{"title":"定量评估 2 型糖尿病患者的代谢记忆及其对肾功能衰退的预测:回顾性观察研究","authors":"Kentaro Oniki , Takuro Shigaki , Ayami Kajiwara-Morita , Keiichi Shigetome , Akira Yoshida , Hideaki Jinnouchi , Junji Saruwatari","doi":"10.1016/j.dsx.2025.103225","DOIUrl":null,"url":null,"abstract":"<div><h3>Aims</h3><div>This study quantitatively assesses metabolic memory by modeling the relationship between hyperglycemic exposure and renal function decline in patients with type 2 diabetes (T2D).</div></div><div><h3>Methods</h3><div>This retrospective longitudinal study included 381 Japanese patients with T2D. Hyperglycemic exposure was presented by calculating the area under the curve (AUC) for HbA1c ≥ 6 % (AUC<sub>HbA1c ≥ 6 %</sub>) during the observation period. A non-linear mixed-effects model was constructed to predict changes in estimated glomerular filtration rate (eGFR) based on AUC<sub>HbA1c ≥ 6 %</sub>.</div></div><div><h3>Results</h3><div>The relationship between AUC<sub>HbA1c ≥ 6 %</sub> and eGFR changes was shown by a sigmoidal curve, with sex, age, diabetic retinopathy, dyslipidemia, and hypertension incorporated as covariates. The predictive utility of the model was validated using goodness-of-fit plot, visual predictive check, and bootstrap methods.</div></div><div><h3>Conclusions</h3><div>We developed an AUC<sub>HbA1c ≥ 6 %</sub>-based model to predict renal function decline in patients with T2D, showing that AUC<sub>HbA1c ≥ 6 %</sub> may serve as a quantitative indicator of metabolic memory.</div></div>","PeriodicalId":48252,"journal":{"name":"Diabetes & Metabolic Syndrome-Clinical Research & Reviews","volume":"19 4","pages":"Article 103225"},"PeriodicalIF":4.3000,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Quantitative assessment of metabolic memory and its prediction of renal function decline in patients with type 2 diabetes: A retrospective observational study\",\"authors\":\"Kentaro Oniki , Takuro Shigaki , Ayami Kajiwara-Morita , Keiichi Shigetome , Akira Yoshida , Hideaki Jinnouchi , Junji Saruwatari\",\"doi\":\"10.1016/j.dsx.2025.103225\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Aims</h3><div>This study quantitatively assesses metabolic memory by modeling the relationship between hyperglycemic exposure and renal function decline in patients with type 2 diabetes (T2D).</div></div><div><h3>Methods</h3><div>This retrospective longitudinal study included 381 Japanese patients with T2D. Hyperglycemic exposure was presented by calculating the area under the curve (AUC) for HbA1c ≥ 6 % (AUC<sub>HbA1c ≥ 6 %</sub>) during the observation period. A non-linear mixed-effects model was constructed to predict changes in estimated glomerular filtration rate (eGFR) based on AUC<sub>HbA1c ≥ 6 %</sub>.</div></div><div><h3>Results</h3><div>The relationship between AUC<sub>HbA1c ≥ 6 %</sub> and eGFR changes was shown by a sigmoidal curve, with sex, age, diabetic retinopathy, dyslipidemia, and hypertension incorporated as covariates. The predictive utility of the model was validated using goodness-of-fit plot, visual predictive check, and bootstrap methods.</div></div><div><h3>Conclusions</h3><div>We developed an AUC<sub>HbA1c ≥ 6 %</sub>-based model to predict renal function decline in patients with T2D, showing that AUC<sub>HbA1c ≥ 6 %</sub> may serve as a quantitative indicator of metabolic memory.</div></div>\",\"PeriodicalId\":48252,\"journal\":{\"name\":\"Diabetes & Metabolic Syndrome-Clinical Research & Reviews\",\"volume\":\"19 4\",\"pages\":\"Article 103225\"},\"PeriodicalIF\":4.3000,\"publicationDate\":\"2025-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Diabetes & Metabolic Syndrome-Clinical Research & Reviews\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1871402125000426\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENDOCRINOLOGY & METABOLISM\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Diabetes & Metabolic Syndrome-Clinical Research & Reviews","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1871402125000426","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENDOCRINOLOGY & METABOLISM","Score":null,"Total":0}
Quantitative assessment of metabolic memory and its prediction of renal function decline in patients with type 2 diabetes: A retrospective observational study
Aims
This study quantitatively assesses metabolic memory by modeling the relationship between hyperglycemic exposure and renal function decline in patients with type 2 diabetes (T2D).
Methods
This retrospective longitudinal study included 381 Japanese patients with T2D. Hyperglycemic exposure was presented by calculating the area under the curve (AUC) for HbA1c ≥ 6 % (AUCHbA1c ≥ 6 %) during the observation period. A non-linear mixed-effects model was constructed to predict changes in estimated glomerular filtration rate (eGFR) based on AUCHbA1c ≥ 6 %.
Results
The relationship between AUCHbA1c ≥ 6 % and eGFR changes was shown by a sigmoidal curve, with sex, age, diabetic retinopathy, dyslipidemia, and hypertension incorporated as covariates. The predictive utility of the model was validated using goodness-of-fit plot, visual predictive check, and bootstrap methods.
Conclusions
We developed an AUCHbA1c ≥ 6 %-based model to predict renal function decline in patients with T2D, showing that AUCHbA1c ≥ 6 % may serve as a quantitative indicator of metabolic memory.
期刊介绍:
Diabetes and Metabolic Syndrome: Clinical Research and Reviews is the official journal of DiabetesIndia. It aims to provide a global platform for healthcare professionals, diabetes educators, and other stakeholders to submit their research on diabetes care.
Types of Publications:
Diabetes and Metabolic Syndrome: Clinical Research and Reviews publishes peer-reviewed original articles, reviews, short communications, case reports, letters to the Editor, and expert comments. Reviews and mini-reviews are particularly welcomed for areas within endocrinology undergoing rapid changes.