Material and methods: This prospective cohort study was conducted on 68 patients who underwent surgical management for an unstable ankle injury. Demographic details, fracture type and associated medical comorbidities were recorded. Pre-operative radiographic assessment was done for all patients. At the end of one year follow-up, clinical (American Orthopaedic foot and ankle society-AOFAS and Olerud-Molander ankle - OMAS) scores and radiological parameters were assessed and analysed.
Results: Fracture dislocation (0.008), diabetes mellitus (0.017), level of alchohol consumption (0.008) and pre-operative talocrural angle (TCA) > 100° (0.03) were significant predictors of poor outcomes as per AOFAS. Fracture dislocation (0.029), diabetes mellitus (0.004), pre-operative TCA > 100° (0.009), female gender (0.001), age more than 60 years (0.002) and open injuries (0.034) had significantly poor outcome as per OMAS. Other parameters (smoking, hypertension, classification, syndesmotic injury, medial clear space and tibiofibular overlap) did not affect the outcome significantly.
Conclusion: Our study showed that poor outcome predictors in unstable ankle fractures are age >60 years, female gender, diabetes mellitus, alcohol consumption, fracture dislocation, open fractures and pre-op TCA >100°.
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.