At a glance
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NCT07427927N/AActiveUpdate OverdueUpdated 4mo ago · Completion was 6mo agoData-driven Clustering in Hemorrhoid Surgery: Retrospective Monocentric Study for the Identification of Clinical Phenotypes
In Brief
An observational study evaluating Any surgical procedure for hemorrhoidal disease for Hemorrhoid and Hemorrhoid Prolapse. Active but no longer recruiting, targeting 100 participants across 1 site.
Signals
Detailed Summary
This retrospective, single-center observational study will use routinely collected perioperative data from adults undergoing surgery for symptomatic hemorrhoidal disease to identify data-driven clinical phenotypes. Unsupervised machine learning will be applied to characterize clusters of patients based on demographic, clinical, anatomical, and surgical variables. The study will explore whether the resulting phenotypes differ in operative complexity and postoperative course, and will generate hypotheses to inform future predictive models and personalized surgical planning.
Study Details
Timeline
Interventions
standard hemorrhoidectomy, advanced hemorrhoidectomy, prolapsectomy, Doppler-guided procedures, or combined techniques