Clinical Impact of a Machine Learning Decision Support System for Empirical Antibiotic Therapy

Trial statusNot yet recruiting
Trial phaseNot applicable
Trial typeInterventional
Biological sexAll
Age18+
SponsorInstituto de Investigación Sanitaria Gregorio Marañón

About this trial

The goal of this quasi-experimental study is to analyze if a Machine Learning Clinical Decision Support System can improve the empirical antibiotic treatment in patients with pneumonia, urinary tract infection and / or sepsis.

The main questions it aims to answer are:

* Primary outcome: clinical success defined as clinical cure (resolution of all signs and symptoms related to infection); no complications until day 30 (recurrence, or development of adverse events- AEs-); no new acquisition of MDROs; and survival at day 30. * Secondary outcomes: a subgroup analysis of the primary outcome according to the department participants, infectious syndrome, severity of the infection assessed by the SOFA score, and in microbiological confirmed infections. In microbiological confirmed infections, desirability of Outcome Ranking (DOOR) for the Management of Antimicrobial Therapy (MAT) according to the beta-lactam classification

Researchers will compare a pre-intervention group with a post-intervention to see if improve in the DOOR MAT score

Participants in the post-intervention group will:

• Received empirical antibiotic therapy prescribed by their treating physicians according to the machine-learning recommendations

Eligibility criteria

This trial does not accept healthy volunteers

Qualifiers

Adult patients (aged ≥18 years)

Admitted to the Nephrology, Oncology or ICU wards

Diagnosis of sepsis, pneumonia and/or UTI

Empirical antibiotics prescribed

Disqualifiers

informed consent obtained > 48 hours since the infection onset

beta-lactam allergy

infection syndrome other than sepsis, pneumonia or UTI

confirmed no-bacterial infection

Trial design

Design model

Sequential

Treatments tested in this trial

  • Machine Learning Decision Support System

    Other intervention

    iAST® (Pragmatech AI Solutions) is a medical device designed to assist the antibiotic prescription, currently approved by the European Medicines Agency. It used complex algorithms to accurately predict the most likely recommended antibiotics for providing coverage for specific aerobic bacteria before definitive microbiological results, bacterial identification and antibiotic susceptibility testing, were known

Treatment groups

486 Participants
are divided into 2 treatment groups
Group A: Pre-interventionalNo intervention 0 interventions
Group B: InterventionalExperimental treatment 1 intervention

Trial outcomes

Primary outcomes

1

Clinical success

resolution of all signs and symptoms related to infection with no complications and survival

Time frame
30-Day

Secondary outcomes

Other outcomes

Locations

This trial has no locations.

Sponsors and contacts

Click on the lead sponsor to view all of their trials.

This trial is not recruiting at the moment. You can still explore other options: