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Classification of long-term clinical course of Parkinson's disease using clustering algorithms on social support registry database SCIE SCOPUS

Title
Classification of long-term clinical course of Parkinson's disease using clustering algorithms on social support registry database
Authors
Park, DoughoLee, Su YunKim, Jong HunKim, Hyoung Seop
Date Issued
2023-09
Publisher
SPRINGERNATURE
Abstract
Although Parkinson's disease (PD) has a heterogeneous disease course, it remains challenging to establish subtypes. We described and clustered the natural course of Parkinson's disease (PD) with respect to functional disability and mortality. This retrospective cohort study utilized the Korean National Health Insurance Service database, which contains the social support registry database for patients with PD. We extracted patients newly diagnosed with PD in 2009 and followed them up until the end of 2018. Functional disability was assessed based on the long-term care insurance (LTCI) and National Disability Registry data. Further, we measured all-cause mortality during the observation period. We included 2944 eligible patients. The surviving patients were followed up for 113.7 +/- 3.3 months. Among the patients who died, patients with and without disability registration were followed up for 61.4 +/- 30.1 and 43.2 +/- 32.0 months, respectively. The cumulative survival rate was highest in cluster 1 and decreased from Cluster 1 to Cluster 6. In the multivariable Cox regression analysis, the defined clusters were significantly associated with increased long-term mortality (adjusted hazard ratio [aHR], 3.440; 95% confidence interval [CI], 3.233-3.659; p < 0.001). Further, age (aHR, 1.038; 95% CI, 1.031-1.045; p < 0.001), diabetes (aHR, 1.146; 95% CI, 1.037-1.267; p = 0.007), and chronic kidney disease (aHR, 1.382; 95% CI, 1.080-1.768; p = 0.010) were identified as independent risk factors for increased risk of long-term mortality. Contrastingly, the female gender (aHR, 0.753; 95% CI, 0.681-0.833; p < 0.001) and a higher LTCI grade (aHR, 0.995; 95% CI, 0.992-0.997; p < 0.001) were associated with a significantly decreased long-term mortality risk. We identified six clinical course clusters for PD using longitudinal data regarding the social support registry and mortality. Our results suggest that PD progression is heterogeneous in terms of disability and mortality.
URI
https://oasis.postech.ac.kr/handle/2014.oak/123628
DOI
10.1186/s40537-023-00819-z
ISSN
2196-1115
Article Type
Article
Citation
JOURNAL OF BIG DATA, vol. 10, no. 1, 2023-09
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김형섭KIM, HYOUNG SEOP
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