In:
Annals of Neurology, Wiley, Vol. 90, No. 1 ( 2021-07), p. 62-75
Kurzfassung:
This multilanguage study used simple speech recording and high‐end pattern analysis to provide sensitive and reliable noninvasive biomarkers of prodromal versus manifest α‐synucleinopathy in patients with idiopathic rapid eye movement sleep behavior disorder (iRBD) and early‐stage Parkinson disease (PD). Methods We performed a multicenter study across the Czech, English, German, French, and Italian languages at 7 centers in Europe and North America. A total of 448 participants (337 males), including 150 with iRBD (mean duration of iRBD across language groups 0.5–3.4 years), 149 with PD (mean duration of disease across language groups 1.7–2.5 years), and 149 healthy controls were recorded; 350 of the participants completed the 12‐month follow‐up. We developed a fully automated acoustic quantitative assessment approach for the 7 distinctive patterns of hypokinetic dysarthria. Results No differences in language that impacted clinical parkinsonian phenotypes were found. Compared with the controls, we found significant abnormalities of an overall acoustic speech severity measure via composite dysarthria index for both iRBD ( p = 0.002) and PD ( p 〈 0.001). However, only PD ( p 〈 0.001) was perceptually distinct in a blinded subjective analysis. We found significant group differences between PD and controls for monopitch ( p 〈 0.001), prolonged pauses ( p 〈 0.001), and imprecise consonants ( p = 0.03); only monopitch was able to differentiate iRBD patients from controls ( p = 0.004). At the 12‐month follow‐up, a slight progression of overall acoustic speech impairment was noted for the iRBD ( p = 0.04) and PD ( p = 0.03) groups. Interpretation Automated speech analysis might provide a useful additional biomarker of parkinsonism for the assessment of disease progression and therapeutic interventions. ANN NEUROL 2021;90:62–75
Materialart:
Online-Ressource
ISSN:
0364-5134
,
1531-8249
Sprache:
Englisch
Verlag:
Wiley
Publikationsdatum:
2021
ZDB Id:
2037912-2
