Vera-Cruz PN, Palmes PP, Tonogan L, Troncillo AH, et al.
Malaysian orthopaedic journal. Date of publication 2020 Nov 1;volume 14(3):114-123.
1. Malays Orthop J. 2020 Nov;14(3):114-123. doi: 10.5704/MOJ.2011.018.
Comparison of WIFi, University of Texas and Wagner Classification Systems as
Major Amputation Predictors for Admitted Diabetic Foot Patients: A Prospective
Cohort Study.
Vera-Cruz PN(1), Palmes PP(1), Tonogan L(2), Troncillo AH(2).
Author information:
(1)Department of Internal Medicine, West Visayas State University Medical
Center, Iloilo City, Philippines.
(2)Department of Orthopaedics, West Visayas State University Medical Center,
Iloilo City, Philippines.
INTRODUCTION: Classifications systems are powerful tools that could reduce the
length of hospital stay and economic burden. The Would, Ischemia, and Foot
Infection (WIFi) classification system was created as a comprehensive system for
predicting major amputation but is yet to be compared with other systems. Thus,
the objective of this study is to compare the predictive abilities for major
lower limb amputation of WIFi, Wagner and the University of Texas Classification
Systems among diabetic foot patients admitted in a tertiary hospital through a
prospective cohort design.
MATERIALS AND METHODS: Sixty-three diabetic foot patients admitted from June 15,
2019 to February 15, 2020. Methods included one-on-one interview for
clinico-demographic data, physical examination to determine the classification.
Patients were followed-up and outcomes were determined. Pearson Chi-square or
Fisher's Exact determined association between clinico-demographic data, the
classifications, and outcomes. The receiver operating characteristic (ROC) curve
determined predictive abilities of classification systems and paired analysis
compared the curves. Area Under the Receiver Operating Characteristic Curve
(AUC) values used to compare the prediction accuracy. Analysis was set at 95%
CI.
RESULTS: Results showed hypertension, duration of diabetes, and ambulation
status were significantly associated with major amputation. WIFi showed the
highest AUC of 0.899 (p = 0.000). However, paired analysis showed AUC
differences between WIFi, Wagner, and University of Texas classifications by
grade were not significantly different from each other.
CONCLUSION: The WIFi, Wagner, and University of Texas classification systems are
good predictors of major amputation with WIFi as the most predictive.
© 2020 Malaysian Orthopaedic Association (MOA). All Rights Reserved.
DOI: 10.5704/MOJ.2011.018
PMCID: PMC7751999
PMID: 33403071
