BACKGROUND: The present study aims to add to the body of evidence delineating the learning curve for a shoulder surgeon to become proficient in focussed ultrasound for the detection of full-thickness rotator cuff tears, as well as to describe a learning method for this skill. METHODS: Consecutive patients who were scheduled to undergo an arthroscopy for rotator cuff disease were scanned immediately before surgery by a senior shoulder surgeon with limited previous experience of shoulder ultrasound. The presence or absence of a full-thickness rotator cuff tear on scan was compared with intra-operative findings as the gold standard. RESULTS: Two hundred and ten shoulders were scanned over three equal learning periods. Comparing predictive values from the first to the third training period, sensitivity improved from 0.86 to 0.95, specificity from 0.92 to 0.98, negative predictive value from 0.94 to 0.98, and positive predictive value from 0.82 to 0.95. CONCLUSIONS: The high predictive values obtained in the present study for surgeon-led detection of cuff tears using ultrasound are comparable with those quoted for musculoskeletal radiologists in the literature. The present study adds evidence that a shoulder surgeon can achieve accelerated learning of this skill and offers some potentially time-saving and patient-friendly alternatives to existing guidelines.
BACKGROUND: The present study aims to add to the body of evidence delineating the learning curve for a shoulder surgeon to become proficient in focussed ultrasound for the detection of full-thickness rotator cuff tears, as well as to describe a learning method for this skill. METHODS: Consecutive patients who were scheduled to undergo an arthroscopy for rotator cuff disease were scanned immediately before surgery by a senior shoulder surgeon with limited previous experience of shoulder ultrasound. The presence or absence of a full-thickness rotator cuff tear on scan was compared with intra-operative findings as the gold standard. RESULTS: Two hundred and ten shoulders were scanned over three equal learning periods. Comparing predictive values from the first to the third training period, sensitivity improved from 0.86 to 0.95, specificity from 0.92 to 0.98, negative predictive value from 0.94 to 0.98, and positive predictive value from 0.82 to 0.95. CONCLUSIONS: The high predictive values obtained in the present study for surgeon-led detection of cuff tears using ultrasound are comparable with those quoted for musculoskeletal radiologists in the literature. The present study adds evidence that a shoulder surgeon can achieve accelerated learning of this skill and offers some potentially time-saving and patient-friendly alternatives to existing guidelines.
Authors: Joseph P Iannotti; James Ciccone; Daniel D Buss; Jeffrey L Visotsky; Edward Mascha; Kathy Cotman; Nandkumar M Rawool Journal: J Bone Joint Surg Am Date: 2005-06 Impact factor: 5.284
Authors: Richard James Murphy; Michael Todd Daines; Andrew Jonathan Carr; Jonathan Lloyd Rees Journal: J Bone Joint Surg Am Date: 2013-02-06 Impact factor: 5.284
Authors: Ali S Farooqi; Alexander Lee; David Novikov; Ann Marie Kelly; Xinning Li; John D Kelly; Robert L Parisien Journal: Orthop J Sports Med Date: 2021-10-11