Montreal Cognitive Assessment for the screening and prediction of cognitive decline in early Parkinson's disease

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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.

Introduction

Mild cognitive impairment in Parkinson Disease (PD-MCI) and dementia (PDD) are highly prevalent and contribute significantly to poor quality of life in PD [1], [2]. There is growing evidence to demonstrate that even in early PD, there is a high prevalence of cognitive impairment [3], [4], [5]. The prevalence of cognitive impairment in early PD has been reported to be as high as 38.2% [4]. It is thus essential that clinicians routinely screen for and manage cognitive impairment in early PD. Its significance has been highlighted by various studies and by the Movement Disorders Society (MDS) Task Force on PD-MCI [4]. Risk factors for cognitive impairment in PD include older age, lower education, worse motor scores, rigidity, postural instability, increased daytime somnolence, and cerebral white matter disease [3], [6], [7], [8], [9].

Cognitive impairment in PD typically involves multiple domains including episodic memory, executive function, working memory/attention, visuospatial function and psychomotor speed [5], [9], [10], [11], [12], [13], [14]. Thorough evaluation of these various domains would require comprehensive neuropsychological evaluations as suggested by the MDS taskforce [15]. However in a routine clinical practice, due to time and manpower constraints, it is often not feasible to perform comprehensive neuropsychological evaluations. In these situations, the availability of short, simple and reliable cognitive screening instruments would allow clinicians to screen for cognitive impairment and initiate early pharmacological and non-pharmacological management. Several screening tests including the mini mental state examination (MMSE) and Montreal Cognitive Evaluation (MOCA) have been reported to be useful for this purpose. The Montreal Cognitive Assessment (MoCA) [16] has been previously described as a useful screening tool in PD with good discriminant validity [17], [18], good inter-rater and intra-rater reliability [19], good correlation with a neuropsychological battery [19], and has no ceiling effect, unlike the MMSE [20], [21].

Studies thus far describing the usefulness of the MOCA have been largely cross sectional in nature and the utility of the MOCA in predicting longitudinal cognitive decline has not been fully evaluated. The few longitudinal studies investigating the usefulness of the MoCA, were limited by either lack of clinical diagnosis or by lack of neuropsychological evaluations [22], [23].

To study the effectiveness of the MOCA for the screening of PD-MCI and in predicting longitudinal cognitive decline in early PD, we performed a prospective longitudinal study of patients with mild PD, supported by clinical evaluation and comprehensive neuropsychological assessment. We hypothesized that the MOCA will be effective as a screening tool for PD-MCI and will also be able to predict cognitive decline in early PD.

Section snippets

Study participants

Patients with mild PD presenting at a tertiary neurology centre were prospectively recruited from August 2011 to March 2012. The diagnosis of PD was made by neurologists trained in movement disorders according to the National Institute of Neurological Disorders and Stroke (NINDS) criteria [24]. Only patients with mild PD, having a Hoehn & Yahr (H&Y) stage <3 were recruited. Patients with serious medical and psychiatric co-morbidities were excluded. This study was approved by the institutional

Cross sectional analyses

A total of 95 patients were studied. The mean age was 66.37 (SD, 7.86), mean duration of PD was 5.29 years (SD, 3.91) and mean H&Y score was 1.99 (SD, 0.45). At baseline, 34 participants fulfilled the MDS Level 2 criteria for PD-MCI. The remaining 61 were classified as PD-NCI. PD-MCI patients were significantly older and less educated compared to PD-NCI patients (Table 1). There were no significant differences in gender, race and duration of PD. On cognitive testing, PD-MCI patients did

Discussion

The principal finding of this study is the predictive utility of the MoCA in determining longitudinal progression of cognitive impairment among patients with early PD. Against the MMSE, the MoCA was able to discriminate patients at risk of future cognitive decline based on their initial cognitive testing. A MoCA score of ≤26 translates to an increased risk of progressing from PD-NCI to PD-MCI and from PD-MCI to PDD. In addition, the cross sectional findings of this study add to the literature,

Contributorship

  • Nagaendran Kandiah contributed to the design of the study, statistical analysis, interpretation of the data, and drafting of the manuscript.

  • Angeline Zhang contributed to statistical analysis, interpretation of the data, and revising the manuscript for intellectual content.

  • Alvin Rae Cenina contributed to statistical analysis, interpretation of the data, and revising the manuscript for intellectual content.

  • Wing Lok Au contributed to the design of the study, analysis, interpretation of the data,

Disclosures

Nagaendran Kandiah has received honorarium and CME sponsorship from Lundbeck, Novartis, Pfeizer and Eisai. He has also received research funding from Singhealth Foundation, Media Development Authority of Singapore and the National Medical Research Council of Singapore.

Angeline Zhang reports no disclosures.

Alvin Rae Cenina reports no disclosures.

Wing Lok Au reports no disclosures.

Nivedita Nadkarni reports no disclosures.

Louis CS Tan has received research support from Singapore Millenium

Funding

This research was supported by the Singapore National Research Foundation and was administered by the Singapore Ministry of Health's National Medical Research Council.

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