Identifying parkinsonism in mild cognitive impairment.
J Neurol Sci
; 458: 122941, 2024 Mar 15.
Article
en En
| MEDLINE
| ID: mdl-38422782
ABSTRACT
INTRODUCTION:
Clinical parkinsonism is a core diagnostic feature for mild cognitive impairment with Lewy bodies (MCI-LB) but can be challenging to identify. A five-item scale derived from the Unified Parkinson's Disease Rating Scale (UPDRS) has been recommended for the assessment of parkinsonism in dementia. This study aimed to determine whether the five-item scale is effective to identify parkinsonism in MCI.METHODS:
Participants with MCI from two cohorts (n = 146) had a physical examination including the UPDRS and [123I]-FP-CIT SPECT striatal dopaminergic imaging. Participants were classified as having clinical parkinsonism (P+) or no parkinsonism (P-), and with abnormal striatal dopaminergic imaging (D+) or normal imaging (D-). The five-item scale was the sum of UPDRS tremor at rest, bradykinesia, action tremor, facial expression, and rigidity scores. The ability of the scale to differentiate P+D+ and P-D- participants was examined.RESULTS:
The five-item scale had an AUROC of 0.92 in Cohort 1, but the 7/8 cut-off defined for dementia had low sensitivity to identify P+D+ participants (sensitivity 25%, specificity 100%). Optimal sensitivity and specificity was obtained at a 3/4 cut-off (sensitivity 83%, specificity 88%). In Cohort 2, the five-item scale had an AUROC of 0.97, and the 3/4 cut-off derived from Cohort 1 showed sensitivity of 100% and a specificity of 82% to differentiate P+D+ from P-D- participants. The five-item scale was not effective in differentiating D+ from D- participants.CONCLUSIONS:
The five-item scale is effective to identify parkinsonism in MCI, but a lower threshold must be used in MCI compared with dementia.Palabras clave
Texto completo:
1
Colección:
01-internacional
Banco de datos:
MEDLINE
Asunto principal:
Trastornos Parkinsonianos
/
Enfermedad por Cuerpos de Lewy
/
Enfermedad de Alzheimer
/
Disfunción Cognitiva
Límite:
Humans
Idioma:
En
Revista:
J Neurol Sci
Año:
2024
Tipo del documento:
Article