Real-time prediction of ventilator-associated pneumonia onset in ICU: development of a dynamic machine learning model

We present a real-time VAP prediction model that outperforms static classifiers, providing actionable lead time for proactive microbiological surveillance. The model enables risk stratification for enhanced monitoring and, when clinically indicated, timely targeted antimicrobial therapy. Future work will focus on multicenter prospective validation and integration into ICU workflows to assess clinical utility and impact on patient outcomes.

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Publication Details

Journal
Journal of Anesthesia Analgesia and Critical Care
Published
2026-01-13
DOI
https://doi.org/10.1186/s44158-025-00313-3
Primary Topic
Sepsis Diagnosis and Treatment
Type
article
Field-Weighted Citation Impact
0.00
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article

Real-time prediction of ventilator-associated pneumonia onset in ICU: development of a dynamic machine learning model

Andrea Ancona, Lucrezia Rovati, Francesca Alfieri, Simone Zappalá et al.
Journal of Anesthesia Analgesia and Critical Care
Sepsis Diagnosis and Treatment
article

Real-time prediction of ventilator-associated pneumonia onset in ICU: development of a dynamic machine learning model

Andrea Ancona, Lucrezia Rovati, Francesca Alfieri, Simone Zappalá, Amedeo Guzzardella, Giacomo Grasselli, Vittorio Scaravilli
article en

Abstract

We present a real-time VAP prediction model that outperforms static classifiers, providing actionable lead time for proactive microbiological surveillance. The model enables risk stratification for enhanced monitoring and, when clinically indicated, timely targeted antimicrobial therapy. Future work will focus on multicenter prospective validation and integration into ICU workflows to assess clinical utility and impact on patient outcomes.

Journal of Anesthesia Analgesia and Critical CareVol. 6(1)
University of Milan (IT), Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico (IT), Department of Medical Sciences (BY), University of Milano-Bicocca (IT)
Good health and well-being
Openalex Percentile: Top 89%
Sepsis Diagnosis and Treatment
DOIOpen Access PDFOpenAlex
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Real-time prediction of ventilator-associated pneumonia onset in ICU: development of a dynamic machine learning model — Andrea Ancona, Lucrezia Rovati, et al. · Journal of Anesthesia Analgesia and Critical Care (2026) | TGRS Research Map | TGRS