Evidence map›Paper›PMID 39659308›Full record

ArticleCureus2024

Utility of Abdominal Cross-Sectional Imaging in Motor Vehicle Accidents in an Inner City Trauma Center: A Retrospective Cohort Study.

Allen T Yu, Aliza S Gross, Alex L Huang, Jason Brody, Luis Suarez-Rodriguez, Susan Talbert, Raymond V Wedderburn, Kusuma Nio

Abstract read
In one paragraph

Article in Cureus, 2024. 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

8 authors.

Allen T YuTrauma and Acute Care Surgery, Icahn School of Medicine at Mount Sinai, New York, USA.
Aliza S GrossMedicine, Icahn School of Medicine at Mount Sinai, New York, USA.
Alex L HuangTrauma and Acute Care Surgery, Icahn School of Medicine at Mount Sinai, New York, USA.
Jason BrodyTrauma and Acute Care Surgery, Icahn School of Medicine at Mount Sinai, New York, USA.
Luis Suarez-RodriguezTrauma and Acute Care Surgery, Yale New Haven Hospital, New Haven, USA.
Susan TalbertTrauma and Acute Care Surgery, Icahn School of Medicine at Mount Sinai, New York, USA.
Raymond V WedderburnTrauma and Acute Care Surgery, Icahn School of Medicine at Mount Sinai, New York, USA.
Kusuma NioTrauma and Acute Care Surgery, Icahn School of Medicine at Mount Sinai, New York, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background The use of computed tomography (CT) of the abdomen and pelvis following motor vehicle collisions (MVCs) as standard diagnostic evaluation is widely accepted. However, the incidence of positive findings is low, and it is unknown which features increase the risk of having abdominal injuries. Objectives The aim of this study is to identify risk factors on presentation that are associated with positive CT findings. Methods A retrospective review of patients from January 2020 to January 2023 in a level II urban trauma center who were in MVCs was performed. Standard ACS TQIP metrics were recorded, as well as vehicle speed, CT findings, and presenting characteristics. Low-speed MVCs were considered to be ≤25 mph and high-speed MVCs were considered to be >25 mph. Results In 4,444 trauma activations, there were 738 (16.6%) MVCs: 310 (42.0%) were low-speed, 160 (21.7%) were high-speed, and 268 (36.3%) were unknown-speed. Twenty-nine patients had positive CT findings. There was a significant difference in positive CT findings in low-speed versus high-speed MVCs (1.9% vs 5.9%, p < 0.05). Multivariate analysis for positive CT findings revealed that high-speed and unknown MVCs (OR

Indexed as

collision speedct of the abdomen and pelvis (ctap)intra-abdominal injurymotor vehicle collisionmvc

Identifiers

PMID39659308
PMCPMC11630415

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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.