Loneliness, social isolation, and effects on cognitive decline in patients with dementia: A retrospective cohort study using natural language processing.
James A C Myers, Tom Stafford, Ivan Koychev, Robert Perneczky, Oliver Bandmann, Nemanja Vaci
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引用次数: 0
Abstract
Introduction: The study aimed to compare cognitive trajectories between patients with reports of social isolation and loneliness and those without.
Methods: Reports of social isolation, loneliness, and Montreal Cognitive Assessment (MoCA) scores were extracted from dementia patients' medical records using natural language processing models and analyed using mixed-effects models.
Results: Lonely patients (n = 382), compared to controls (n = 3912), showed an average MoCA score that was 0.83 points lower at diagnosis (P = 0.008) and throughout the disease. Socially isolated patients (n = 523) experienced a 0.21 MoCA point per year faster rate of cognitive decline in the 6 months before diagnosis (P = 0.029), but were comparable to controls before this period. This led to average MoCA scores that were 0.69 MoCA points lower at diagnosis (P = 0.011).
Discussion: Lower cognitive levels in lonely and socially isolated patients suggest that these factors may contribute to dementia progression.
Highlights: Developed Natural Language Processing model to detect social isolation and loneliness in electronic health records.Patients with loneliness reports have lower Montreal Cognitive Assessment (MoCA) scores than other patients.Social isolation was related to the faster decline in MoCA scores before diagnosis.Social isolation and loneliness are promising targets for slowing cognitive decline.
期刊介绍：
Alzheimer''s & Dementia: Diagnosis, Assessment & Disease Monitoring (DADM) is an open access, peer-reviewed, journal from the Alzheimer''s Association® that will publish new research that reports the discovery, development and validation of instruments, technologies, algorithms, and innovative processes. Papers will cover a range of topics interested in the early and accurate detection of individuals with memory complaints and/or among asymptomatic individuals at elevated risk for various forms of memory disorders. The expectation for published papers will be to translate fundamental knowledge about the neurobiology of the disease into practical reports that describe both the conceptual and methodological aspects of the submitted scientific inquiry. Published topics will explore the development of biomarkers, surrogate markers, and conceptual/methodological challenges. Publication priority will be given to papers that 1) describe putative surrogate markers that accurately track disease progression, 2) biomarkers that fulfill international regulatory requirements, 3) reports from large, well-characterized population-based cohorts that comprise the heterogeneity and diversity of asymptomatic individuals and 4) algorithmic development that considers multi-marker arrays (e.g., integrated-omics, genetics, biofluids, imaging, etc.) and advanced computational analytics and technologies.
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