AI Algorithm for Surveillance of Deep Surgical Site Infections After Elective Colorectal Surgery.
NCT ID: NCT07130656
Last Updated: 2025-08-24
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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RECRUITING
1200 participants
OBSERVATIONAL
2025-01-15
2025-10-30
Brief Summary
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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.
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Detailed Description
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Epidemiological surveillance is one of the eight core components of the World Health Organization (WHO) Infection Prevention and Control Programmes. These include surveillance programmes for surgical site infection (SSI), which have proven to be effective in all types of surgery and in a variety of settings.
For a programme to be effective, surveillance for HCAIs must be active, prospective and continuous, comprising a surveillance period up to 30-90 days post-intervention, to cover the high rate of SSIs detected after discharge.
At present, infection control teams perform a manual, prospective, time-consuming and almost artisanal work, which should make a transition to automated or semi-automated surveillance that leverages the possibilities offered by today\'s information technology.
The evolution of surveillance systems should benefit from this new possibilities offered by artificial intelligence, allowing automated detection of suspected SSI adverse events from clinical course text, microbiology reports or coding of diagnoses, procedures, complications and readmissions.
The aim of this study was to evaluate the performance of a novel algorithm to detect to detect SSI at its three anatomical levels, in a cohort of elective colorectal surgery patients who have been previously screened within a nationwide healthcare-associated infection surveillance system.
Conditions
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Study Design
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COHORT
RETROSPECTIVE
Study Groups
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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.
Diagnosis of SSI
Diagnosis of SSI by manual system in colorectal surgery procedures enrolled in the SSI surveillance programme.
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
Diagnosis of SSI
Diagnosis of SSI by manual system in colorectal surgery procedures enrolled in the SSI surveillance programme.
Interventions
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Diagnosis of SSI
Diagnosis of SSI by manual system in colorectal surgery procedures enrolled in the SSI surveillance programme.
Eligibility Criteria
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Inclusion Criteria
Exclusion Criteria
* Infection present at operation
* Previous intestinal stoma
18 Years
ALL
No
Sponsors
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Hospital de Granollers
OTHER
Responsible Party
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Josep M Badia
Prof
Principal Investigators
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Diana Navarro, PhD
Role: STUDY_CHAIR
Hospital General de Granollers
Locations
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Hospital General de Granollers
Granollers, Barcelona, Spain
Countries
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Central Contacts
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Facility Contacts
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Other Identifiers
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Infect-IA-2
Identifier Type: -
Identifier Source: org_study_id
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