Evidence map›Paper›PMID 39395934›Full record

SynthesisBMC emergency medicine2024

Clinical prediction models for the management of blunt chest trauma in the emergency department: a systematic review.

Ceri Battle, Elaine Cole, Kym Carter, Edward Baker

2 registry-linked trialsAbstract readSystematic Review
In one paragraph

Synthesis in BMC emergency medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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.

NCT06734338 recruitingnot on this mapstarted 2025, after this paper: background citation

Validation of the STUMBL Score for Risk Stratification in Emergency Department Patients With Blunt Thoracic Trauma: A Prospective Observational Study in Iraq

TypeobservationalSponsorAl-Nahrain UniversityRan2025 to 2026Enrolled188ConditionsChest Trauma
NCT06737575 not yet recruitingnot on this mapstarted 2025, after this paper: background citation

Validation of Chest Trauma Scoring Systems in Predicting Blunt Chest Injury Outcomes in Iraq: A Prospective Study

TypeobservationalSponsorAl-Nahrain UniversityRan2025 to 2025Enrolled190ConditionsChest Injury Trauma Blunt
3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. SA journal of radiology · 2026
    Article
  5. Article
  6. Article
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

4 authors.

Ceri BattlePhysiotherapy Dept, Morriston Hospital, Swansea Bay University Health Board, Swansea, Wales, SA6 6NL, UK. Ceri.battle@Wales.nhs.uk.
Elaine ColeCentre of Trauma Sciences, Blizard Institute, Queen Mary University of London, London, UK.
Kym CarterSwansea Trials Unit, Swansea University Medical School, Swansea University, Swansea, UK.
Edward BakerEmergency Dept, Kings College Hospital, London, UK.

Funding

HCRW_ RFPPB-16-1193
6 · The paper itself

Abstract

backgroundThe aim of this systematic review was to investigate how clinical prediction models compare in terms of their methodological development, validation, and predictive capabilities, for patients with blunt chest trauma presenting to the Emergency Department.

methodsA systematic review was conducted across databases from 1st Jan 2000 until 1st April 2024. Studies were categorised into three types of multivariable prediction research and data extracted regarding methodological issues and the predictive capabilities of each model. Risk of bias and applicability were assessed.

results41 studies were included that discussed 22 different models. The most commonly observed study design was a single-centre, retrospective, chart review. The most widely externally validated clinical prediction models with moderate to good discrimination were the Thoracic Trauma Severity Score and the STUMBL Score. DISCUSSION: This review demonstrates that the predictive ability of some of the existing clinical prediction models is acceptable, but high risk of bias and lack of subsequent external validation limits the extensive application of the models. The Thoracic Trauma Severity Score and STUMBL Score demonstrate better predictive accuracy in both development and external validation studies than the other models, but require recalibration and / or update and evaluation of their clinical and cost effectiveness. REVIEW REGISTRATION: PROSPERO database ( https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=351638 ).

Indexed as

Emergency Service, HospitalThoracic InjuriesWounds, NonpenetratingHumansBlunt chest traumaClinical prediction modelsSystematic review

Identifiers

PMID39395934
PMCPMC11470733

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

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.