, G. R.; Jost, S. T.; Sommerauer, M.
Show abstract
BackgroundIsolated rapid eye movement (REM) sleep behavior disorder (iRBD) cohorts have provided novel insights in the earliest neurodegenerative processes in -synucleinopathies. Even though polysomnography remains the gold standard for diagnosis, an accurate questionnaire-based algorithm to identify eligible subjects could facilitate efficient recruitment in research. ObjectivesThis study aimed to optimize the identification of subjects with iRBD from the general population. MethodsBetween June 2020 and July 2021, we placed newspaper advertisements including the single-question screen for RBD (RBD1Q). Participants evaluations included a structured telephone screening consisting of the RBD screening questionnaire (RBDSQ) and additional sleep-related questionnaires. We examined anamnestic information predicting polysomnography-proven iRBD using logistic regressions and receiver operating characteristic curves. Results543 participants answered the advertisements and 185 subjects fulfilling in- and exclusion criteria were screened. Of these, 124 received polysomnography after expert selection and 78 (62.9%) were diagnosed with iRBD. Selected items of the RBDSQ, the Pittsburgh Sleep Quality Index, the STOP-Bang questionnaire, and age predicted iRBD with high accuracy in a multiple logistic regression model (area under the curve >80%). Comparing the algorithm to the sleep expert decision, 77 instead of 124 polysomnographies (62.1%) would have been carried out, while 63 (80.8%) of iRBD patients would have been identified. 32 of 46 (69.6%) unnecessary polysomnography examinations could have been avoided. ConclusionsOur proposed algorithm displayed high diagnostic accuracy for polysomnography-proven iRBD in a cost-effective manner and may be a convenient tool for application in research and clinical settings. External validation sets are warranted to prove its reliability.
Matching journals
The top 5 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Association of sleep abnormalities in older adults with risk of developing Parkinson’s disease 97%
- Wake and non-rapid eye movement sleep dysfunction is associated with colonic neuropathology in Parkinson’s disease 97%
- EEG-based Machine Learning Models for the Prediction of Phenoconversion Time and Subtype in iRBD 95%
Similar papers in this journal
- Ambulatory detection of isolated REM sleep behavior disorder combining actigraphy and questionnaire 98%
- A comprehensive analysis of dominant and recessive parkinsonism genes in REM sleep behavior disorder 94%
- The non-coding GBA1 rs3115534 variant is associated with REM sleep behavior disorder in Nigerians 92%
Similar papers in this journal
- RBDAct: Home screening of REM sleep behaviour disorder based on wrist actigraphy in Parkinson’s patients 96%
- Age-related differences in the association between REM sleep and the polygenic risk for Parkinson's disease 94%
- α4β2 * Nicotinic Cholinergic Receptor Target Engagement in Parkinson Disease Gait-Balance Disorders 91%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.