Evidence map›Paper›PMID 41225646›Full record

ReviewCritical care (London, England)2025

Opportunities, challenges and future perspectives for target trial emulation in critical care clinical research.

Carmen A T Reep, Evert-Jan Wils, Leo Heunks

Abstract readReview
In one paragraph

Review in Critical care (London, England), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. 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

3 authors.

Carmen A T ReepDepartment of Intensive Care, Erasmus Medical Center, Rotterdam, The Netherlands.
Evert-Jan WilsDepartment of Intensive Care, Franciscus Gasthuis & Vlietland, Rotterdam, The Netherlands.
Leo HeunksDepartment of Intensive Care, Radboud University Medical Center, Nijmegen, The Netherlands. Leo.Heunks@radboudumc.nl.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Target trial emulation (TTE) is a powerful framework for addressing causal questions using observational data. By explicitly designing analyses to mimic a hypothetical randomized trial, TTE enables researchers to more precisely define their research questions, leading to more clinically meaningful conclusions. Its forward-looking design also helps limit common biases, such as immortal time bias and selection bias. Understanding TTE principles is essential not only for researchers working with observational data but also for clinicians who aim to critically interpret the growing number of TTE studies, as well as studies addressing causal questions without explicit use of the TTE framework. In this review, using the timing of switch from controlled to assisted ventilation as a key example, we outline the core assumptions underpinning valid causal inference in TTE: consistency, conditional exchangeability, and positivity. We discuss practical challenges in dynamic critical care settings, including defining a meaningful time zero, handling grace periods, and selecting and properly adjusting for confounders. We also discuss caveats, such as TTE's applicability to non-modifiable interventions, limited applicability for intention-to-treat effects, and the need for high-resolution longitudinal data. Finally, we provide a visual summary linking each trial component to key indicators of high-quality emulation.

Indexed as

Biomedical ResearchCritical CareResearch DesignHumansRandomized Controlled Trials as TopicCausal inferenceCritical careObservational dataTarget trial emulation

Identifiers

PMID41225646
PMCPMC12613904

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.