Risk stratification systems for diabetic foot ulcers: a systematic review

• Type: Another Publication in an International Scientific Journal
• Date: 2011

Authors

Matilde Soares (Author) FMUP; Boyko, EJ (Author) Other; Ribeiro, J (Author) Other; Ribeiro, I (Author) Other; Mario Dinis Ribeiro (Author) FMUP

Journal

Title: Diabetologia

Vol. 54 No. 5

Pages: 1190-1199

ISSN: 0012-186X

Publisher: Springer Nature

Indexing

ISI Web of Knowledge - 63 Citations

Scopus - 70 Citations

Other information

Authenticus ID: P-002-S63

DOI: 10.1007/s00125-010-2030-3

Abstract (EN): Several risk stratification systems have been proposed for predicting development of diabetic foot ulcer. However, little has been published that assesses their similarities and disparities, diagnostic accuracy and evidence level. Consequently, we conducted a systematic review of the existing stratification systems. We searched the MEDLINE database for studies (published until April 2010) describing the creation and validation of risk stratification systems for prediction of diabetic foot ulcer development. We included 13 studies describing or evaluating the following different risk degree stratification systems: University of Texas; International Working Group on Diabetic Foot; Scottish Intercollegiate Guideline Network (SIGN); American Diabetes Association; and Boyko and colleagues. We confirmed that five variables were included in almost all the systems: diabetic neuropathy, peripheral vascular disease, foot deformity, and previous foot ulcer and amputation. The number of variables included ranged from four to eight and the number of risk groups from two to six. Only four studies reported or allowed the calculation of diagnostic accuracy measures. The SIGN system showed some higher diagnostic accuracy values, particularly positive likelihood ratio, while predictive ability was confirmed through external validation only in the system of Boyko et al. Foot ulcer risk stratification systems are a much needed tool for screening patients with diabetes. The core variables of various systems are very similar, but the number of included variables in each model and risk groups varied greatly. Overall, the quality of evidence for these systems is low, as little validation of their predictive ability has been done.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 10