ArticleCanadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes2021
Volumetric Markers of Body Composition May Improve Personalized Prediction of Major Arterial Bleeding After Pelvic Fracture: A Secondary Analysis of the Baltimore CT Prediction Model Cohort.
Article in Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed, 4 citations in OpenAlex.
- Application of evidence-based nursing in nursing practice of patients with pelvic fracture.Medicine · 2026Observational
- Pulmonary contusion: automated deep learning-based quantitative visualization.Emergency radiology · 2023Article
- Does a "Cushion Effect" Really Exist? A Morphomic Analysis of Vulnerable Road Users with Serious Blunt Abdominal Injury.Healthcare (Basel, Switzerland) · 2021Article
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5 authors at 1 institution in 1 country.
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Abstract
methodsThis work is a retrospective secondary analysis of a single institution cohort used in the development of the Baltimore CT prediction model. The cohort includes 115 consecutive patients that underwent admission contrast-enhanced CT of the abdomen and pelvis for blunt trauma with pelvic ring disruption followed by conventional angiography. Major arterial injury requiring angioembolization served as the outcome variable. Angioembolization was required in 73/115 patients (63% of the cohort). Average age was 46.9 years (±SD 20.4). Body composition measurements were determined as 2-dimensional (2D) or 3-dimensional (3D) parameters and included mid-L3 trabecular bone attenuation, abdominal visceral fat area or volume, and percent muscle fat fraction (as a marker of sarcopenia) measured using segmentation and histogram analysis.
resultsModels incorporating 2D (Model B) or 3D markers (model C) of body composition showed improvement over the original Baltimore model (model A) in all parameters of performance, quality, and fit (area under the receiver-operating curve [AUC], Akaike information criterion, Brier score, Hosmer-Lemeshow test, and adjusted-R2). Area under the receiver-operating curve increased from 0.83 (A), to 0.86 (B), and 0.88 (C). The greatest improvement was seen with 3D parameters.
conclusionOnce automated, quantitative visualization tools providing "free" 3D body composition information can be expected to improve personalized precision diagnostics, outcome prediction, and decision support in patients with bleeding pelvic fractures.
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