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.

• Klíčová slova
• Parkinson's disease, clinimetric, cognitive, dementia, neuropsychology, rating scales, test,
• MeSH
• jazyk (prostředek komunikace) * MeSH
• kognitivní dysfunkce * diagnóza   etiologie   MeSH
• lidé MeSH
• neuropsychologické testy * normy   MeSH
• paměť * fyziologie   MeSH
• Parkinsonova nemoc * komplikace   MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• systematický přehled 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.

• Publikační typ
• časopisecké články MeSH

BACKGROUND AND OBJECTIVES: The impact of dopaminergic medication on language in Parkinson's disease (PD) remains poorly understood. This observational, naturalistic study aimed to investigate the effects of long-term dopaminergic therapy on language performance in patients with de-novo PD based on a high-level linguistic analysis of natural spontaneous discourse. METHODS: A fairy-tale narration was recorded at baseline and a 12-month follow-up. The speech samples were automatically analyzed using six representative lexical and syntactic features based on automatic speech recognition and natural language processing. RESULTS: We enrolled 109 de-novo PD patients compared to 68 healthy controls. All subjects completed the 12-month follow-up; 92 PD patients were on stable dopaminergic medication (PD-treated), while 17 PD patients remained without medication (PD-untreated). At baseline, the PD-treated group exhibited abnormalities in syntactic domains, particularly in sentence length (p = 0.018) and sentence development (p = 0.042) compared to healthy controls. After 12 months of dopaminergic therapy, PD-treated showed improvements in the syntactic domain, including sentence length (p = 0.012) and sentence development (p = 0.030). Of all PD-treated patients, 37 were on monotherapy with dopamine agonists and manifested improvement in sentence length (p = 0.048), while 32 were on monotherapy with levodopa and had no language amelioration. No changes in language parameters over time were seen in both the PD-untreated group and healthy controls. DISCUSSION: Initiation of dopaminergic therapy improved high-language syntactic deficits in de-novo PD, confirming the role of dopamine in cognitive-linguistic processing. Automated linguistic analysis of spontaneous speech via natural language processing can assist in improving the prediction and management of language deficits in PD.

• Klíčová slova
• Discourse, Levodopa, Linguistic analysis, Natural language processing, Speech,
• MeSH
• agonisté dopaminu * terapeutické užití   MeSH
• antiparkinsonika * terapeutické užití   MeSH
• dopaminové látky * terapeutické užití   MeSH
• lidé středního věku MeSH
• lidé MeSH
• následné studie MeSH
• Parkinsonova nemoc * farmakoterapie   komplikace   MeSH
• řeč * účinky léků   MeSH
• senioři MeSH
• výsledek terapie MeSH
• Check Tag
• lidé středního věku MeSH
• lidé MeSH
• mužské pohlaví MeSH
• senioři MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• pozorovací studie MeSH
• Názvy látek
• agonisté dopaminu * MeSH
• antiparkinsonika * MeSH
• dopaminové látky * MeSH

BACKGROUND AND OBJECTIVES: Patients with synucleinopathies such as multiple system atrophy (MSA) and Parkinson's disease (PD) frequently display speech and language abnormalities. We explore the diagnostic potential of automated linguistic analysis of natural spontaneous speech to differentiate MSA and PD. METHODS: Spontaneous speech of 39 participants with MSA compared to 39 drug-naive PD and 39 healthy controls matched for age and sex was transcribed and linguistically annotated using automatic speech recognition and natural language processing. A quantitative analysis was performed using 6 lexical and syntactic and 2 acoustic features. Results were compared with human-controlled analysis to assess the robustness of the approach. Diagnostic accuracy was evaluated using sensitivity analysis. RESULTS: Despite similar disease duration, linguistic abnormalities were generally more severe in MSA than in PD, leading to high diagnostic accuracy with an area under the curve of 0.81. Compared to controls, MSA showed decreased grammatical component usage, more repetitive phrases, shorter sentences, reduced sentence development, slower articulation rate, and increased duration of pauses, whereas PD had only shorter sentences, reduced sentence development, and longer pauses. Only slower articulation rate was distinctive for MSA while unchanged for PD relative to controls. The highest correlation was found between bulbar/pseudobulbar clinical score and sentence length (r = -0.49, p = 0.002). Despite the relatively high severity of dysarthria in MSA, a strong agreement between manually and automatically computed results was achieved. DISCUSSION: Automated linguistic analysis may offer an objective, cost-effective, and widely applicable biomarker to differentiate synucleinopathies with similar clinical manifestations.

• Klíčová slova
• Automated linguistic analysis, Language, Multiple system atrophy, Natural language processing, Spontaneous discourse,
• MeSH
• diferenciální diagnóza MeSH
• lidé středního věku MeSH
• lidé MeSH
• multisystémová atrofie * diagnóza   komplikace   MeSH
• Parkinsonova nemoc * diagnóza   komplikace   MeSH
• senioři MeSH
• zpracování přirozeného jazyka * MeSH
• Check Tag
• lidé středního věku MeSH
• lidé MeSH
• mužské pohlaví MeSH
• senioři MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH