Estimation of the epidemiology of dementia and associated neuropsychiatric symptoms by applying machine learning to real-world data

IF 5.2 3区 医学 Q1 PSYCHIATRY
Javier Mar , Ania Gorostiza , Arantzazu Arrospide , Igor Larrañaga , Ane Alberdi , Carlos Cernuda , Álvaro Iruin , Mikel Tainta , Lorea Mar-Barrutia , Oliver Ibarrondo
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引用次数: 7

Abstract

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.

通过将机器学习应用于现实世界数据来估计痴呆和相关神经精神症状的流行病学
痴呆相关神经精神症状(NPS)的发病率尚不清楚,这阻碍了对其人口负担的评估。本研究的目的是获得痴呆症和NPS的人群发病率和患病率的大致估计。方法考虑到痴呆症人群的动态性,在2019年初和年底对巴斯克卫生服务数据库(真实数据)进行了回顾性研究。使用经过验证的随机森林模型,根据所有诊断为痴呆症的患者的电子健康记录中的存在情况,分别识别抑郁症和精神病性群集。结果在登记的60岁以上的631,949人中,28,563人被诊断为痴呆,其中15,828人(55.4%)表现为精神病症状,19,461人(68.1%)表现为抑郁症状。2019年痴呆症的发病率为6.8/1000人年。大多数抑郁症(72.3%)和精神病性NPS(51.9%)发生在痴呆患者中。患抑郁症型NPS的风险随着诊断为痴呆症、住在养老院和女性的年龄而增加,但随着年龄的增长而下降。在精神病群集模型中,男性性别和年龄的影响是相反的,两者都增加了这类症状的可能性。结论污名化因素影响了社会和态度环境,延误了痴呆症的诊断,使患者无法得到适当的护理,加剧了家庭的痛苦。本研究证明了大数据与现实世界数据在精神病学研究中的协同作用。
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来源期刊
自引率
3.30%
发文量
58
期刊介绍: The Spanish Journal of Psychiatry and Mental Health (SJPMH), incorporated into ISSN 1888-9891, is the official scientific publication of the Spanish Society of Psychiatry and Mental Health. The journal focuses on studying mental illnesses, their pathological processes, and their psychosocial consequences, and aims to disseminate scientific advances in all areas related to mental health and illness. SJPMH accepts unpublished works on psychiatry and mental health, including their medical and social implications. The journal provides space for research in the biological, clinical, and psychosocial fields. Manuscripts undergo peer-review by external reviewers before being accepted for publication. SJPMH is indexed in Index Medicus/Medline, IBECS, Social Sciences Citation Index Journal Citation Reports/Social Sciences Edition, and Current Contents/Social and Behavioral Sciences.
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