Evidence map›Paper›PMID 40167933›Full record

ArticleLa Radiologia medica2025

Opportunistic prognostication by computerized tomography (CT) in the emergency department: analysis on 1920 patients and creation of a simple and fast scoring system.

Alberto Stefano Tagliafico, Stefano Benenati, Italo Porto, Carlo Martinoli, Pietro Ameri, HSM score Collaborators

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Article in La Radiologia medica, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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1 citing paper in PubMed.

  1. Multimodal imaging fusion and machine learning model development: differential diagnosis of spinal inflammatory lesions using combined CT hounsfield units and MRI features.European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society · 2026
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5 · Who and what money

Authors and funding

6 authors.

Alberto Stefano Tagliafico *IRCCS Ospedale Policlinico San Martino, Genova, Italy. alberto.tagliafico@unige.it.ORCID http://orcid.org/0000-0003-1736-0697
Stefano Benenati *Department of Internal Medicine, University of Genova, Genova, Italy.
Italo PortoIRCCS Ospedale Policlinico San Martino, Genova, Italy.
Carlo MartinoliIRCCS Ospedale Policlinico San Martino, Genova, Italy.
Pietro AmeriIRCCS Ospedale Policlinico San Martino, Genova, Italy.
HSM score Collaborators

Funding

Ministero della Salute Italian Ministry of Health (Ricerca Corrente IRCCS Ospedale Policlinico San Martino 2022-2024)
6 · The paper itself

Abstract

purposeTo use simple CT measurements of musculoskeletal and cardiovascular systems to create a CT-based score to predict mortality in patients admitted to the Emergency Department (ED).

methodsThe study received IRB approval. Non-contrast abdominal CT of > 18 year old patients admitted to the ER between January 2019 and January 2020 were evaluated by a team of twelve radiologists to calculate: (1) diameter of the infrarenal aorta in millimeter; (2) cross sectional area and composition (Hounsfield units) of the psoas muscle at the third lumbar vertebra (LV); (3) bone density, as quantified at the first lumbar vertebra (LV); (4) presence or absence of dilated abdominal aorta. Thirty-day all-cause mortality (ACM) was determined through hospital and electronic records.

resultsN = 1920 unique patients were evaluated. The mean age was 65 ± 19 years and 46% were female. Death occurred in 7.9% of patients by 30 days from admission. The derivation dataset comprised 1462 patients. At multivariable analysis, age (OR 1.02, 95% CI: 1.007-1.04, p = 0.005), psoas cross sectional area (OR 0.99, 95% CI: 0.997-0.999, p < 0.001) and density (OR 0.96, 95% CI: 0.95-0.98, p < 0.001), and dilated infrarenal aorta (OR 1.85, 95% CI: 1-3.28, p = 0.04) were predictors of the outcome. We accordingly derived a 4-item risk score. In the derivation dataset, the score yielded moderate-high discrimination, with an AUC of 0.73 and excellent diagnostic agreement. In the validation dataset (N = 458), discrimination was high (AUC = 0.83).

conclusionSimple measurements gathered during a standard CT may allow determining the risk of mortality in the heterogeneous patient population admitted to the ED in a cost- and time-effective manner.

Indexed as

Emergency Service, HospitalTomography, X-Ray ComputedAgedAged, 80 and overAorta, AbdominalFemaleHumansMaleMiddle AgedPredictive Value of TestsPrognosisPsoas MusclesRetrospective StudiesBiomarkerComputed tomographyEmergency

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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 Socratic graph.