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Simultaneous tonic and phasic REM sleep without atonia best predicts early phenoconversion to neurodegenerative disease in idiopathic REM sleep behavior disorder

Publikace na 1. lékařská fakulta |
2019

Tento text není v aktuálním jazyce dostupný. Zobrazuje se verze "en".Abstrakt

Study Objectives: Rapid eye movement (REM) sleep without atonia (RWA) is the main polysomnographic feature of idiopathic REM sleep behavior disorder (iRBD) and is considered to be a promising biomarker predicting conversion to manifested synucleinopathy. Besides conventionally evaluated tonic, phasic and any RWA, we took into consideration also periods, when phasic and tonic RWA appeared simultaneously and we called this activity "mixed RWA." The study aimed to evaluate different types of RWA, to reveal the most relevant biomarker to the conversion.

Methods: A total of 55 patients with confirmed iRBD were recruited with mean follow-up duration 2.3 +/- 0.7 years. Scoring of RWA was based on Sleep Innsbruck Barcelona rules.

Positive phenocoversion was ascertained according to standard diagnostic criteria during follow-up. Receiver operator characteristic analysis was applied to evaluate predictive performance of different RWA types.

Results: A total of nine patients (16%) developed neurodegenerative diseases. Yearly phenoconversion rate was 5.5%.

Significantly higher amounts of mixed (p = 0.009), tonic (p = 0.020), and any RWA (p = 0.049) were found in converters. Optimal cutoffs differentiating the prediction were 16.4% (sensitivity 88.9; specificity 69.6) for tonic, 4.4% (sensitivity 88.9; specificity 60.9) for mixed, and 36.8% (sensitivity 77.8; specificity 65.2) for any RWA.

With area under the curve (AUC) 0.778, mixed RWA has proven to be the best predictive test followed by tonic (AUC 0.749) and any (AUC 0.710). Conclusions: Mixed, tonic and any RWA may serve as biomarkers predicting the conversion into neurodegenerative disease in iRBD.

The best predictive value lies within mixed RWA, thus it should be considered as standard biomarker.