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Predicting the Path to Attrition: Multidomain Risk Assessment in Diabetic Foot Ulcer Offloading Randomized Controlled
Aminreza Khandan1, Mohammad Dehghan Rouzi1, David G Armstrong2
1Department of Surgery, Center for Advanced Surgical and Interventional Technology, David Geffen School of Medicine, University of California, Los Angeles, CA.
Objective:
To test whether measured baseline wound, functional, and psychosocial metrics predict attrition from a diabetic foot ulcer randomized controlled trial (RCT) using an offloading device.
Research Design And Methods:
In a 12-week RCT, participants were randomized to removable, removable plus education, or smart removable (feedback-enabled) boots. A secondary analysis projected baseline variables onto a unified attrition-risk scale using a normalization framework and radar visualization, with higher values indicating greater risk. Multivariable logistic regression estimated predictors; discrimination was assessed using the receiver operating characteristic area under the curve (AUC).
Results:
Of 210 participants, 76 (36%) withdrew or were lost to follow-up. Slower gait (odds ratio [OR] 1.16) and higher depressive symptoms (OR 1.52) independently predicted attrition. Integrated smart boot metrics demonstrated strong discrimination (AUC 0.81).
Conclusions:
Baseline clinical, functional, and psychosocial variables, integrated through risk-normalized radar visualization, may guide retention strategies. Lower withdrawal in the smart boot group may reflect reinforcement through real-time adherence reminders.
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