Evidence map›Paper›PMID 38169157›Full record

ArticleJournal of diabetes2024

Kidney function trajectories, associated factors, and outcomes in multiethnic Asian patients with type 2 diabetes.

Liang Feng, Yong Mong Bee, Xiuju Fu, Jia Liang Kwek, Choong Meng Chan, Tazeen H Jafar

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Article in Journal of diabetes, 2024. 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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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Liang FengProgram in Health Services & Systems Research, Duke-NUS Medical School, Singapore, Singapore.ORCID https://orcid.org/0000-0002-0252-0136
Yong Mong BeeDepartment of Endocrinology, Singapore General Hospital, Singapore, Singapore.
Xiuju FuInstitute of High Performance Computing, A*STAR, Singapore, Singapore.
Jia Liang KwekDepartment of Renal Medicine, Singapore General Hospital, Singapore, Singapore.
Choong Meng ChanDepartment of Renal Medicine, Singapore General Hospital, Singapore, Singapore.
Tazeen H JafarProgram in Health Services & Systems Research, Duke-NUS Medical School, Singapore, Singapore.ORCID https://orcid.org/0000-0001-7454-8376

Funding

Agency for Science, Techonology and Research (A*STAR)Industry Alignment Fund-Pre-Positioning Programme (IAF-PP) H19/01/a0/023National Heart Center SingaporeSingapore Cardiac Data BankSingapore General Hospital
6 · The paper itself

Abstract

backgroundWe examined the trajectory of estimated glomerular filtrate rate (eGFR), associated risk factors, and its relationship with end-stage kidney disease (ESKD) among a multiethnic patient population with type 2 diabetes in Singapore.

methodsA follow-up study included 62 080 individuals with type 2 diabetes aged ≥18 years in a multi-institutional SingHealth Diabetes Registry between 2013 and 2019. eGFR trajectories were analyzed using latent class linear mixed models. Factors associated with eGFR trajectories were evaluated using multinomial logistic regression. The association of eGFR trajectories with ESKD was assessed via competing risk models.

resultsTrajectory of kidney function, determined by eGFR, was nonlinear. The trajectory pattern was classified as stable initially then gradual decline (75%), progressive decline (21.9%), and rapid decline (3.1%). Younger age, female sex, Malay ethnicity, lower-income housing type, current smoking, higher glycated hemoglobin, lower low-density lipoprotein, higher triglyceride, uncontrolled blood pressure, albuminuria, cardiovascular disease, hypertension, and higher eGFR levels each were associated with progressive or rapid decline. Compared with the trajectory of stable initially then gradual eGFR decline, progressive decline increased the hazard of ESKD by 6.14-fold (95% confidence interval [CI]: 4.96-7.61)) and rapid decline by 82.55 folds (95% CI: 55.90-121.89).

conclusionsThree nonlinear trajectory classes of kidney function were identified among multiethnic individuals with type 2 diabetes in Singapore. About one in four individuals had a progressive or rapid decline in eGFR. Our results suggest that eGFR trajectories are correlated with multiple social and modifiable risk factors and inform the risk of ESKD.

Indexed as

Diabetes Mellitus, Type 2Glomerular Filtration RateAdultAgedAsian PeopleDiabetic NephropathiesDisease ProgressionFemaleFollow-Up StudiesHumansKidneyKidney Failure, ChronicMaleMiddle AgedPrognosisRegistriesalbuminuriaestimated glomerular filtration ratelatent class linear mixed modelsrisk factorstrajectoriestype 2 diabetes

Identifiers

PMID38169157
PMCPMC11418407

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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.