Evidence map›Paper›PMID 36862245›Full record

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

The association of radiologic body composition parameters with clinical outcomes in level-1 trauma patients.

Arthur A R Sweet, Tim Kobes, Roderick M Houwert, Rolf H H Groenwold, Pim Moeskops, Luke P H Leenen, Pim A de Jong, Wouter B Veldhuis, Mark C P M van Baal

Open access · hybridAbstract read
In one paragraph

Article 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. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
0.6field-weighted citation impact, top 33% of its field
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 synthesis or guideline pooled it, 2 citations in OpenAlex.

  1. Pooled it
  2. Observational
  3. Coronary artery calcification detected by initial polytrauma CT in severely injured patients: retrospective single-center cohort study.European journal of trauma and emergency surgery : official publication of the European Trauma Society · 2024
    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

9 authors at 3 institutions in 1 country.

Arthur A R SweetDepartment of Surgery, University Medical Center Utrecht, PO Box 85500, 3508 GA, Utrecht, The Netherlands. a.a.r.sweet@outlook.com.ORCID http://orcid.org/0000-0003-2061-6403
Tim KobesDepartment of Surgery, University Medical Center Utrecht, PO Box 85500, 3508 GA, Utrecht, The Netherlands.
Roderick M HouwertDepartment of Surgery, University Medical Center Utrecht, PO Box 85500, 3508 GA, Utrecht, The Netherlands.
Rolf H H GroenwoldDepartment of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands.
Pim MoeskopsQuantib, Rotterdam, The Netherlands.
Luke P H LeenenDepartment of Surgery, University Medical Center Utrecht, PO Box 85500, 3508 GA, Utrecht, The Netherlands.
Pim A de JongDepartment of Radiology, University Medical Center Utrecht, Utrecht, The Netherlands.
Wouter B VeldhuisDepartment of Radiology, University Medical Center Utrecht, Utrecht, The Netherlands.
Mark C P M van BaalDepartment of Surgery, University Medical Center Utrecht, PO Box 85500, 3508 GA, Utrecht, The Netherlands.
University Medical Center Utrecht · NLLeiden University Medical Center · NLUtrecht University · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThe present study aims to assess whether CT-derived muscle mass, muscle density, and visceral fat mass are associated with in-hospital complications and clinical outcome in level-1 trauma patients.

methodsA retrospective cohort study was conducted on adult patients admitted to the University Medical Center Utrecht following a trauma between January 1 and December 31, 2017. Trauma patients aged 16 years or older without severe neurological injuries, who underwent a CT that included the abdomen within 7 days of admission, were included. An artificial intelligence (AI) algorithm was used to retrieve muscle areas to calculate the psoas muscle index and to retrieve psoas muscle radiation attenuation and visceral fat (VF) area from axial CT images. Multivariable logistic and linear regression analyses were performed to assess associations between body composition parameters and outcomes.

resultsA total of 404 patients were included for analysis. The median age was 49 years (interquartile range [IQR] 30-64), and 66.6% were male. Severe comorbidities (ASA 3-4) were seen in 10.9%, and the median ISS was 9 (IQR 5-14). Psoas muscle index was not independently associated with complications, but it was associated with ICU admission (odds ratio [OR] 0.79, 95% confidence interval [CI] 0.65-0.95), and an unfavorable Glasgow Outcome Scale (GOS) score at discharge (OR 0.62, 95% CI 0.45-0.85). Psoas muscle radiation attenuation was independently associated with the development of any complication (OR 0.60, 95% CI 0.42-0.85), pneumonia (OR 0.63, 95% CI 0.41-0.96), and delirium (OR 0.49, 95% CI 0.28-0.87). VF was associated with developing a delirium (OR 1.95, 95% CI 1.12-3.41).

conclusionIn level-1 trauma patients without severe neurological injuries, automatically derived body composition parameters are able to independently predict an increased risk of specific complications and other poor outcomes.

Indexed as

Artificial IntelligenceDeliriumAdultBody CompositionFemaleHospitalizationHumansMaleMiddle AgedRetrospective StudiesAutomatic segmentationBody compositionComplicationsComputed tomographyTrauma

Identifiers

PMID36862245
PMCPMC10449658
OpenAlexW4322757573

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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.