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Systematic review
Clinical predictors of fracture in patients with shoulder dislocation: systematic review of diagnostic test accuracy studies
  1. Ilaria Oldrini1,
  2. Laura Coventry1,
  3. Alex Novak2,
  4. Steve Gwilym3,4,
  5. David Metcalfe1,2,3
  1. 1Warwick Medical School, University of Warwick, Coventry, UK
  2. 2Emergency Department, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
  3. 3Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK
  4. 4Department of Trauma Surgery, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
  1. Correspondence to Dr David Metcalfe, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, Oxfordshire, UK; david.metcalfe{at}ndorms.ox.ac.uk

Abstract

Background Prereduction radiographs are conventionally used to exclude fracture before attempts to reduce a dislocated shoulder in the ED. However, this step increases cost, exposes patients to ionising radiation and may delay closed reduction. Some studies have suggested that prereduction imaging may be omitted for a subgroup of patients with shoulder dislocations.

Objectives To determine whether clinical predictors can identify patients who may safely undergo closed reduction of a dislocated shoulder without prereduction radiographs.

Methods A systematic review and meta-analysis of diagnostic test accuracy studies that have evaluated the ability of clinical features to identify concomitant fractures in patients with shoulder dislocation. The search was updated to 23 June 2022 and language limits were not applied. All fractures were included except for Hill-Sachs lesions. Quality assessment was undertaken using the Quality Assessment of Diagnostic Accuracy Studies 2 tool. Data were pooled and meta-analysed by fitting univariate random effects and multilevel mixed effects logistic regression models.

Results Eight studies reported data on 2087 shoulder dislocations and 343 concomitant fractures. The most important potential sources of bias were unclear blinding of those undertaking the clinical (6/8 studies) and radiographic (3/8 studies) assessment. The prevalence of concomitant fracture was 17.5%. The most accurate clinical predictors were age >40 (positive likelihood ratio (LR+) 1.8, 95% CI 1.5 to 2.1; negative likelihood ratio (LR−) 0.4, 95% CI 0.2 to 0.6), female sex (LR+ 2.0, 95% CI 1.6 to 2.4; LR− 0.7, 95% CI 0.6 to 0.8), first-time dislocation (LR+ 1.7, 95% CI 1.4 to 2.0; LR− 0.2, 95% CI 0.1 to 0.5) and presence of humeral ecchymosis (LR+ 3.0–5.7, LR− 0.8–1.1). The most important mechanisms of injury were high-energy mechanism fall (LR+ 2.0–9.8, LR− 0.4–0.8), fall >1 flight of stairs (LR+ 3.8, 95% CI 0.6 to 13.1; LR− 1.0, 95% CI 0.9 to 1.0) and motor vehicle collision (LR+ 2.3, 95% CI 0.5 to 4.0; LR− 0.9, 95% CI 0.9 to 1.0). The Quebec Rule had a sensitivity of 92.2% (95% CI 54.6% to 99.2%) and a specificity of 33.3% (95% CI 23.1% to 45.3%), but the Fresno-Quebec rule identified all clinically important fractures across two studies: sensitivity of 100% (95% CI 89% to 100%) in the derivation dataset and 100% (95% CI 90% to 100%) in the validation study. The specificity of the Fresno-Quebec rule ranged from 34% (95% CI 28% to 41%) in the derivation dataset to 24% (95% CI 16% to 33%) in the validation study.

Conclusion Clinical prediction rules may have a role in supporting shared decision making after shoulder dislocation, particularly in the prehospital and remote environments when delay to imaging is anticipated.

  • Systematic Review
  • clinical assessment
  • fractures and dislocations

Data availability statement

Data are available upon reasonable request. Not applicable.

http://dx.doi.org/10.1136/emermed-2022-212696

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    Data availability statement

    Data are available upon reasonable request. Not applicable.

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    Footnotes

    • Handling editor Richard Body

    • Twitter @i_oldrini, @AlexTNovak, @SteveGwilym, @TraumaDataDoc

    • Contributors IO led and undertook the initial systematic review. LC independently screened abstracts, extracted data and performed quality assessments. SG and AN contributed to the study design, data interpretation and critical review of the manuscript. DM designed and supervised the study then prepared the manuscript for publication and is the guarantor.

    • Funding DM is supported by a NIHR Advanced Fellowship and the NIHR Oxford Biomedical Research Centre.

    • Competing interests None declared.

    • Patient and public involvement Patients and/or the public were not involved in the design, conduct, reporting or dissemination plans of this research.

    • Provenance and peer review Not commissioned; externally peer reviewed.

    • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.