Detail publikace

Speech prosody impairment predicts cognitive decline in Parkinson’s disease

Originální název

Speech prosody impairment predicts cognitive decline in Parkinson’s disease

Anglický název

Speech prosody impairment predicts cognitive decline in Parkinson’s disease

Jazyk

en

Originální abstrakt

Background Impairment of speech prosody is characteristic for Parkinson’s disease (PD) and does not respond well to dopaminergic treatment. Objectives We assessed whether baseline acoustic parameters, alone or in combination with other predominantly non-dopaminergic symptoms may predict global cognitive decline as measured by the Addenbrooke’s cognitive examination (ACE-R) and/or worsening of cognitive status as assessed by a detailed neuropsychological examination. Methods Forty-four consecutive non-depressed PD patients underwent clinical and cognitive testing, and acoustic voice analysis at baseline and at the two-year follow-up. Influence of speech and other clinical parameters on worsening of the ACE-R and of the cognitive status was analyzed using linear and logistic regression. Results The cognitive status (classified as normal cognition, mild cognitive impairment and dementia) deteriorated in 25% of patients during the follow-up. The multivariate linear regression model consisted of the variation in range of the fundamental voice frequency (F0VR) and the REM Sleep Behavioral Disorder Screening Questionnaire (RBDSQ). These parameters explained 37.2% of the variability of the change in ACE-R. The most significant predictors in the univariate logistic regression were the speech index of rhythmicity (SPIR; p = 0.012), disease duration (p = 0.019), and the RBDSQ (p = 0.032). The multivariate regression analysis revealed that SPIR alone led to 73.2% accuracy in predicting a change in cognitive status. Combining SPIR with RBDSQ improved the prediction accuracy of SPIR alone by 7.3%. Conclusions Impairment of speech prosody together with symptoms of RBD predicted rapid cognitive decline and worsening of PD cognitive status during a two-year period.

Anglický abstrakt

Background Impairment of speech prosody is characteristic for Parkinson’s disease (PD) and does not respond well to dopaminergic treatment. Objectives We assessed whether baseline acoustic parameters, alone or in combination with other predominantly non-dopaminergic symptoms may predict global cognitive decline as measured by the Addenbrooke’s cognitive examination (ACE-R) and/or worsening of cognitive status as assessed by a detailed neuropsychological examination. Methods Forty-four consecutive non-depressed PD patients underwent clinical and cognitive testing, and acoustic voice analysis at baseline and at the two-year follow-up. Influence of speech and other clinical parameters on worsening of the ACE-R and of the cognitive status was analyzed using linear and logistic regression. Results The cognitive status (classified as normal cognition, mild cognitive impairment and dementia) deteriorated in 25% of patients during the follow-up. The multivariate linear regression model consisted of the variation in range of the fundamental voice frequency (F0VR) and the REM Sleep Behavioral Disorder Screening Questionnaire (RBDSQ). These parameters explained 37.2% of the variability of the change in ACE-R. The most significant predictors in the univariate logistic regression were the speech index of rhythmicity (SPIR; p = 0.012), disease duration (p = 0.019), and the RBDSQ (p = 0.032). The multivariate regression analysis revealed that SPIR alone led to 73.2% accuracy in predicting a change in cognitive status. Combining SPIR with RBDSQ improved the prediction accuracy of SPIR alone by 7.3%. Conclusions Impairment of speech prosody together with symptoms of RBD predicted rapid cognitive decline and worsening of PD cognitive status during a two-year period.

BibTex


@article{BUT125730,
  author="Irena {Rektorová} and Jiří {Mekyska} and Eva {Janoušová} and Milena {Košťálová} and Ilona {Eliášová} and Martina {Mračková} and Dagmar {Berankova} and Tereza {Nečasová} and Zdeněk {Smékal} and Radek {Mareček}",
  title="Speech prosody impairment predicts cognitive decline in Parkinson’s disease",
  annote="Background

Impairment of speech prosody is characteristic for Parkinson’s disease (PD) and does not respond well to dopaminergic treatment.



Objectives

We assessed whether baseline acoustic parameters, alone or in combination with other predominantly non-dopaminergic symptoms may predict global cognitive decline as measured by the Addenbrooke’s cognitive examination (ACE-R) and/or worsening of cognitive status as assessed by a detailed neuropsychological examination.



Methods

Forty-four consecutive non-depressed PD patients underwent clinical and cognitive testing, and acoustic voice analysis at baseline and at the two-year follow-up. Influence of speech and other clinical parameters on worsening of the ACE-R and of the cognitive status was analyzed using linear and logistic regression.



Results

The cognitive status (classified as normal cognition, mild cognitive impairment and dementia) deteriorated in 25% of patients during the follow-up. The multivariate linear regression model consisted of the variation in range of the fundamental voice frequency (F0VR) and the REM Sleep Behavioral Disorder Screening Questionnaire (RBDSQ). These parameters explained 37.2% of the variability of the change in ACE-R. The most significant predictors in the univariate logistic regression were the speech index of rhythmicity (SPIR; p = 0.012), disease duration (p = 0.019), and the RBDSQ (p = 0.032). The multivariate regression analysis revealed that SPIR alone led to 73.2% accuracy in predicting a change in cognitive status. Combining SPIR with RBDSQ improved the prediction accuracy of SPIR alone by 7.3%.



Conclusions

Impairment of speech prosody together with symptoms of RBD predicted rapid cognitive decline and worsening of PD cognitive status during a two-year period.

",
  chapter="125730",
  doi="10.1016/j.parkreldis.2016.05.018",
  howpublished="print",
  number="1",
  volume="29",
  year="2016",
  month="august",
  pages="90--95",
  type="journal article"
}