Amputation Risk Prediction Tools for Patients With Diabetic Foot: A Systematic Review.

Area of Science:

• Diabetic Foot Research
• Clinical Prediction Models
• Risk Stratification

Background:

• Diabetic foot ulcers are a leading cause of lower limb amputation.
• Accurate risk prediction models are crucial for timely intervention and prevention of amputation.
• Existing models require systematic evaluation for clinical utility.

Purpose of the Study:

• To systematically review and evaluate amputation risk prediction models for patients with diabetic foot.
• To identify key predictive factors and assess the performance and applicability of existing models.
• To guide future development of more effective risk prediction tools.

Main Methods:

• Comprehensive literature search across multiple databases (PubMed, Embase, Web of Science, CNKI, etc.).
• Screening of 2134 articles, with 9 studies meeting inclusion criteria.
• Data extraction on model construction, predictive factors, and efficacy indicators (AUC, sensitivity, specificity).

Main Results:

• Nine studies described 15 prediction models and one tool, with 8 studies showing a high risk of bias.
• Key predictive factors included diabetes duration, glycated hemoglobin, white blood cell count, fibrinogen, and infection.
• Diabetes duration, white blood cell count, and fibrinogen were the most common predictive factors identified.

Conclusions:

• Current diabetic foot amputation risk prediction models demonstrate good predictive performance.
• Significant limitations include a high risk of bias and suboptimal clinical applicability in the literature.
• Future research should focus on validating/calibrating existing tools or developing new models with reduced bias and enhanced clinical utility.