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Development of Machine Learning Models for the Prediction of Complications After Colonic, Colorectal and Small Intestine Anastomosis in Psychiatric and Non-psychiatric Patient Collectives (P-Study)

NCT05257863 · Status: UNKNOWN · Type: OBSERVATIONAL · Enrollment: 10000

Last updated 2023-05-09

No results posted yet for this study

Summary

Our study aims to lay the basis for a predictive modeling service for postoperative complications and prolonged hospital stay in patients suffering from psychiatric diseases undergoing colorectal surgery.

Furthermore, we aim to investigate the impact of preoperative Risk factors, psychiatric and psychosomatic diseases on the outcomes of colorectal surgery and the complications after colorectal surgeries like anastomosis insufficiency via predictive modeling techniques

The service mentioned above will be publicly available as a web-based application

Conditions

  • Postoperative Complications
  • Psychosomatic Disorder
  • Psychiatric Disorder
  • Cancer
  • Diverticulitis
  • Morbus Crohn
  • Colitis Ulcerosa
  • Anastomotic Leak
  • Anastomotic Complication
  • Small Intestine Anastomotic Leak

Sponsors & Collaborators

  • University of Basel

    collaborator OTHER

  • University of Hamburg-Eppendorf

    collaborator OTHER

  • Dr. Med Anas Taha

    lead OTHER

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2022-05-01
Primary Completion
2023-12-31
Completion
2023-12-31

Countries

  • Switzerland

Study Locations

More Related Trials

Entities

Diseases

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 NCT05257863 on ClinicalTrials.gov