Surgical Site InfectionInfect-IA-3NCT06626399
ChatGPT-4 for Surgical Site Infection Detection From Electronic Health Records After Colorectal Surgery.
An observational study of Surgical Site Infection, run by Hospital de Granollers at 1 site in Spain.
Trial 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). Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Surgical Site Infection
- What is being tested?
- Diagnosis of SSI
- How many people
- 1,100 participants
- Where
- 1 siteSpain
- Study dates
- 15 Jan 2025to 30 Nov 2025
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- Adult, Older adult
Study population: Patients undergoing elective colorectal surgery in Hospital General de Granollers in the period 2010-2023
Who may be able to join
- Elective colorectal resection
Who cannot join
- Emergency surgery
- Infection present at operation
- Previous intestinal stoma
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
Spain1 site, 1 recruiting
- Recruiting
Hospital General de Granollers
Granollers, Barcelona, 08402
Josep M Badia, 670702099, jmbadiaperez@gmail.com
About this study
Official title: Evaluation of ChatGPT-4 for the Detection of Surgical Site Infections From Electronic Health Records After Colorectal Surgery: A Diagnostic Accuracy Study.
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.
This study aimed to evaluate the ability of ChatGPT-4o to detect surgical site infection at the three anatomical levels.
Read the detailed description
Healthcare-associated infections (HAIs) have a negative impact on patient health, represent a significant healthcare and economic burden on healthcare systems and are considered the most preventable cause of serious adverse events in hospitalised patients.
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.
This study aims to evaluate the ability of ChatGPT to detect surgical site infections (SSI) at the three anatomical levels described by the CDC.
The study will retrospectively compare the results of the AI chatbot in diagnosing SSI, trained using the US CDC definition criteria, with a large cohort of elective colorectal surgery patients already evaluated through a nationwide nosocomial infection surveillance system, which will be the comparative gold standard.
- Conditions
- Surgical Site Infection
- Being tested
- Diagnosis of SSI
- Keywords
- Surgical site infection, Surveillance, ChatGPT, Natural language processing, Artificial inteligence
- Medical subject headings
- Surgical Wound Infection
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Diagnosis of SSIDiagnostic test
Diagnosis of SSI by manual system in colorectal surgery procedures enrolled in the SSI surveillance programme.
| Study group | Role | What they receive |
|---|---|---|
| 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. Receives: Diagnostic Test: Diagnosis of SSI | |
| Patients assessed for SSI by Open IA's ChatGPT 4 chatbot | Patients undergoing colorectal surgery enrolled in the nationwide SSI surveillance programme and assessed for SSI using the Open IA's ChatGPT 4 chatbot. Receives: Diagnostic Test: Diagnosis of SSI |
What is being measured
The primary outcome is the main question the study is designed to answer.
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)
Measured: 30 days
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted3 Oct 2024
- Study start15 Jan 2025
- Primary completion30 Sep 2025 (estimated)
- Study completion30 Nov 2025 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (1)Papers the sponsor has linked to this study.
- Other trials for Surgical Site InfectionStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Case-control
- Time perspective
- Retrospective
- Enrolment
- 1,100 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Hospital de Granollers
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Josep M Badia, Hospital de Granollers
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06626399
- Sponsor's protocol ID
- Infect-IA-3
- Acronym
- Infect-IA-3
- Status last verified
- Aug 2025
- First submitted
- 2 Oct 2024
- Last updated
- 15 Aug 2025
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Publications
Casanova-Portoles D, Badia JM, Forero CG, Sanchez-Martinez N, Alonso-Solis T, Romero M, Amillo M, Amador-Gil S, Rubies C, Sancho J. Validation of ChatGPT-4o for detecting surgical site infections after colorectal surgery from electronic health records: A large-scale diagnostic accuracy study. Int J Infect Dis. 2026 Jul;168:108705. doi: 10.1016/j.ijid.2026.108705. Epub 2026 Apr 11.
PubMed 41967571
Study at a glance
From the registry record, last updated by the sponsor on 15 Aug 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Evaluation of ChatGPT-4 for the Detection of Surgical Site Infections From Electronic Health Records After Colorectal Surgery: A Diagnostic Accuracy Study.
- ClinicalTrials.gov ID
- NCT06626399
- Acronym / sponsor ID
- Infect-IA-3 / Infect-IA-3
- Conditions
- Surgical Site Infection
- Keywords
- Surgical site infection, Surveillance, ChatGPT, Natural language processing, Artificial inteligence
- Study type
- Observational
- Recruitment status
- Recruiting
- Enrolment
- 1,100 participants (estimated)
- Lead sponsor
- Hospital de GranollersUniversity, hospital or other
- Study start
- 15 Jan 2025 (actual)
- Primary completion
- 30 Sep 2025 (estimated)
- Study completion
- 30 Nov 2025 (estimated)
- First posted
- 3 Oct 2024 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
This study aimed to evaluate the ability of ChatGPT-4o to detect surgical site infection at the three anatomical levels.
Detailed description
Healthcare-associated infections (HAIs) have a negative impact on patient health, represent a significant healthcare and economic burden on healthcare systems and are considered the most preventable cause of serious adverse events in hospitalised patients.
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.
This study aims to evaluate the ability of ChatGPT to detect surgical site infections (SSI) at the three anatomical levels described by the CDC.
The study will retrospectively compare the results of the AI chatbot in diagnosing SSI, trained using the US CDC definition criteria, with a large cohort of elective colorectal surgery patients already evaluated through a nationwide nosocomial infection surveillance system, which will be the comparative gold standard.
Study design
- Observational model
- Case-control
- Time perspective
- Retrospective
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Patients assessed for SSI using the standard manual surveillance method | – | Diagnostic Test: Diagnosis of SSIPatients undergoing colorectal surgery enrolled in the nationwide SSI surveillance programme and assessed for SSI using the standard manual surveillance method. |
| Patients assessed for SSI by Open IA's ChatGPT 4 chatbot | – | Diagnostic Test: Diagnosis of SSIPatients undergoing colorectal surgery enrolled in the nationwide SSI surveillance programme and assessed for SSI using the Open IA's ChatGPT 4 chatbot. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Age groups
- Adult, Older adult
- Study population
- Patients undergoing elective colorectal surgery in Hospital General de Granollers in the period 2010-2023
Key inclusion criteria (1 listed)
- Elective colorectal resection
Key exclusion criteria (3 listed)
- Emergency surgery
- Infection present at operation
- Previous intestinal stoma
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Diagnosis of SSIDiagnosis of SSI by manual system in colorectal surgery procedures enrolled in the SSI surveillance programme. | Diagnostic test | Patients assessed for SSI by Open IA's ChatGPT 4 chatbot, Patients assessed for SSI using the standard manual surveillance method |
Primary outcome
Rate of surgical site infection
Time frame: 30 days
Rate of Surgical site infection according to the definitions of the CDC-NHSN (Centers for Disease Control and Prevention-National Healthcare Safety Network)
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 15 Aug 2025.
- Derived from this study: PubMed 41967571Casanova-Portoles D, Badia JM, Forero CG, Sanchez-Martinez N, Alonso-Solis T, Romero M, Amillo M, Amador-Gil S, Rubies C, Sancho J. Validation of ChatGPT-4o for detecting surgical site infections after colorectal surgery from electronic health records: A large-scale diagnostic accuracy study. Int J Infect Dis. 2026 Jul;168:108705. doi: 10.1016/j.ijid.2026.108705. Epub 2026 Apr 11.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Surgical Site Infection, run by Hospital de Granollers at 1 site in Spain.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 1 inclusion and 3 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: looking for participants now, as of the sponsor's last update on 15 Aug 2025. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Spain. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Josep Badia, MD, PhD (670702099, jmbadiaperez@gmail.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Rate of surgical site infection (time frame: 30 days). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT06626399, which also lists 1 linked publication.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 15 Aug 2025.