Estimation of the epidemiology of dementia and associated neuropsychiatric symptoms by applying machine learning to real-world data
| Autor: | Álvaro Iruin, Ania Gorostiza, Carlos Cernuda, Mikel Tainta, Arantzazu Arrospide, Javier Mar, Lorea Mar-Barrutia, Ane Alberdi, Oliver Ibarrondo, Igor Larrañaga |
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| Rok vydání: | 2021 |
| Předmět: |
Male
medicine.medical_specialty Population Machine Learning 03 medical and health sciences 0302 clinical medicine mental disorders Epidemiology medicine Dementia Humans 030212 general & internal medicine Psychiatry education Retrospective Studies Estimation education.field_of_study business.industry Incidence (epidemiology) Female sex Retrospective cohort study General Medicine medicine.disease Nursing Homes Psychiatry and Mental health Psychotic Disorders Female business Real world data 030217 neurology & neurosurgery |
| Zdroj: | Revista de psiquiatria y salud mental. 15(3) |
| ISSN: | 2173-5050 |
| Popis: | Introduction Incidence rates of dementia-related neuropsychiatric symptoms (NPS) are not known and this hampers the assessment of their population burden. The objective of this study was to obtain an approximate estimate of the population incidence and prevalence of both dementia and NPS. Methods Given the dynamic nature of the population with dementia, a retrospective study was conducted within the database of the Basque Health Service (real-world data) at the beginning and end of 2019. Validated random forest models were used to identify separately depressive and psychotic clusters according to their presence in the electronic health records of all patients diagnosed with dementia. Results Among the 631,949 individuals over 60 years registered, 28,563 were diagnosed with dementia, of whom 15,828 (55.4%) showed psychotic symptoms and 19,461 (68.1%) depressive symptoms. The incidence of dementia in 2019 was 6.8/1000 person-years. Most incident cases of depressive (72.3%) and psychotic (51.9%) NPS occurred in cases of incident dementia. The risk of depressive-type NPS grows with years since dementia diagnosis, living in a nursing home, and female sex, but falls with older age. In the psychotic cluster model, the effects of male sex, and older age are inverted, both increasing the probability of this type of symptoms. Conclusions The stigmatization factor conditions the social and attitudinal environment, delaying the diagnosis of dementia, preventing patients from receiving adequate care and exacerbating families’ suffering. This study evidences the synergy between big data and real-world data for psychiatric epidemiological research. |
| Databáze: | OpenAIRE |
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