Pain Mapping as a Predictive Model for Diagnosis and Treatment in Foot and Ankle Conditions

Abstract

Category: Other; Ankle; Ankle Arthritis; Bunion; Hindfoot; Lesser Toes; Midfoot/Forefoot Introduction/Purpose: With the COVID19 pandemic, virtual consultations are becoming a necessity. Clinicians are having to adapt consultations to determine where patients' symptoms are, and what the appropriate next line of investigation or treatment should be, without the benefit of traditional face-to-face contact. The aim of this project was therefore to use pain mapping in foot and ankle conditions, in order to see if there was a predictive correlation between certain symptomatic areas and the ultimate surgical treatment required by patients. Methods: Data was collected prospectively from patients attending foot and ankle clinics from 2014 to 2019, and this was cross- matched with operative data subsequently. Data included patient demographics, co-morbidities, smoking status and previous injuries or surgeries. In a structured questionnaire, patients also marked the regions of the foot and ankle that they thought were the most symptomatic. The foot and ankle was divided into 12 segments for the purpose of analysis. Results: A total of 2007 patients completed these questionnaires, from which operative data was available for 407 patients. In the first instance, data was analysed for 122 patients who underwent one of five specific procedures. Pain mapping was found to have a good predictive value for first MTP fusion and bunion surgery (n=20, 46), 1st metatarsal cheilectomy (n=10) and arthroscopic ankle arthrodesis (n=23). The least predictive pain mapping was seen for patients who had a triple arthrodesis (n=23), with those patients presenting with pain more globally in the foot and ankle. Conclusion: The results suggest that pain mapping can be used effectively as postal questionnaires, prior to a virtual consultation, as an aid to predict diagnosis and the ultimate treatment required in some specific foot and ankle conditions.