Development and validation of a nomogram for predicting moderate-to-severe diabetic foot ulcers in type 2 diabetes
Summary: This study developed and validated a nomogram model to predict the risk of moderate to severe diabetic foot ulcers (DFUs) in patients with type 2 diabetes. Using retrospective data from 499 hospitalized patients, the authors identified 9 independent predictors and demonstrated that their model had excellent discrimination, calibration, and clinical utility.
Key Highlights:
- Study cohort: 499 patients with type 2 diabetes hospitalized between January 2021 and December 2023.
- Predictors included: Diabetic kidney disease (DKD), diabetic peripheral neuropathy (DPN), diabetic retinopathy (DR), peripheral angiopathy (PAD), D-dimer, K-time, total cholesterol (TC), LDL-C, and HDL-C.
- Model performance: The nomogram achieved an AUC of 0.977 (95% CI 0.965–0.989) in the training set and 0.977 (95% CI 0.958–0.996) in the validation set.
- Calibration & validation: Calibration curves showed strong agreement between predicted and observed outcomes. Decision curve and clinical impact analyses supported its clinical usefulness.
- Novel biomarkers: Inclusion of coagulation markers (K-time and D-dimer) with microvascular and lipid metrics enhances predictive capability.
- Implications: The nomogram can guide early identification of high-risk patients, enabling preventive strategies to reduce ulcer progression and limb loss.
Read the full article in Frontiers in Endocrinology
Keywords:
Jinying Zhang,
Jing Lin,
Lizhen Wu,
Jiayu Lin,
nomogram,
diabetic foot ulcer prediction,
type 2 diabetes,
coagulation markers,
DKD,
DPN,
PAD