Evidence map›Paper›PMID 26440607›Full record

Observational studyPLoS medicine2015

Derivation and validation of two decision instruments for selective chest CT in blunt trauma: a multicenter prospective observational study (NEXUS Chest CT).

Robert M Rodriguez, Mark I Langdorf, Daniel Nishijima, Brigitte M Baumann, Gregory W Hendey, Anthony J Medak, Ali S Raja, Isabel E Allen, William R Mower

Open access · goldAbstract readMulticenter StudyObservational StudyValidation Study
In one paragraph

Observational study in PLoS medicine, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
6.5field-weighted citation impact, top 3% 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

19 citing papers in PubMed, 64 citations in OpenAlex.

  1. Observational
  2. Article
  3. Article
  4. A clinical decision instrument to safely reduce abdominopelvic CT use in minor blunt trauma patients.European journal of trauma and emergency surgery : official publication of the European Trauma Society · 2025
    Article
  5. Assessing the role of chest CT in minor blunt trauma: evaluation of the NEXUS decision instrument across an expanded population.European journal of trauma and emergency surgery : official publication of the European Trauma Society · 2025
    Article
  6. Review
  7. Article
  8. CT as a first-line modality in elderly patients with stable blunt chest trauma.Chinese journal of traumatology = Zhonghua chuang shang za zhi · 2021
    Article
  9. Chest tube output, duration, and length of stay are similar for pneumothorax and hemothorax seen only on computed tomography vs. chest radiograph.European journal of trauma and emergency surgery : official publication of the European Trauma Society · 2021
    Article
  10. Article
  11. Hemothorax: A Review of the Literature.Clinical pulmonary medicine · 2020
    Article
  12. Article
  13. Article
  14. Pulmonary contusion.Journal of thoracic disease · 2019
    Review
  15. Article
  16. Review
  17. Article
  18. Article
  19. Pulmonary Contusion-An Unusual Clinical and Radiological Presentation: Case Report.Journal of investigative medicine high impact case reports
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors at 7 institutions in 1 country.

Robert M RodriguezDepartment of Emergency Medicine, University of California, San Francisco, California, United States of America.
Mark I LangdorfDepartment of Emergency Medicine, University of California, Irvine, California, United States of America.
Daniel NishijimaDepartment of Emergency Medicine, University of California, Davis, California, United States of America.
Brigitte M BaumannDepartment of Emergency Medicine, Cooper Medical School of Rowan University, Camden, New Jersey, United States of America.
Gregory W HendeyDepartment of Emergency Medicine, UCSF Fresno Medical Education and Research, Fresno, California, United States of America.
Anthony J MedakDepartment of Emergency Medicine, School of Medicine, University of California, San Diego, California, United States of America.
Ali S RajaDepartment of Emergency Medicine, Massachusetts General Hospital/Harvard Medical School, Boston, Massachusetts, United States of America.
Isabel E AllenUniversity of California, San Francisco, California, United States of America.
William R MowerDepartment of Emergency Medicine, University of California, Los Angeles, California, United States of America.
University of California, San Francisco · USCooper Medical School of Rowan University · USHarvard University · USUniversity of California, Davis · USUniversity of California, Irvine · USUniversity of California, Los Angeles · USUniversity of California, San Diego · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundUnnecessary diagnostic imaging leads to higher costs, longer emergency department stays, and increased patient exposure to ionizing radiation. We sought to prospectively derive and validate two decision instruments (DIs) for selective chest computed tomography (CT) in adult blunt trauma patients. METHODS AND

findingsFrom September 2011 to May 2014, we prospectively enrolled blunt trauma patients over 14 y of age presenting to eight US, urban level 1 trauma centers in this observational study. During the derivation phase, physicians recorded the presence or absence of 14 clinical criteria before viewing chest imaging results. We determined injury outcomes by CT radiology readings and categorized injuries as major or minor according to an expert-panel-derived clinical classification scheme. We then employed recursive partitioning to derive two DIs: Chest CT-All maximized sensitivity for all injuries, and Chest CT-Major maximized sensitivity for only major thoracic injuries (while increasing specificity). In the validation phase, we employed similar methodology to prospectively test the performance of both DIs. We enrolled 11,477 patients-6,002 patients in the derivation phase and 5,475 patients in the validation phase. The derived Chest CT-All DI consisted of (1) abnormal chest X-ray, (2) rapid deceleration mechanism, (3) distracting injury, (4) chest wall tenderness, (5) sternal tenderness, (6) thoracic spine tenderness, and (7) scapular tenderness. The Chest CT-Major DI had the same criteria without rapid deceleration mechanism. In the validation phase, Chest CT-All had a sensitivity of 99.2% (95% CI 95.4%-100%), a specificity of 20.8% (95% CI 19.2%-22.4%), and a negative predictive value (NPV) of 99.8% (95% CI 98.9%-100%) for major injury, and a sensitivity of 95.4% (95% CI 93.6%-96.9%), a specificity of 25.5% (95% CI 23.5%-27.5%), and a NPV of 93.9% (95% CI 91.5%-95.8%) for either major or minor injury. Chest CT-Major had a sensitivity of 99.2% (95% CI 95.4%-100%), a specificity of 31.7% (95% CI 29.9%-33.5%), and a NPV of 99.9% (95% CI 99.3%-100%) for major injury and a sensitivity of 90.7% (95% CI 88.3%-92.8%), a specificity of 37.9% (95% CI 35.8%-40.1%), and a NPV of 91.8% (95% CI 89.7%-93.6%) for either major or minor injury. Regarding the limitations of our work, some clinicians may disagree with our injury classification and sensitivity thresholds for injury detection.

conclusionsWe prospectively derived and validated two DIs (Chest CT-All and Chest CT-Major) that identify blunt trauma patients with clinically significant thoracic injuries with high sensitivity, allowing for a safe reduction of approximately 25%-37% of unnecessary chest CTs. Trauma evaluation protocols that incorporate these DIs may decrease unnecessary costs and radiation exposure in the disproportionately young trauma population.

Indexed as

Decision Support TechniquesTomography, X-Ray ComputedAdultAlgorithmsFemaleHumansMaleMiddle AgedPredictive Value of TestsProspective StudiesSensitivity and SpecificityThoracic InjuriesUnited StatesWounds, Nonpenetrating

Identifiers

PMID26440607
PMCPMC4595216
OpenAlexW2167774225

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.