Evidence map›Paper›PMID 33914402›Full record

ArticleAcademic emergency medicine : official journal of the Society for Academic Emergency Medicine2021

Comparison of a trauma comorbidity index with other measures of comorbidities to estimate risk of trauma mortality.

Peter C Jenkins, Brian E Dixon, Stephanie A Savage, Aaron E Carroll, Craig D Newgard, Christopher J Tignanelli, Mark R Hemmila, Lava Timsina

Abstract read
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In one paragraph

Article in Academic emergency medicine : official journal of the Society for Academic Emergency Medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

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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.

Peter C JenkinsDepartment of Surgery, Indiana University School of Medicine, Indianapolis, Indiana, USA.ORCID 0000-0002-8527-8268
Brian E DixonRegenstrief Institute, Indianapolis, Indiana, USA.ORCID 0000-0002-1121-0607
Stephanie A SavageDepartment of Surgery, University of Wisconsin, Madison, Wisconsin, USA.
Aaron E CarrollRegenstrief Institute, Indianapolis, Indiana, USA.
Craig D NewgardDepartment of Emergency Medicine, Oregon Health & Science University School of Medicine, Portland, Oregon, USA.ORCID 0000-0003-1083-3455
Christopher J TignanelliDepartment of Surgery, University of Minnesota School of Medicine, Minneapolis, Minnesota, USA.
Mark R HemmilaDepartment of Surgery, University of Michigan School of Medicine, Ann Arbor, Michigan, USA.
Lava TimsinaDepartment of Surgery, Indiana University School of Medicine, Indianapolis, Indiana, USA.

Funding

University of Minnesota Clinical and Translational Science Institute (UMN CTSI)UL1TR002494 · NCATS · UNIVERSITY OF MINNESOTA · PI BLAZAR, BRUCE R, WEISDORF, DANIEL J · 2018 to 2022
$34.9M
Quality Assurance and Quality Control Project Management: Improving Submissions and Study Conduct in the Human Subjects Research Prior Approval ProcessUL1TR002529 · NCATS · INDIANA UNIVERSITY INDIANAPOLIS · PI MOE, SHARON M, WIEHE, SARAH ELIZABETH · 2018 to 2022
$27.2M
NCATS NIH HHS UL1 TR002494NCATS NIH HHS UL1 TR002529NCATS NIH HHS UL1TR002529
6 · The paper itself

Abstract

backgroundComorbidities influence the outcomes of injured patients, yet a lack of consensus exists regarding how to quantify that association. This study details the development and internal validation of a trauma comorbidity index (TCI) designed for use with trauma registry data and compares its performance to other existing measures to estimate the association between comorbidities and mortality.

methodsIndiana state trauma registry data (2013-2015) were used to compare the TCI with the Charlson and Elixhauser comorbidity indices, a count of comorbidities, and comorbidities as separate variables. The TCI approach utilized a randomly selected training cohort and was internally validated in a distinct testing cohort. The C-statistic of the adjusted models was tested using each comorbidity measure in the testing cohort to assess model discrimination. C-statistics were compared using a Wald test, and stratified analyses were performed based on predicted risk of mortality. Multiple imputation was used to address missing data.

resultsThe study included 84,903 patients (50% each in training and testing cohorts). The Indiana TCI model demonstrated no significant difference between testing and training cohorts (p = 0.33). It produced a C-statistic of 0.924 in the testing cohort, which was significantly greater than that of models using the other indices (p < 0.05). The C-statistics of models using the Indiana TCI and the inclusion of comorbidities as separate variables-the method used by the American College of Surgeons Trauma Quality Improvement Program-were comparable (p = 0.11) but use of the TCI approach reduced the number of comorbidity-related variables in the mortality model from 19 to one.

conclusionsWhen examining trauma mortality, the TCI approach using Indiana state trauma registry data demonstrated superior model discrimination and/or parsimony compared to other measures of comorbidities.

Indexed as

ComorbidityCohort StudiesHospital MortalityHumans

Identifiers

PMID33914402
PMCPMC9668346

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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.