Objective: This study distilled patterns of patient performance recognized by clinical professionals in people with Parkinson’s disease (PD) and cognitive impairment on the Montreal Cognitive Assessment (MoCA) and their health data to reveal diagnostically relevant disease stratifications overlooked by the current MoCA scoring method.

Background: PD is the second most common neurodegenerative disorder in North America, and the prevalence rate is increasing [1]. The motor movement complications from PD are well characterized, but the cognitive impairment spectrum of mild or minor (PD-MCI) to major (PDD) is highly heterogeneous between individuals, making it difficult to detect and categorize. It is well known that PD-MCI reduces patient quality of life and is a risk factor for developing PDD and early mortality [2]. Therefore, it is vital to continue investigating new methods to improve the accuracy and early detection tools for cognitive impairment in PD.

Method: This retrospective analysis collected and de-identified nine MoCA exams and neuropsychological reports containing the health information of patients with PD-MCI and PDD [figure 1]. We conducted 60-minute semi-structured interviews with six clinical neurologists and neuropsychologists specializing in movement disorders or geriatrics using the think aloud protocol [3]. This interview technique required the interviewee to speak aloud their thoughts as they reviewed the documents for the nine model patients. Interviews were then coded using iterative coding methods to extract individual features of importance emphasized by the interviewees as diagnostically significant. These features were then grouped into distinct patterns of cognitive impairment in PD based on consensus between all interview coders.

Results: Three distinct patterns were composed of key features identified by clinical professionals during their review of the retrospective data from a completed MoCA and a neuropsychological report containing health data [table 1].

Conclusion: Leveraging clinical expertise and the inherent human capacity for pattern recognition may provide new insights into the heterogenous etiology across the cognitive impairment spectrum in PD. Our explorative study distilled distinct patterns of patient performance on the MoCA and health features to reveal important patterns in the cognitive impairment spectrum in PD currently unexplored.

Figure 1

Table 1

References: 1. Willis AW, Roberts E, Beck JC, et al. Incidence of Parkinson disease in North America. npj Parkinson’s Disease Nature Research, 2022; 8(1)Published online: December 1, 2022.doi:10.1038/s41531-022-00410-y.
2. Baiano C, Barone P, Trojano L, Santangelo G. Prevalence and clinical aspects of mild cognitive impairment in Parkinson’s disease: A meta-analysis. Movement Disorders John Wiley and Sons Inc., 2020; 35(1): 45–54.
3. Harold C. Sox, Michael C. Higgins, Douglas K. Owens. Differential Diagnosis. Medical Decision Making. Second. Chichester, UK: John Wiley & Sons, Ltd, 2013, pp. 7–26.

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MDS Abstracts - https://www.mdsabstracts.org/abstract/a-qualitative-approach-to-extract-diagnostic-patterns-of-cognitive-impairment-in-parkinsons-disease/