Evidence map›Paper›PMID 40425394›Full record

Observational studyBritish journal of anaesthesia2025

Directed acyclic graphs to minimise bias and optimise causal inference in SNAP-3: an observational cohort study of frailty, multimorbidity, and delirium in older surgical patients.

Claire J Swarbrick, Helen A Blake, Peter Martin, Judith S L Partridge, Iain K Moppett

Abstract readObservational Study
PubMed Full text at PMC Publisher
In one paragraph

Observational study in British journal of anaesthesia, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Observational
  2. Article
  3. Observational
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

5 authors.

Claire J SwarbrickAnaesthesia & Critical Care, Injury, Recovery and Inflammation Sciences, University of Nottingham, Nottingham, UK; Centre for Research and Improvement, Royal College of Anaesthetists, London, UK; Royal Devon University Healthcare NHS Foundation Trust, Exeter, UK. Electronic address: Claire.swarbrick@nottingham.ac.%20uk.
Helen A BlakeDepartment of Primary Care and Population Health, University College London, London, UK.
Peter MartinDepartment of Primary Care and Population Health, University College London, London, UK.
Judith S L PartridgePerioperative medicine for Older People undergoing Surgery (POPS), Guy's and St Thomas' NHS Foundation Trust, London, UK; School of Population Health & Environmental Sciences, Faculty of Life Sciences and Medicine, King's College Hospital, London, UK.
Iain K MoppettAnaesthesia & Critical Care, Injury, Recovery and Inflammation Sciences, University of Nottingham, Nottingham, UK; Centre for Research and Improvement, Royal College of Anaesthetists, London, UK; Royal Devon University Healthcare NHS Foundation Trust, Exeter, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe 3rd Sprint National Anaesthesia Project (SNAP-3) aims to describe the impact of frailty, multimorbidity, and delirium, and their management, on outcomes after surgery within the older surgical population. Causal diagrams, such as directed acyclic graphs (DAGs), are a useful tool for visually representing relationships between variables and for clarifying the causal assumptions underlying a chosen statistical model.

methodsA description of how the SNAP-3 cohort study's DAGs were developed is provided. DAGs have been created for the exposure-outcome relationships between frailty, multimorbidity, and delirium (as an exposure) with postoperative outcomes (length of hospital stay, delirium, morbidity, mortality). DAGs were created following the approach of 'Evidence synthesis for constructing directed acyclic graphs', and revised after independent clinical expert input.

resultsDAGs provide visual representations of assumptions made, and provide an objective approach to appropriate statistical adjustments. Key nodes within all the DAGs included age, dementia, genetic predisposition, hearing and visual impairment, length of stay, malignancy, operative severity, polypharmacy, postoperative perioperative medicine service, preoperative clinic review, sex, social deprivation, urgency, with delirium, frailty, multimorbidity, interaction, morbidity acting as exposures, or outcomes in certain DAGs.

conclusionsDAGs provide a transparent framework for statistical decision-making in observational research. We provide an overview of DAGs using the SNAP-3 DAGs as examples to explain fundamental concepts for developing and using causal diagrams. This overview acknowledges the complexities of exploring clinical relationships and the assumptions that are necessary, providing an opportunity for critique of the relationships described and refinements for future studies.

Indexed as

DeliriumFrailtyMultimorbidityPostoperative ComplicationsAgedAged, 80 and overBiasCohort StudiesFemaleFrail ElderlyHumansLength of StayMaledirected acyclic graphsepidemiologyfrailty syndromegeriatric medicinemultimorbidityperioperative caresurgery

Identifiers

PMID40425394
PMCPMC12226740

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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.