ArticleClinical epidemiology2018
Development and validation of a risk prediction model for severe hypoglycemia in adult patients with type 2 diabetes: a nationwide population-based cohort study.
Article in Clinical epidemiology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 3 of them syntheses that pooled it.
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Who cites it
31 citing papers in PubMed, 3 syntheses or guidelines pooled it, 43 citations in OpenAlex.
- Hypoglycaemia Risk Prediction Models for Type 2 Diabetes: A Systematic Review and Meta-Analysis.Endocrinology, diabetes & metabolism · 2026Pooled it
- Risk factors for hypoglycemia in patients with type 2 diabetes mellitus: a systematic review and meta-analysis.Frontiers in endocrinology · 2026Pooled it
- Data-based modeling for hypoglycemia prediction: Importance, trends, and implications for clinical practice.Frontiers in public health · 2023Pooled it
- Diabetes progression and severe hypoglycemia: a nationwide cohort study of 2,475,605 adults with type 2 diabetes mellitus.The Korean journal of internal medicine · 2026Article
- Predicting acute and chronic diabetes complications among adults newly diagnosed with diabetes: development and validation of dynamic risk prediction models.Nature communications · 2026Article
- Development of risk prediction model for major amputation in patients with diabetic foot.BMC endocrine disorders · 2026Article
- Development and Validation of Nomogram-Based Predictive Models for Severe Hypoglycemia in Adults With Type 1 Diabetes Treated With Multiple Daily Injections: The SEHYPAN Study.Diabetes/metabolism research and reviews · 2026Observational
- Association Between Psoriasis Risk and Body Mass Index and Waist Circumference in Diabetes: A Population-Based Cohort Study.Annals of dermatology · 2026Article
- Development and validation of a hypoglycemia risk prediction model for hospitalized type 2 diabetes patients following laparoscopic colorectal cancer resection: a retrospective cohort study.Frontiers in endocrinology · 2026Article
- Construction and validation of a risk prediction model for hypoglycemia in patients with gestational diabetes mellitus.BMC pregnancy and childbirth · 2025Article
- A CGM-Based model for predicting hypoglycemia in type 2 diabetes patients with TIR in target.Diabetology & metabolic syndrome · 2025Article
- Machine learning-based online prediction of nocturnal hypoglycemia in elderly patients with type 2 diabetes.Frontiers in endocrinology · 2025Article
- Functional outcome after surgical treatment for spontaneous intracerebral hemorrhages: Development of the HeMAtOma score.Brain & spine · 2025Article
- Artificial Intelligence to Diagnose Complications of Diabetes.Journal of diabetes science and technology · 2025Review
- Article
- Reproductive Life Span and Severe Hypoglycemia Risk in Postmenopausal Women with Type 2 Diabetes Mellitus.Diabetes & metabolism journal · 2022Article
- Previously unrecognized risk factors for severe hypoglycaemia requiring emergency medical care in insulin-treated type 2 diabetes: Results from a real-world nested case-control study.Diabetes, obesity & metabolism · 2022Article
- Predicting Risk of Hypoglycemia in Patients With Type 2 Diabetes by Electronic Health Record-Based Machine Learning: Development and Validation.JMIR medical informatics · 2022Article
- Identifying Patients With Hypoglycemia Using Natural Language Processing: Systematic Literature Review.JMIR diabetes · 2022Review
- Article
Corrections and comments
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Authors and funding
7 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeThere is a scarcity of long-term prediction models for severe hypoglycemia (SH) in subjects with type 2 diabetes mellitus (T2DM). In this study, a model was developed and validated to predict the risk of SH in adult patients with T2DM. PATIENTS AND
methodsBaseline and follow-up data from patients with T2DM who received health evaluations from January 1, 2009, to December 31, 2010 (n=1,676,885) were analyzed as development (n=1,173,820) and validation (n=503,065) cohorts using the National Health Insurance Database (DB) in Korea. New SH episodes were identified using ICD-10 codes. A Cox proportional hazards regression model and Cox model coefficients were used to derive a risk scoring system, and 14 predictive variables were selected. A risk score nomogram based on the risk prediction model was created to estimate the 1-year risk of SH.
resultsIn the development cohort, a total of 5,325 (0.45%) patients experienced SH episodes during the follow-up period. After multivariable adjustment, older age, female sex, current smoker, drinking, low body mass index, lack of exercise, previous SH events, insulin or multiple oral hypoglycemic agent use, presence of hypertension or chronic kidney disease, longer duration of diabetes, low or high glucose level, and high Charlson Comorbidity Index score were found to be significant risk factors for the development of SH and were incorporated into the risk model. The concordance indices were 0.871 (95% confidence interval, 0.863-0.881) in development cohort and 0.866 (95% CI, 0.856-0.879) in the validation cohort. The calibration plot showed a nearly 45° line, which indicates that this model predicts well an absolute SH event.
conclusionThis 14-variable prediction model for SH events may be a useful tool to identify high-risk patients and guide prevention of SH in adult patients with T2DM.
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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.