BACKGROUND: Cognitive impairment in Parkinson's disease (PD) is a key non-motor complication during the disease course. OBJECTIVES: A review of detailed cognitive instruments to detect mild cognitive impairment (PD-MCI) or dementia (PDD) is needed to establish optimal tests that facilitate diagnostic accuracy. METHODS: We performed a systematic literature review of tests that assess memory, language including premorbid intelligence, and visuospatial domains (for tests of attention and executive functions see accompanying review) to determine suitability to assess cognition in PD. Based on in-depth scrutiny of psychometric and other relevant clinimetric properties, tests were rated as "recommended," "recommended with caveats," "suggested," or "listed" by the International Parkinson and Movement Disorder Society (IPMDS) panel of experts according to the IPMDS Clinical Outcome Assessment Scientific Evaluation Committee guidelines. RESULTS: We included 39 tests encompassing 48 outcome measures. Seven tests (different versions or subtests of the test counted once) were recommended, including four for memory, one for visuospatial domains, one for language (including three measures), and one for estimated premorbid intelligence. Furthermore, 10 tests (12 measures) were "recommended with caveats," 11 were "suggested," and 11 (15 measures) were "listed." CONCLUSIONS: Recommended neuropsychological tests in memory, visuospatial functions, and language are proposed to guide the assessment of cognitive impairment and its progression in PD-MCI and PDD, and for use in clinical trials to stratify participants or as outcome measures. Novel measures being developed will need extensive validation research to be "recommended." © 2025 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

• Keywords
• Parkinson's disease, clinimetric, cognitive, dementia, neuropsychology, rating scales, test,
• MeSH
• Language * MeSH
• Cognitive Dysfunction * diagnosis   etiology   MeSH
• Humans MeSH
• Neuropsychological Tests * standards   MeSH
• Memory * physiology   MeSH
• Parkinson Disease * complications   MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Systematic Review MeSH

Over the past decade, neuropsychiatric fluctuations in Parkinson's disease (PD) have been increasingly recognized for their impact on patients' quality of life. Speech, a complex function carrying motor, emotional, and cognitive information, offers potential insights into these fluctuations. While previous studies have focused on acoustic analysis to assess motor speech disorders reliably, the potential of linguistic patterns associated with neuropsychiatric fluctuations in PD remains unexplored. This study analyzed the content of spontaneous speech from 33 PD patients in ON and OFF medication states, using machine learning and large language models (LLMs) to predict medication states and a neuropsychiatric state score. The top-performing model, the LLM Gemma-2 (9B), achieved 98% accuracy in differentiating ON and OFF states and its predicted scores were highly correlated with actual scores (Spearman's ρ = 0.81). These methods could provide a more comprehensive assessment of PD treatment effects, allowing remote neuropsychiatric symptom monitoring via mobile devices.

• Publication type
• Journal Article MeSH