Use of Shoulder Imaging in the Outpatient Setting: A Pilot Study.

Curr Probl Diagn Radiol

Department of Radiology, NYU Langone Medical Center, New York, New York; NYU Patient Imaging Quality and Safety Laboratory (PIQS Lab), New York, New York.

Published: January 2019

Purpose: Characterize the clinical utility of diagnostic shoulder imaging modalities commonly used in the outpatient workup of shoulder pain.

Materials/methods: Retrospective review of adults imaged for outpatient shoulder pain from 1/1/2013 to 9/1/2015. To be categorized as "useful", a study had to meet one of the following criteria: change the clinical diagnosis or treatment plan, provide a final diagnosis, or guide definitive treatment. A utility score was assigned to each study based on the number of utility criteria met (range 0-4). A score of 1 was considered low utility; a score of greater than or equal to 2 was considered high utility. Statistical analysis included binary logistic regression and generalized estimating equations.

Results: 210 subjects (65% male); mean age 47 (range 18-84), underwent 302 imaging studies (159 X-ray, 137 MRI, 2 CT, 4 ultrasound) during the study period. 92.1% of all studies met minimum criteria for utility (score >1). Most commonly, diagnostic studies obtained during the outpatient workup of shoulder pain were found to guide definitive treatment (70.5%) or provide a final diagnosis (53%). Most X-rays were categorized as no or low utility (85.5%). 97.8% of the MRI studies were categorized as useful with most being high utility (73%). Overall, MRI was the most useful modality in all clinical scenarios (P = 0.002) and more likely to be high utility (P < 0.001) compared to X-rays. None of the investigated patient or injury characteristics were significant predictors of useful imaging.

Conclusion: Our study suggests that both radiographs and MRI are useful in the evaluation of adult unilateral shoulder pain in the outpatient setting. MRI appears to be the most useful imaging modality in terms of helping guide diagnosis and treatment selection. This serves as a potential first step towards the development of evidence based imaging algorithms that can be used and tested in future studies.

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http://dx.doi.org/10.1067/j.cpradiol.2017.10.011DOI Listing

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