Evidence map›Paper›PMID 37318517›Full record

Observational studyEuropean journal of trauma and emergency surgery : official publication of the European Trauma Society2023

Patterns of computed tomography utilisation in injury management: latent classes approach using linked administrative data in Western Australia.

Ninh T Ha, Mark Harris, Max Bulsara, Jenny Doust, Sviatlana Kamarova, Donald McRobbie, Peter O'Leary, Paul M Parizel, John Slavotinek, Cameron Wright and 2 more

Abstract readObservational Study
In one paragraph

Observational study in European journal of trauma and emergency surgery : official publication of the European Trauma Society, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

12 authors.

Ninh T HaHealth Economics and Data Analytics, Curtin School of Population Health, Faculty of Health Sciences, Curtin University, GPO Box U1987, Perth, WA, 6845, Australia. thi.ha@curtin.edu.au.ORCID http://orcid.org/0000-0002-2789-5604
Mark HarrisSchool of Accounting, Economics and Finance, Faculty of Business and Law, Curtin University, Perth, Western Australia, Australia.
Max BulsaraInstitute for Health Research, University of Notre Dame, Fremantle, WA, Australia.
Jenny DoustAustralian Women and Girls' Health Research Centre, School of Public Health, University of Queensland, Brisbane, Australia.
Sviatlana KamarovaHealth Economics and Data Analytics, Curtin School of Population Health, Faculty of Health Sciences, Curtin University, GPO Box U1987, Perth, WA, 6845, Australia.
Donald McRobbieSchool of Physical Sciences, University of Adelaide, Adelaide, Australia.
Peter O'LearyHealth Economics and Data Analytics, Curtin School of Population Health, Faculty of Health Sciences, Curtin University, GPO Box U1987, Perth, WA, 6845, Australia.
Paul M ParizelMedical School, University of Western Australia, Perth, WA, Australia.
John SlavotinekSA Medical Imaging, SA Health and College of Medicine and Public Health, Flinders University, Adelaide, South Australia, Australia.
Cameron WrightHealth Economics and Data Analytics, Curtin School of Population Health, Faculty of Health Sciences, Curtin University, GPO Box U1987, Perth, WA, 6845, Australia.
David YouensHealth Economics and Data Analytics, Curtin School of Population Health, Faculty of Health Sciences, Curtin University, GPO Box U1987, Perth, WA, 6845, Australia.
Rachael MoorinHealth Economics and Data Analytics, Curtin School of Population Health, Faculty of Health Sciences, Curtin University, GPO Box U1987, Perth, WA, 6845, Australia.

Funding

Australian National Health and Medical Research Council APP1144573
6 · The paper itself

Abstract

purposeWhilst computed tomography (CT) imaging has been a vital component of injury management, its increasing use has raised concern regarding ionising radiation exposure. This study aims to identify latent classes (underlying patterns) of CT use over a 3-year period following the incidence of injury and factors predicting the observed patterns.

methodA retrospective observational cohort study was conducted in 21,544 individuals aged 18 + years presenting to emergency departments (ED) of four tertiary public hospitals with new injury in Western Australia. Mixture modelling approach was used to identify latent classes of CT use over a 3-year period post injury.

resultsAmongst injured people with at least one CT scan, three latent classes of CT use were identified including a: temporarily high CT use (46.4%); consistently high CT use (2.6%); and low CT use class (51.1%). Being 65 + years or older, having 3 + comorbidities, history with 3 + hospitalisations and history of CT use before injury were associated with consistently high use of CT. Injury to the head, neck, thorax or abdomen, being admitted to hospital after the injury and arriving to ED by ambulance were predictors for the temporarily high use class. Living in areas of higher socio-economic disadvantage was a unique factor associated with the low CT use class.

conclusionsInstead of assuming a single pattern of CT use for all patients with injury, the advanced latent class modelling approach has provided more nuanced understanding of the underlying patterns of CT use that may be useful for developing targeted interventions.

Indexed as

Craniocerebral TraumaTomography, X-Ray ComputedEmergency Service, HospitalHospitalizationHumansRetrospective StudiesWestern AustraliaComputed tomographyTrajectory of CT scanning, injury, high use CT scanning

Identifiers

PMID37318517
PMCPMC10728237

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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.