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NCT05718999: XGB&IncHern

XGBoost for Predict Incisional Hernia

Status unknown Last updated 27 February 2023
What this trial tests

trial testing Not intervention in Incisional Hernia in 1,000 participants. Status unknown.

Timeline
30 January 2023
Primary endpoint
22 February 2023
30 November 2023

Quick facts

Lead sponsorHospital Regional de Alta Especialidad del Bajio
StatusStatus unknown
Study typeOBSERVATIONAL
Enrollment1,000
Start date30 January 2023
Primary completion22 February 2023
Estimated completion30 November 2023
Sites1 location across Mexico

Drugs / interventions tested

Conditions studied

Sponsor

Hospital Regional de Alta Especialidad del Bajio

Who can join

Adults 18 to 80, any sex, with Incisional Hernia. Patients with the condition only — healthy volunteers not accepted.

Sponsor's own description

The objective of this study is to develop a predictive model of IH based on machine learning with the use of the XGBoost technique, this will help surgeons in charge of abdominal wall closure to have objective support to determine high-risk patients and in them modify the closure technique or use a mesh according to their choice or the degree of contamination of the abdominal cavity.

Publications & conference data

1 peer-reviewed publication reference this trial (live from Europe PMC):

  1. Incisional hernia prediction using machine learning models.
    Lozada-Hernández EE, Ramirez-DelReal TA, Salazar-Colores S, Armenta-Medina D. · · 2026 · PMID 41761228 · DOI 10.1186/s12911-026-03382-8

Verify or expand the search:

Other recruiting trials for Incisional Hernia

Currently open trials in the same condition.

Other Hospital Regional de Alta Especialidad del Bajio trials

Trials by the same sponsor.

Verify against primary sources

Data sources for this page

Drug Landscape aggregates and links these public records for informational use only. Always verify against the primary source before clinical or regulatory decisions. Canonical URL: https://druglandscape.com/trial/NCT05718999.

Primary sources · FDA · ClinicalTrials.gov · EMA · SEC EDGAR · ChEMBL · Wikidata · full sourcing