ArticleJournal of intensive care2026
Development and validation of VentPilot: an AI-based recommendation system for mechanical ventilation.
Article in Journal of intensive care, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
22 authors.
Funding
Abstract
backgroundMechanical ventilation requires repeated adjustment to changing patient physiology, but consistent individualized management remains challenging. We developed VentPilot, an artificial intelligence-based system for recommending ventilator settings, and evaluated it in multicenter retrospective validation cohorts.
methodsVentPilot was developed using offline reinforcement learning on high-resolution physiologic and ventilator trajectories from Seoul National University Hospital (SNUH), with a reward combining ventilator-free days and intensivist-derived preference feedback. We evaluated VentPilot in an internal validation cohort from SNUH and an external validation cohort from Mayo Clinic. Fitted Q-evaluation assessed the estimated return of VentPilot relative to observed clinician behavior under the prespecified reward function. In a complementary inverse probability-weighted analysis, clinical outcomes were compared between patients with higher versus lower concordance between observed ventilator settings and VentPilot recommendations.
resultsAmong 4296 mechanically ventilated adults, 3002 were included in the derivation cohort, 283 in the internal validation cohort, and 1011 in the external validation cohort. Under the prespecified reward function, fitted Q-evaluation estimated higher returns for VentPilot than for observed clinician behavior in both validation cohorts, with differences in overall reward of 1.6 (95% CI 0.8-2.5) and 1.3 (95% CI 0.6-2.0), respectively. In inverse probability-weighted analyses, higher concordance with VentPilot recommendations was associated with more ventilator-free days within 28 days, with mean differences of 5.0 days (95% CI 2.4-7.6) and 3.1 days (95% CI 1.7-4.6), respectively. Higher concordance was also associated with lower 28-day mortality and shorter ICU length of stay.
conclusionsIn multicenter retrospective validation cohorts, fitted Q-evaluation estimated higher returns for VentPilot than for observed clinician behavior under the prespecified reward function, while greater concordance between observed care and VentPilot recommendations was associated with more favorable clinical outcomes. Further clinical evaluation is warranted to establish VentPilot's safety, usability, and clinical impact.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.