Evidence map›Paper›PMID 42384351›Full record

ArticleIntensive care medicine experimental2026

Behaviour artificial intelligence technology to support the decision-making process of continuation or withdrawal of life-sustaining therapy.

Patrick J Thoral, Jesse de Metz, Stella Mulia, Annebel Ten Broeke, Nicolaas Heyning, Birkitt L Ten Tusscher, Rolf K Gigengack, Hilde M Feijen, Caspar G Chorus, Bas van den Bogaard and 1 more

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Article in Intensive care medicine experimental, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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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.

2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

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No citing paper in PubMed yet.

4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Patrick J ThoralDepartment of Intensive Care Medicine, Center for Critical Care Computational Intelligence, Amsterdam Medical Data Science, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands. p.j.thoral@olvg.nl.ORCID http://orcid.org/0000-0001-6140-7195
Jesse de MetzDepartment of Intensive Care, OLVG, Amsterdam, The Netherlands.
Stella MuliaCouncyl B.V., Delft, The Netherlands.
Annebel Ten BroekeCouncyl B.V., Delft, The Netherlands.
Nicolaas HeyningCouncyl B.V., Delft, The Netherlands.
Birkitt L Ten TusscherDepartment of Intensive Care Medicine, Center for Critical Care Computational Intelligence, Amsterdam Medical Data Science, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
Rolf K GigengackDepartment of Intensive Care Medicine, Center for Critical Care Computational Intelligence, Amsterdam Medical Data Science, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
Hilde M FeijenDepartment of Intensive Care, OLVG, Amsterdam, The Netherlands.
Caspar G ChorusFaculty of Industrial Design Engineering, Delft University of Technology, Delft, The Netherlands.
Bas van den BogaardDepartment of Intensive Care, OLVG, Amsterdam, The Netherlands.
Paul W G ElbersDepartment of Intensive Care Medicine, Center for Critical Care Computational Intelligence, Amsterdam Medical Data Science, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWithholding and withdrawing life-sustaining therapy (LST) is common in European ICUs but significant variations exist. Behaviour artificial intelligence technology (BAIT) may help standardize the ethical dilemma to continue or withdraw LST for patients already admitted to the ICU.

methodsSeveral sessions with intensivists of an academic medical centre and a large urban teaching hospital were held to determine the criteria influencing the process. A discrete choice experiment was conducted during which 25 hypothetical cases were presented to the participants. For each case the participants had to decide whether they would continue, continue with a time limited trial of one week, or withdraw LST. The results of the experiment were used to develop a multinomial logistic regression model that was incorporated in a web-based decision-support system.

resultsThirty-six participants (intensivists and fellows in intensive care medicine) completed the experiment. The estimated model consisted of twelve covariates and showed good model fit (McFadden's ρ

conclusionsWe developed a BAIT system that may support clinicians facing the dilemma of continuing or withdrawing LST by elucidating the key criteria involved in assessing medical futility.

Indexed as

Behaviour artificial intelligenceDecision supportEnd of life careExpert systemsTreatment withdrawal

Identifiers

PMID42384351
PMCPMC13323472

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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.