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CADAVERIC STUDY ON THE LEARNING CURVE OF THE TWO-APPROACH GANZ PERIACETABULAR OSTEOTOMY

Overview of attention for article published in Acta Ortopédica Brasileira, April 2016
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Title
CADAVERIC STUDY ON THE LEARNING CURVE OF THE TWO-APPROACH GANZ PERIACETABULAR OSTEOTOMY
Published in
Acta Ortopédica Brasileira, April 2016
DOI 10.1590/1413-785220162402142388
Pubmed ID
Authors

Fernando Portilho Ferro, Leandro Ejnisman, Helder Souza Miyahara, Christiano Augusto de Castro Trindade, Antônio Faga, José Ricardo Negreiros Vicente

Abstract

: The Bernese periacetabular osteotomy (PAO) is a widely used technique for the treatment of non-arthritic, dysplastic, painful hips. It is considered a highly complex procedure with a steep learning curve. In an attempt to minimize complications, a double anterior-posterior approach has been described. We report on our experience while performing this technique on cadaveric hips followed by meticulous dissection to verify possible complications. : We operated on 15 fresh cadaveric hips using a combined posterior Kocher-Langenbeck and an anterior Smith-Petersen approach, without fluoroscopic control. The PAO cuts were performed and the acetabular fragment was mobilized. A meticulous dissection was carried out to verify the precision of the cuts. : Complications were observed in seven specimens (46%). They included a posterior column fracture, and posterior and anterior articular fractures. The incidence of complications decreased over time, from 60% in the first five procedures to 20% in the last five procedures. : We concluded that PAO using a combined anterior-posterior approach is a reproducible technique that allows all cuts to be done under direct visualization. The steep learning curve described in the classic single incision approach was also observed when using two approaches. IV, Cadaveric Study.

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The data shown below were compiled from readership statistics for 21 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 21 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 5 24%
Student > Postgraduate 4 19%
Researcher 3 14%
Student > Bachelor 2 10%
Professor > Associate Professor 2 10%
Other 1 5%
Unknown 4 19%
Readers by discipline Count As %
Medicine and Dentistry 13 62%
Nursing and Health Professions 1 5%
Psychology 1 5%
Engineering 1 5%
Unknown 5 24%