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

August 8, 2026 updated by: Sofia De La Villa, Instituto de Investigación Sanitaria Gregorio Marañón

Clinical Impact of a Machine Learning Decision Support System for Empirical Antibiotic Therapy: A Prospective Quasi-Experimental Study

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

Study Overview

Status

Not yet recruiting

Conditions

Intervention / Treatment

Study Type

Interventional

Enrollment (Estimated)

486

Phase

  • Not Applicable

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

No

Description

Inclusion Criteria:

  • Adult patients (aged ≥18 years)
  • Admitted to the Nephrology, Oncology or ICU wards
  • Diagnosis of sepsis, pneumonia and/or UTI
  • Empirical antibiotics prescribed

Exclusion Criteria:

  • informed consent obtained > 48 hours since the infection onset
  • beta-lactam allergy
  • infection syndrome other than sepsis, pneumonia or UTI
  • confirmed no-bacterial infection
  • death within the first 48 hours of inclusion or imminent risk of death at time of the inclusion
  • pregnancy and/or breastfeeding
  • inclusion in a clinical trial of antimicrobial treatment

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: Treatment
  • Allocation: Non-Randomized
  • Interventional Model: Sequential Assignment
  • Masking: None (Open Label)

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
No Intervention: Pre-interventional
Hospital standard practices for diagnosis and/or treatment applied
Experimental: Interventional
Hospital standard practices + use of a CDSS tool
Other: Machine Learning Decision Support System
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

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Clinical success
Time Frame: 30-Day
resolution of all signs and symptoms related to infection with no complications and survival
30-Day

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Instituto de Investigación Sanitaria Gregorio Marañón

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Estimated)

September 1, 2026

Primary Completion (Estimated)

August 1, 2027

Study Completion (Estimated)

September 1, 2027

Study Registration Dates

First Submitted

August 5, 2026

First Submitted That Met QC Criteria

August 8, 2026

First Posted (Actual)

August 13, 2026

Study Record Updates

Last Update Posted (Actual)

August 13, 2026

Last Update Submitted That Met QC Criteria

August 8, 2026

Last Verified

August 1, 2026

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

  • MICRO.HGUGM.2026-003

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

UNDECIDED

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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