Predicting complete finger extension in Dupuytren's disease

Abstract

Multiple studies have reported the effectiveness of treatment on contracture reduction in Dupuytren's disease. However, very few studies have attempted to quantify to which extent patient and disease characteristics influence the chance of achieving a straight finger after surgery. Therefore, the aim of this study is to explore to which extent pre-operative patient and disease characteristics can reliably predict a straight finger after surgery for Dupuytren's disease. In total, 812 and 281 patients, who underwent a limited fasciectomy or needle fasciotomy, respectively, were included in the final analyses. Analysis was performed using a logistic modeling framework. For both treatments, the combination of the extension deficit at baseline; which finger is most affected, which joint is most affected, and the number of affected fingers provided reliable predictions. Classical patient characteristics, such as age and sex, had no additional predictive value. The models presented in this study provide reliable predictions and could be helpful in informing patients and managing their expectations.

Keywords: Dupuytren's disease; Goniometry; Prediction; Treatment outcome.