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Data-driven Clustering in Hemorrhoid Surgery: Retrospective Monocentric Study for the Identification of Clinical Phenotypes

NCT07427927 · Status: ENROLLING_BY_INVITATION · Type: OBSERVATIONAL · Enrollment: 100

Last updated 2026-08-27

No results posted yet for this study

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.

Conditions

  • Hemorrhoid
  • Hemorrhoid Prolapse

Interventions

PROCEDURE

Any surgical procedure for hemorrhoidal disease

standard hemorrhoidectomy, advanced hemorrhoidectomy, prolapsectomy, Doppler-guided procedures, or combined techniques

Sponsors & Collaborators

  • IRCCS Policlinico S. Donato

    lead OTHER

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2024-12-01
Primary Completion
2025-12-31
Completion
2026-12-31

Countries

  • Italy

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07427927 on ClinicalTrials.gov