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Predicting drop-out in early-stage Type 1 Diabetes clinical trials to improve retention through Personalized Engagement Strategies
Background: Patient non-adherence and drop-out increase the time and cost of clinical trials. A tool that predicts, at…
Improving Precision of Clinical Trials Results in T1 Diabetes with Transferrable Prognostic Models
Background: In randomized controlled trials (RCTs), assay sensitivity issues can affect both statistical power and the confidence in…
Predicting Patient Drop-Out in Clinical Trials: A First Step Toward Personalized Engagement Strategies
Objective: Patient non-adherence and drop-out significantly extend the duration and cost of clinical trials. A predictive tool identifying…
Prediction of the response to repetitive transcranial magnetic stimulation of the motor cortex in peripheral neuropathic pain and validation of a new algorithm
Abstract: Motor cortex repetitive transcranial magnetic stimulation (M1-rTMS) induces analgesic effects in neuropathic pain, but not all patients…
Self-Training in Pain Assessment as a Mediator of the Prognostic Performance of Pain Variability
Background and Aims Baseline Pain Variability (PV) is often cited as a key predictor of placebo response (1-3)….
MODELING THE EXPECTATIONS FOR IMPROVEMENT IN OSTEOARTHRITIS TRIALS TO ENHANCE MANAGEMENT STRATEGIES
Objective: The expectations of improvement among subjects participating in a Randomized Controlled Trials (RCT) are one of the…
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