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Evaluation of the Artificial Intelligence-based Prescription Support Software iAST® for the Choice of Empirical and Semi-targeted Antibiotic Treatment

NCT06174519 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 325

Last updated 2023-12-22

No results posted yet for this study

Summary

Inadequate treatment of infections frequently leads to complications that cause new visits to the doctor, lengthen hospital stays and can lead to sepsis, even causing the death of affected patients. Several scientific studies have documented that up to 20%-30% of antibiotic prescriptions are incorrect and do not cover the microorganism causing the infection. iAST® is a simple antibiotic prescribing aid tool that applies complex algorithms based on the latest artificial intelligence technologies to accurately predict the best specific antibiotic for a patient, before knowing the definitive microbiological results (bacterial identification and antibiogram). The objective of the present trial is to demonstrate the non-inferiority of iAST® with respect to physicians for the appropriate choice of empiric and semi-directed therapy of common infectious diseases, including sepsis, urinary tract infections and ventilator-associated pneumonias or tracheobronchitis. The adequacy of the medical prescription and the iAST® prediction will be compared taking the antibiogram report as a reference. The study design is retrospective, so that no intervention will be done on the patients. The investigators will conduct a retrospective search for infection cases and note the antibiotic treatment prescribed by the doctors. In parallel, they will enter basic patient data such as age, sex, service where they were treated, type of infection and microorganism (in the case of semi-directed treatment evaluation) into the iAST® software and will write down the first three treatment options recommended by the tool. The treatments of both arms (medical treatment and iAST® prediction) will be compared with the microbiological results and the success rate of each of them will be calculated.

Conditions

Interventions

DEVICE

Medical device simulation

For the subjects included, investigators used the iAST® tool to predict which antibiotics would have been recommended as the top three choices both for empiric and semi-targeted therapy and recorded this data with the percentage of coverage predicted (the first three antibiotics in the iAST® ranking that have been tested in the antibiogram of the center where the study was carried were chosen). Investigators checked the final microbiological reports and logged if the recovered bacteria were susceptible to the drug prescribed by doctors and simulated by the iAST® tool according to the final antibiogram results.

Sponsors & Collaborators

  • NAMSA

    collaborator OTHER

  • Grupo Hospital de Madrid

    collaborator OTHER

  • Pragmatech AI Solutions

    lead INDUSTRY

Principal Investigators

  • José Barberán, MD, PhD · Grupo HM Hospitales

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2023-08-01
Primary Completion
2023-12-01
Completion
2023-12-01

Countries

  • Spain

Study Locations

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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 NCT06174519 on ClinicalTrials.gov