Evidence map›Paper›PMID 42014230›Full record

ArticleBritish journal of anaesthesia2026

Defining estimands in anaesthesia clinical trials: a scoping review and framework.

Gethmini A Siriwardena, Sarah Luu, Rukshala K Gunaratne, Julie A Simpson, Kate Leslie, Sabine Braat, Anurika P De Silva

Abstract readScoping Review
In one paragraph

Article in British journal of anaesthesia, 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

7 authors.

Gethmini A SiriwardenaCentre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, VIC, Australia.
Sarah LuuDepartment of Critical Care, Melbourne Medical School, University of Melbourne, Melbourne, VIC, Australia; Department of Anaesthesia, Austin Health, Melbourne, VIC, Australia.
Rukshala K GunaratneCentre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, VIC, Australia.
Julie A SimpsonCentre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, VIC, Australia; Nuffield Department of Medicine, University of Oxford, Oxford, UK; Methods and Implementation Support for Clinical and Health (MISCH) Research Hub, University of Melbourne, Melbourne, VIC, Australia.
Kate LeslieDepartment of Critical Care, Melbourne Medical School, University of Melbourne, Melbourne, VIC, Australia; Department of Anaesthesia and Pain Management, Royal Melbourne Hospital, Melbourne, VIC, Australia.
Sabine BraatCentre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, VIC, Australia; Methods and Implementation Support for Clinical and Health (MISCH) Research Hub, University of Melbourne, Melbourne, VIC, Australia.
Anurika P De SilvaCentre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, VIC, Australia; Methods and Implementation Support for Clinical and Health (MISCH) Research Hub, University of Melbourne, Melbourne, VIC, Australia. Electronic address: anurika.de@unimelb.edu.au.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIntercurrent events, such as treatment switching and rescue medication, commonly occur in anaesthesia trials, and can affect the occurrence or interpretation of primary outcomes. The estimand framework provides strategies for handling these events, aligning trial objectives with outcomes.

methodsWe conducted a scoping review of RCTs with ≥100 participants published from January 2020 to June 2024 in ten high-impact journals, including patients receiving anaesthesia before surgery. We examined whether estimands were reported and identified intercurrent events. A structured framework was developed by mapping intercurrent events to intervention-outcome combinations investigated across all included anaesthesia trials.

resultsAmong 139 included trials, none explicitly used the estimand framework, and an estimand could be inferred in only 27 (19%). The primary outcome was defined in all trials, while other attributes were often not inferable: target population (44 [32%]), treatment condition (21 [15%]), summary measure (22 [16%]) and intercurrent event handling (84 [60%]). The most common intercurrent events were not receiving the randomised intervention (64 [46%]), treatment discontinuation (38 [27%]), and treatment switching (27 [19%]). Anaesthesia-related intercurrent events included surgery cancellation (37 [27%]) and non-protocolised anaesthesia management (17 [12%]). Findings informed the development of a structured, interactive web-based tool linking intercurrent events to intervention-outcome combinations, refined by expert review.

conclusionsUse of estimands in anaesthesia trials is limited. Our tool supports structured identification and handling of intercurrent events in anaesthesia trials. Greater collaboration between statisticians and clinicians, with consistent application of the estimand framework, is needed to improve clarity and interpretability of future anaesthesia research.

Indexed as

AnesthesiaRandomized Controlled Trials as TopicResearch DesignHumansanaesthesia clinical trialsclinical trial designestimand frameworkICH E9(R1)intercurrent eventsperioperative medicinerandomised controlled trialscoping review

Identifiers

PMID42014230
PMCPMC13494091

What Socratic 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 Socratic graph.