AI Algorithm for Surveillance of Deep Surgical Site Infections After Elective Colorectal Surgery.

NCT07130656 | Recruiting

• 1 other identifier: Infect-IA-2
• Study Type: observational
• Target: 1,200
• Locations: 1 country
• Sites: 1

Brief Summary

Epidemiological surveillance is one of the eight core components of the World Health Organization Infection Prevention and Control Programmes. These include surveillance programmes for surgical site infection (SSI). At present, for SSI surveillance, infection control teams perform a manual time-consuming work, which could make a transition to automated surveillance leveraging the new information technology. The aim of this study was to evaluate the performance of a novel algorithm to detect SSI in a cohort of elective colorectal surgery patients who have been previously screened within a nationwide healthcare-associated infection surveillance system.

Conditions

Surgical Site Infection

Keywords

Surgical Site Infection; Surveillance; Articicial inteligence; Algorithms

Outcome Measures

Primary Outcomes (1)

• Rate of surgical site infection

  Rate of Surgical site infection according to the definitions of the CDC-NHSN (Centers for Disease Control and Prevention-National Healthcare Safety Network)

  30 days

Study Arms (2)

Patients assessed for SSI using the standard manual surveillance method

Patients undergoing colorectal surgery enrolled in the nationwide SSI surveillance programme and assessed for SSI using the standard manual surveillance method.

Diagnostic Test: Diagnosis of SSI

Patients assessed for SSI by an algorithm

Patients undergoing colorectal surgery enrolled in the nationwide SSI surveillance programme and assessed for SSI using the new algorithm

Diagnostic Test: Diagnosis of SSI

Interventions

Diagnosis of SSI DIAGNOSTIC_TEST

Diagnosis of SSI by manual system in colorectal surgery procedures enrolled in the SSI surveillance programme.

Patients assessed for SSI by an algorithm; Patients assessed for SSI using the standard manual surveillance method

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Patients undergoing elective colorectal surgery in Hospital General de Granollers in the period 2010-2023

You may qualify if:

• Elective colorectal resection

You may not qualify if:

• Emergency surgery
• Infection present at operation
• Previous intestinal stoma

Sponsors & Collaborators

• Hospital de Granollers: lead

Study Sites (1)

Hospital General de Granollers

Granollers, Barcelona, 08402, Spain

RECRUITING

Related Publications (1)

• Casanova-Portoles D, Badia JM, Forero CG, Sanchez-Martinez N, Romero M, Alonso-Solis T, Limon E, Pujol M, Sancho J. A structured-data algorithm for semiautomated surveillance of surgical site infection after colorectal surgery: A diagnostic accuracy study. J Infect Public Health. 2026 Jan 15;19(4):103151. doi: 10.1016/j.jiph.2026.103151. Online ahead of print.

  PMID: 41637931 DERIVED

MeSH Terms

Conditions

Surgical Wound Infection

Condition Hierarchy (Ancestors)

Wound Infection; Infections; Postoperative Complications; Pathologic Processes; Pathological Conditions, Signs and Symptoms

Study Officials

• Diana Navarro, PhD

  Hospital General de Granollers

  STUDY CHAIR

Central Study Contacts

Josep M Badia, MD, PhD

CONTACT

670702099; jmbadiaperez@gmail.com

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: RETROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Prof

Study Record Dates

• First Submitted: August 12, 2025
• First Posted: August 19, 2025
• Study Start: January 15, 2025
• Primary Completion: August 30, 2025
• Study Completion: October 30, 2025
• Last Updated: August 24, 2025

Record last verified: 2025-08

Data Sharing

• IPD Sharing: Will not share

Locations

ES (1)