Evidence map›Paper›PMID 41796383›Full record

ReviewCritical care (London, England)2026

Reporting practices and impact of withdrawal of life-sustaining treatment on outcomes in acute brain injury clinical trials: a literature review and simulation study.

Shaurya Taran, Jeffrey M Singh, Christopher J Yarnell, Victoria A McCredie, Damon C Scales, Niall D Ferguson, Kuan Liu, Neill K J Adhikari

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Critical care (London, England), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

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

8 authors.

Shaurya TaranDepartment of Medicine, University Health Network, Toronto, ON, Canada. shaurya.taran@mail.utoronto.ca.ORCID http://orcid.org/0000-0001-7639-0365
Jeffrey M SinghDepartment of Medicine, University Health Network, Toronto, ON, Canada.
Christopher J YarnellDepartment of Critical Care Medicine and Research Institute, Scarborough Health Network, Toronto, Canada.
Victoria A McCredieDepartment of Medicine, University Health Network, Toronto, ON, Canada.
Damon C ScalesInterdepartmental Division of Critical Care Medicine, University of Toronto, Toronto, ON, Canada.
Niall D FergusonDepartment of Medicine, University Health Network, Toronto, ON, Canada.
Kuan Liu *Institute of Health Policy, Management, and Evaluation, University of Toronto, Toronto, ON, Canada.
Neill K J Adhikari *Interdepartmental Division of Critical Care Medicine, University of Toronto, Toronto, ON, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWithdrawal of life-sustaining treatment (WLST) is common in clinical trials of patients with acute brain injuries (ABI), but current reporting practices and impact on trial-reported findings are unclear. We evaluated reporting practices of WLST in contemporary clinical trials of patients with ABI and quantified the magnitude of bias on treatment effect estimates in hypothetical trials.

methodsWe conducted a literature review of contemporary ABI randomized clinical trials and a simulation-based analysis. In the literature review, we included two-arm, randomized, superiority trials of adults with ABI (traumatic brain injury, intracranial hemorrhage, subarachnoid hemorrhage, ischemic stroke, or post-cardiac arrest brain injury) published in 10 high-impact journals from January 1, 2015 to December 19, 2024. We extracted WLST characteristics including frequency, timing, reasons, and neuro-prognostication criteria. In the simulation-based analysis, we evaluated the impact of WLST misclassification-defined as WLST occurring in patients who could have survived with a good neurological outcome-on observed treatment effects. For each scenario, we estimated the observed treatment effect after misclassification and calculated bias as the difference between observed and true treatment effects. We assessed both blinded and unblinded trials and binary and ordinal neurologic outcomes.

resultsAmong 69 trials included in the literature review, 17 trials (24.6%) reported WLST frequency, 9 (13.0%) timing, 10 (14.5%) reasons, and 7 (10.1%) standardized neuro-prognostication criteria. In simulations of blinded trials, WLST misclassification consistently attenuated observed treatment effects. Increasing the fraction of misclassified WLST events led to progressively greater bias, making beneficial treatments appear less effective and harmful treatments appear less harmful. In unblinded trial simulations, the direction of bias varied by the magnitude of the true treatment effect and degree of misclassification. Findings were similar for binary and ordinal neurologic outcomes. Across all simulations, WLST misclassification reversed statistical conclusions in a median of 22.1% (interquartile range 17.4-32.4%) of trials.

conclusionsWLST is poorly reported in contemporary ABI trials. Misclassification of WLST-related deaths leads to important bias in trial-reported treatment effects, potentially yielding underpowered studies and erroneous trial conclusions. Standardized, transparent WLST reporting is essential to strengthen ABI trial design and interpretation.

Indexed as

Brain InjuriesWithholding TreatmentHumansRandomized Controlled Trials as TopicTreatment OutcomeAcute brain injuryBiasRandomized clinical trialsWithdrawal of life-sustaining treatment

Identifiers

PMID41796383
PMCPMC13081334

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.