Evidence map›Paper›PMID 37794668›Full record

ArticlePsychiatry investigation2023

Multimorbidity Pattern and Risk for Mortality Among Patients With Dementia: A Nationwide Cohort Study Using Latent Class Analysis.

Che-Sheng Chu, Shu-Li Cheng, Ya-Mei Bai, Tung-Ping Su, Shih-Jen Tsai, Tzeng-Ji Chen, Fu-Chi Yang, Mu-Hong Chen, Chih-Sung Liang

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Article in Psychiatry investigation, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

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5citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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5 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Che-Sheng ChuDepartment of Psychiatry, Kaohsiung Veterans General Hospital, Kaohsiung, Taiwan.
Shu-Li ChengDepartment of Nursing, Mackay Medical College, Taipei, Taiwan.
Ya-Mei BaiDepartment of Psychiatry, Taipei Veterans General Hospital, Taipei, Taiwan.
Tung-Ping SuDepartment of Psychiatry, Taipei Veterans General Hospital, Taipei, Taiwan.
Shih-Jen TsaiDepartment of Psychiatry, Taipei Veterans General Hospital, Taipei, Taiwan.
Tzeng-Ji ChenDepartment of Psychiatry, Cheng Hsin General Hospital, Taipei, Taiwan.
Fu-Chi YangDepartment of Neurology, Tri-Service General Hospital, Taipei, Taiwan.
Mu-Hong ChenDepartment of Psychiatry, Taipei Veterans General Hospital, Taipei, Taiwan.
Chih-Sung LiangDepartment of Psychiatry, Beitou Branch, Tri-Service General Hospital, Taipei, Taiwan.

Funding

Kaohsiung Veterans General Hospital KGVGH-110-051Kaohsiung Veterans General Hospital KSVGH111-082Kaohsiung Veterans General Hospital KSVGH111-181Kaohsiung Veterans General Hospital VGHKS-109-070MacKay Medical College, Taiwan MMC-RD-111-1B-P003Ministry of Science and Technology, Taiwan 107-2314-B-075-063-MY3Ministry of Science and Technology, Taiwan 108-2314-B-075-037Ministry of Science and Technology, Taiwan MOST-109-2314-B-075B-001-MY2Taipei Veterans General Hospital V106B-020Taipei Veterans General Hospital V107B-010Taipei Veterans General Hospital V107C-181Taipei Veterans General Hospital V108B-012Yen Tjing Ling Medical Foundation CI-110-30
6 · The paper itself

Abstract

objectiveIndividuals with dementia are at a substantially elevated risk for mortality; however, few studies have examined multimorbidity patterns and determined the inter-relationship between these comorbidities in predicting mortality risk.

methodsThis is a prospective cohort study. Data from 6,556 patients who were diagnosed with dementia between 1997 and 2012 using the Taiwan National Health Insurance Research Database were analyzed. Latent class analysis was performed using 16 common chronic conditions to identify mortality risk among potentially different latent classes. Logistic regression was performed to determine the adjusted association of the determined latent classes with the 5-year mortality rate.

resultsWith adjustment for age, a three-class model was identified, with 42.7% of participants classified as "low comorbidity class (cluster 1)", 44.2% as "cardiometabolic multimorbidity class (cluster 2)", and 13.1% as "FRINGED class (cluster 3, characterized by FRacture, Infection, NasoGastric feeding, and bleEDing over upper gastrointestinal tract)." The incidence of 5-year mortality was 17.6% in cluster 1, 26.7% in cluster 2, and 59.6% in cluster 3. Compared with cluster 1, the odds ratio for mortality was 9.828 (95% confidence interval [CI]=6.708-14.401; p<0.001) in cluster 2 and 1.582 (95% CI=1.281-1.953; p<0.001) in cluster 3.

conclusionAmong patients with dementia, the risk for 5-year mortality was highest in the subpopulation characterized by fracture, urinary and pulmonary infection, upper gastrointestinal bleeding, and nasogastric intubation, rather than cancer or cardiometabolic comorbidities. These findings may improve decision-making and advance care planning for patients with dementia.

Indexed as

DementiaLatent class analysisMortalityMultimorbidity

Identifiers

PMID37794668
PMCPMC10555512

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.