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São Paulo med. j ; 136(4): 292-297, July-Aug. 2018. tab
Article in English | LILACS | ID: biblio-962737

ABSTRACT

ABSTRACT BACKGROUND: This study was designed to define the accuracy of shoulder ultrasonography for diagnosing supraspinatus tendon tears. This examination is routinely used by orthopedists and may do away with the need for other examinations for diagnosing these tendon injuries. The aim of this study was to evaluate the sensitivity and specificity of shoulder ultrasonography for diagnosing supraspinatus tendon injuries, using magnetic resonance imaging as the reference. DESIGN AND SETTING: Prospective accuracy study at a single center: the Shoulder and Elbow Surgery Clinic of the Department of Orthopedics and Traumatology. METHODS: Shoulder ultrasonography was performed on 80 patients of both genders, over 18 years of age, with complaints of shoulder pain and clinically suspected supraspinatus tendon lesions. Jobe's test and a full can test were performed. In addition, they underwent magnetic resonance imaging in a 3.0-tesla machine, as the reference standard. The examinations were performed and interpreted by radiologists. RESULTS: Ultrasonography showed sensitivity of 36.3% and specificity of 91.7% for supraspinatus tears overall: sensitivity of 25.8% and specificity of 91.8% for partial tears and sensitivity of 46.2% and specificity of 100% for full-thickness tears. Ultrasonography showed high accuracy for diagnosing full-thickness tears: 91.3%. The p-values were 0.003 for tears overall, 0.031 for partial tears and < 0.001 for full-thickness tears. CONCLUSIONS: Ultrasonography showed low sensitivity for detecting supraspinatus tears, but high specificity for both partial and full-thickness tears.


Subject(s)
Humans , Male , Female , Adult , Middle Aged , Aged , Young Adult , Shoulder Joint/injuries , Shoulder Joint/diagnostic imaging , Tendon Injuries/diagnostic imaging , Shoulder Injuries/diagnostic imaging , Magnetic Resonance Imaging , Prospective Studies , Reproducibility of Results , Ultrasonography , Sensitivity and Specificity , Data Accuracy
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