谷歌浏览器插件
订阅小程序
在清言上使用

Accuracy of Infraspinatus Isometric Testing in Predicting Tear Size and Tendon Reparability: Comparison with Imaging and Arthroscopy.

Journal of Shoulder and Elbow Surgery(2017)

引用 8|浏览11
暂无评分
摘要
BACKGROUND:The purpose of this study was to examine the accuracy of external rotation in neutral (0° external position) and in shortened position (45° external position) in relation to rotator cuff tear size, tendon reparability, and other clinical, surgical, and imaging findings.METHODS:This was a prospective blinded diagnostic study of consecutive surgical candidates for rotator cuff repair using magnetic resonance imaging and arthroscopic surgery as the "gold standards." The area under a receiver operating characteristic (AUROC) curve was calculated for each position.RESULTS:Eighty-five patients (35 female [41%] and 50 male [59%]; age, 65 years [standard deviation = 10]) were included. Sixty patients (71%) had a minor tear (4 small, 56 moderate), and 25 patients (29%) had a major tear (17 large and 8 massive). Seventy patients (82%) had a full repair, and 15 (18%) patients underwent a partial repair. There were 26 (31%) associated full-thickness tears of the infraspinatus. The isometric strength testing in both positions had good to excellent accuracy (range, 0.80-0.90) for detecting reparability, tear retraction, infraspinatus atrophic changes observed by the clinician, and infraspinatus fatty infiltration on magnetic resonance images. The shortened position had an overall higher accuracy than the neutral position and was more clinically useful for detecting an infraspinatus full-thickness tear (AUROC = 0.84 vs 0.78) and rotator cuff tear size (AUROC = 0.80 vs. 0.75).CONCLUSIONS:The isometric external rotation is an accurate test in diagnosing different aspects of rotator cuff disease and specifically of the infraspinatus muscle. The isometric strength at the shortened position was a better predictor of clinical, surgical, and imaging findings.
更多
查看译文
关键词
Level I,Prospective Design,Diagnostic Study
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要