Predictive modeling and risk assessment of pancreatic β-cell dysfunction in type 2 diabetes

Type 2 diabetes mellitus (T2DM) is a widespread metabolic disorder driven in part by pancreatic β-cell dysfunction. This study aims to identify key determinants of β-cell impairment in T2DM patients and develop a predictive risk model to enhance clinical management strategies. This retrospective study included 120 patients newly diagnosed with T2DM who were admitted to our hospital between March 2023 and March 2024. We measured fasting plasma glucose, fasting insulin, and other relevant metabolic indicators. Insulin resistance and β-cell function were evaluated using the homeostasis model assessment (homeostasis model assessment insulin-resistance and homeostasis model assessment-β). To identify independent risk factors, we performed both univariate and multivariate stepwise regression analyses, and subsequently constructed predictive models based on the results. The cohort exhibited moderate insulin resistance (homeostasis model assessment insulin-resistance: 2.93 ± 0.77) and significant β-cell dysfunction (homeostasis model assessment-β: 33.74 ± 11.46). Regression analysis identified age, body mass index (BMI), sedentary lifestyle, and triglyceride levels as independent predictors of insulin resistance (P < .05), yielding the following model: logit (1) = 2.371 + 0.862 × age + 0.612 × BMI + 0.598 × sedentary + 0.237 × triglyceride. Similarly, age, BMI, and sedentary behavior were independently associated with β-cell dysfunction (P < .05), leading to the model: logit (2) = 29.562 + 2.947 × age + 9.570 × BMI + 3.205 × sedentary. Newly diagnosed T2DM patients frequently present with insulin resistance and β-cell impairment. High-risk subgroups include individuals aged ≥ 40, those with elevated BMI, physical inactivity, and dyslipidemia. The proposed predictive models may aid in early risk stratification and personalized intervention.

Authors

Institutions

Publication Details

Journal
Medicine
Published
2025-09-19
DOI
https://doi.org/10.1097/md.0000000000044462
Primary Topic
Diabetes Management and Research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Predictive modeling and risk assessment of pancreatic β-cell dysfunction in type 2 diabetes

Nan Wu, Yuqin Sun
Medicine
Diabetes Management and Research
article

Predictive modeling and risk assessment of pancreatic β-cell dysfunction in type 2 diabetes

Nan Wu, Yuqin Sun
article en

Abstract

Type 2 diabetes mellitus (T2DM) is a widespread metabolic disorder driven in part by pancreatic β-cell dysfunction. This study aims to identify key determinants of β-cell impairment in T2DM patients and develop a predictive risk model to enhance clinical management strategies. This retrospective study included 120 patients newly diagnosed with T2DM who were admitted to our hospital between March 2023 and March 2024. We measured fasting plasma glucose, fasting insulin, and other relevant metabolic indicators. Insulin resistance and β-cell function were evaluated using the homeostasis model assessment (homeostasis model assessment insulin-resistance and homeostasis model assessment-β). To identify independent risk factors, we performed both univariate and multivariate stepwise regression analyses, and subsequently constructed predictive models based on the results. The cohort exhibited moderate insulin resistance (homeostasis model assessment insulin-resistance: 2.93 ± 0.77) and significant β-cell dysfunction (homeostasis model assessment-β: 33.74 ± 11.46). Regression analysis identified age, body mass index (BMI), sedentary lifestyle, and triglyceride levels as independent predictors of insulin resistance (P < .05), yielding the following model: logit (1) = 2.371 + 0.862 × age + 0.612 × BMI + 0.598 × sedentary + 0.237 × triglyceride. Similarly, age, BMI, and sedentary behavior were independently associated with β-cell dysfunction (P < .05), leading to the model: logit (2) = 29.562 + 2.947 × age + 9.570 × BMI + 3.205 × sedentary. Newly diagnosed T2DM patients frequently present with insulin resistance and β-cell impairment. High-risk subgroups include individuals aged ≥ 40, those with elevated BMI, physical inactivity, and dyslipidemia. The proposed predictive models may aid in early risk stratification and personalized intervention.

MedicineVol. 104(38)
Jilin Medical University (CN)
Openalex Percentile: Top 65%
Diabetes Management and Research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.