Trial reportDiabetes care2026
Predicting the Path to Attrition: Multidomain Risk Assessment in Diabetic Foot Ulcer Offloading Randomized Controlled Trials.
Trial report in Diabetes care, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
objectiveTo 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
methodsIn 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).
resultsOf 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).
conclusionsBaseline 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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