Clinical Subtypes of Older Adults Starting Long-term Care in Japan and Their Association with Prognoses: a Data-driven Cluster Analysis

Overview

Journal Sci Rep

Specialty Science

Date 2024 Jun 28

PMID 38942898

Authors

Yuji Ito

Masao Iwagami

Jun Komiyama

Yoko Hamasaki

Naoaki Kuroda

Ai Suzuki

Tomoko Ito

Tadahiro Goto

Eric Y F Wan

Francisco T T Lai

Nanako Tamiya

Affiliations

Soon will be listed here.

Abstract

We aimed to identify the clinical subtypes in individuals starting long-term care in Japan and examined their association with prognoses. Using linked medical insurance claims data and survey data for care-need certification in a large city, we identified participants who started long-term care. Grouping them based on 22 diseases recorded in the past 6 months using fuzzy c-means clustering, we examined the longitudinal association between clusters and death or care-need level deterioration within 2 years. We analyzed 4,648 participants (median age 83 [interquartile range 78-88] years, female 60.4%) between October 2014 and March 2019 and categorized them into (i) musculoskeletal and sensory, (ii) cardiac, (iii) neurological, (iv) respiratory and cancer, (v) insulin-dependent diabetes, and (vi) unspecified subtypes. The results of clustering were replicated in another city. Compared with the musculoskeletal and sensory subtype, the adjusted hazard ratio (95% confidence interval) for death was 1.22 (1.05-1.42), 1.81 (1.54-2.13), and 1.21 (1.00-1.46) for the cardiac, respiratory and cancer, and insulin-dependent diabetes subtypes, respectively. The care-need levels more likely worsened in the cardiac, respiratory and cancer, and unspecified subtypes than in the musculoskeletal and sensory subtype. In conclusion, distinct clinical subtypes exist among individuals initiating long-term care.

References

Matsuda T, Iwagami M, Suzuki T, Jin X, Watanabe T, Tamiya N . Correlation between the Barthel Index and care need levels in the Japanese long-term care insurance system. Geriatr Gerontol Int. 2019; 19(11):1186-1187. DOI: 10.1111/ggi.13777. View

Suzuki A, Jin X, Ito T, Yoshie S, Ishizaki T, Iijima K . Factors Affecting Care-Level Deterioration among Older Adults with Mild and Moderate Disabilities in Japan: Evidence from the Nationally Standardized Survey for Care-Needs Certification. Int J Environ Res Public Health. 2022; 19(5). PMC: 8910748. DOI: 10.3390/ijerph19053065. View

Ibarra-Castillo C, Guisado-Clavero M, Violan-Fors C, Pons-Vigues M, Lopez-Jimenez T, Roso-Llorach A . Survival in relation to multimorbidity patterns in older adults in primary care in Barcelona, Spain (2010-2014): a longitudinal study based on electronic health records. J Epidemiol Community Health. 2018; 72(3):185-192. DOI: 10.1136/jech-2017-209984. View

Ito T, Mori T, Takahashi H, Shimafuji N, Iijima K, Yoshie S . Prevention services via public long-term care insurance can be effective among a specific group of older adults in Japan. BMC Health Serv Res. 2021; 21(1):531. PMC: 8166019. DOI: 10.1186/s12913-021-06495-0. View

Konig I, Fuchs O, Hansen G, von Mutius E, Kopp M . What is precision medicine?. Eur Respir J. 2017; 50(4). DOI: 10.1183/13993003.00391-2017. View

Cohen J, Schrauben S, Zhao L, Basso M, Cvijic M, Li Z . Clinical Phenogroups in Heart Failure With Preserved Ejection Fraction: Detailed Phenotypes, Prognosis, and Response to Spironolactone. JACC Heart Fail. 2020; 8(3):172-184. PMC: 7058514. DOI: 10.1016/j.jchf.2019.09.009. View

Ahlqvist E, Storm P, Karajamaki A, Martinell M, Dorkhan M, Carlsson A . Novel subgroups of adult-onset diabetes and their association with outcomes: a data-driven cluster analysis of six variables. Lancet Diabetes Endocrinol. 2018; 6(5):361-369. DOI: 10.1016/S2213-8587(18)30051-2. View

Violan C, Fernandez-Bertolin S, Guisado-Clavero M, Foguet-Boreu Q, Valderas J, Vidal Manzano J . Five-year trajectories of multimorbidity patterns in an elderly Mediterranean population using Hidden Markov Models. Sci Rep. 2020; 10(1):16879. PMC: 7547668. DOI: 10.1038/s41598-020-73231-9. View

Mori T, Hamada S, Yoshie S, Jeon B, Jin X, Takahashi H . The associations of multimorbidity with the sum of annual medical and long-term care expenditures in Japan. BMC Geriatr. 2019; 19(1):69. PMC: 6404301. DOI: 10.1186/s12877-019-1057-7. View

10.

Wang R, Wang Z . Precision Medicine: Disease Subtyping and Tailored Treatment. Cancers (Basel). 2023; 15(15). PMC: 10417651. DOI: 10.3390/cancers15153837. View

11.

Maruta M, Tabira T, Makizako H, Sagari A, Miyata H, Yoshimitsu K . Impact of Outpatient Rehabilitation Service in Preventing the Deterioration of the Care-Needs Level Among Japanese Older Adults Availing Long-Term Care Insurance: A Propensity Score Matched Retrospective Study. Int J Environ Res Public Health. 2019; 16(7). PMC: 6480242. DOI: 10.3390/ijerph16071292. View

12.

Tazzeo C, Rizzuto D, Calderon-Larranaga A, Roso-Llorach A, Marengoni A, Welmer A . Multimorbidity patterns and risk of frailty in older community-dwelling adults: a population-based cohort study. Age Ageing. 2021; 50(6):2183-2191. PMC: 8581386. DOI: 10.1093/ageing/afab138. View

13.

Mitsutake S, Ishizaki T, Teramoto C, Shimizu S, Ito H . Patterns of Co-Occurrence of Chronic Disease Among Older Adults in Tokyo, Japan. Prev Chronic Dis. 2019; 16:E11. PMC: 6362710. DOI: 10.5888/pcd16.180170. View

14.

Violan C, Foguet-Boreu Q, Fernandez-Bertolin S, Guisado-Clavero M, Cabrera-Bean M, Formiga F . Soft clustering using real-world data for the identification of multimorbidity patterns in an elderly population: cross-sectional study in a Mediterranean population. BMJ Open. 2019; 9(8):e029594. PMC: 6719769. DOI: 10.1136/bmjopen-2019-029594. View

15.

Kuroda N, Hamada S, Sakata N, Jeon B, Iijima K, Yoshie S . Antipsychotic use and related factors among people with dementia aged 75 years or older in Japan: A comprehensive population-based estimation using medical and long-term care data. Int J Geriatr Psychiatry. 2018; 34(3):472-479. PMC: 6590349. DOI: 10.1002/gps.5041. View

16.

Iwagami M, Tamiya N . The Long-Term Care Insurance System in Japan: Past, Present, and Future. JMA J. 2021; 2(1):67-69. PMC: 7930803. DOI: 10.31662/jmaj.2018-0015. View

17.

Marengoni A, Tazzeo C, Calderon-Larranaga A, Roso-Llorach A, Onder G, Zucchelli A . Multimorbidity Patterns and 6-Year Risk of Institutionalization in Older Persons: The Role of Social Formal and Informal Care. J Am Med Dir Assoc. 2021; 22(10):2184-2189.e1. DOI: 10.1016/j.jamda.2020.12.040. View

18.

Bi Q, Goodman K, Kaminsky J, Lessler J . What is Machine Learning? A Primer for the Epidemiologist. Am J Epidemiol. 2019; 188(12):2222-2239. DOI: 10.1093/aje/kwz189. View

19.

Vetrano D, Roso-Llorach A, Fernandez S, Guisado-Clavero M, Violan C, Onder G . Twelve-year clinical trajectories of multimorbidity in a population of older adults. Nat Commun. 2020; 11(1):3223. PMC: 7320143. DOI: 10.1038/s41467-020-16780-x. View

20.

Tamiya N, Noguchi H, Nishi A, Reich M, Ikegami N, Hashimoto H . Population ageing and wellbeing: lessons from Japan's long-term care insurance policy. Lancet. 2011; 378(9797):1183-92. DOI: 10.1016/S0140-6736(11)61176-8. View