title: Montreal Cognitive Assessment for the screening and prediction of cognitive decline in early Parkinson's disease.
abstract: BACKGROUND
  Early diagnosis of cognitive impairment in PD would allow appropriate monitoring and timely intervention to reduce the progression to dementia (PDD).
  
  
  OBJECTIVE
  To study the usefulness of the Montreal Cognitive Assessment (MoCA) in the screening for mild cognitive impairment (PD-MCI) and its predictive utility in determining longitudinal cognitive decline in PD.
  
  
  METHODS
  Prospective longitudinal study of patients with mild PD. PD-MCI and PDD was diagnosed based on the Movement Disorder taskforce (MDS) criteria. Receiver Operating Characteristic analyses and Cox regression analyses were performed.
  
  
  RESULTS
  95 patients; mean age 66.37 (SD 7.86); mean H&Y score of 1.99 (SD 0.45) were studied. At baseline, 34 patients fulfilled the MDS criteria for PD-MCI. MoCA, compared to the MMSE had a high discriminatory power in detecting PD-MCI [Area Under Curve (AUC) of 0.912, p < 0.001]. A MoCA score of ≤26 provided a sensitivity of 93.1% for the diagnosis of PD-MCI. In the longitudinal cohort over 2 years, baseline MOCA was useful in predicting cognitive decline (AUC of 0.707, p = 0.05). With Cox regression analyses, a 1-point lower score on baseline MoCA was associated with a 34% increased risk of cognitive decline [Hazard ratio (HR) 1.34; 95% CI: 1.03-1.74: p = 0.029]. A baseline MoCA ≤26 was highly predictive of progressive cognitive decline (HR 3.47, 95% CI: 2.38-5.07; p < 0.01).
  
  
  CONCLUSIONS
  MoCA is a reliable tool in predicting cognitive decline in early PD. A MoCA score of ≤26 significantly increases the risk for progressive cognitive decline.
authors.affiliation: Department of Neurology, National Neuroscience Institute, Singapore; Duke-NUS, Graduate Medical School, Singapore. Electronic address: Nagaendran_Kandiah@nni.com.sg.
authors.forename: Nagaendran
authors.initials: N
authors.lastname: Kandiah
authors.affiliation: Department of Neurology, National Neuroscience Institute, Singapore.
authors.forename: Angeline
authors.initials: A
authors.lastname: Zhang
authors.affiliation: Department of Neurology, National Neuroscience Institute, Singapore.
authors.forename: Alvin Rae
authors.initials: AR
authors.lastname: Cenina
authors.affiliation: Department of Neurology, National Neuroscience Institute, Singapore; Duke-NUS, Graduate Medical School, Singapore.
authors.forename: Wing Lok
authors.initials: WL
authors.lastname: Au
authors.affiliation: Centre for Quantitative Medicine, Duke-NUS, Singapore.
authors.forename: Nivedita
authors.initials: N
authors.lastname: Nadkarni
authors.affiliation: Department of Neurology, National Neuroscience Institute, Singapore; Duke-NUS, Graduate Medical School, Singapore.
authors.forename: Louis Cs
authors.initials: LC
authors.lastname: Tan
mesh_terms: D000368:Aged; D003072:Cognition Disorders / Q000175:diagnosis* / Q000209:etiology*; D003430:Cross-Sectional Studies; D005260:Female; D006801:Humans; D008137:Longitudinal Studies; D008297:Male; D008403:Mass Screening; D008875:Middle Aged; D009483:Neuropsychological Tests; D010300:Parkinson Disease / Q000150:complications*; D011237:Predictive Value of Tests; D012372:ROC Curve; D012680:Sensitivity and Specificity
keywords: Cognitive functions; Dementia; Parkinson's disease