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A Parsimonious Four-Variable Nomogram for Predicting Lower-Extremity Amputation in Patients with Type 2 Diabetes and
Haipeng Zhang1, Jian Guo1, Yongfang Ma2
1Department of Trauma Orthopedics, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, 830000, People's Republic of China.
Diabetes, Metabolic Syndrome and Obesity : Targets and Therapy
|August 14, 2026
Summary
A new nomogram using serum albumin, platelet count, smoking history, and hypertension can predict lower-extremity amputation (LEA) risk in diabetic foot ulcer (DFU) patients. This simple tool aids in-hospital risk stratification for type 2 diabetes patients.
Area of Science:
- Medical Science
- Clinical Research
- Diabetes Management
Background:
- Diabetic foot ulcers (DFUs) are the primary cause of non-traumatic lower-extremity amputations (LEAs).
- Existing risk-stratification tools for LEA are often complex and not suitable for routine clinical practice.
- There is a need for simple, accessible methods to assess amputation risk in DFU patients.
Purpose of the Study:
- To develop a straightforward nomogram for predicting in-hospital LEA risk.
- To utilize routinely available clinical indicators for risk stratification.
- To improve early identification of high-risk patients with type 2 diabetes and DFUs.
Main Methods:
- A retrospective cohort study of 508 hospitalized patients with type 2 diabetes-related DFUs.
- Data split into training (n=357) and validation (n=151) sets.
- LASSO regression and bootstrap stepwise logistic regression used to identify key predictors (serum albumin, platelet count, smoking history, hypertension).
- Nomogram construction and evaluation of discrimination (AUC) and calibration.
Main Results:
- A four-variable nomogram incorporating serum albumin, platelet count, smoking history, and hypertension was developed.
- The nomogram demonstrated moderate discrimination with an AUC of 0.788 in the training set and 0.755 in the validation set.
- Acceptable calibration and potential clinical utility were indicated by decision curve analysis.
Conclusions:
- A simple nomogram using routine clinical data can estimate in-hospital LEA risk in patients with type 2 diabetes-related DFUs.
- The model shows potential for early risk stratification, aiding clinical decision-making.
- External multi-center validation is necessary before widespread clinical adoption.
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