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Orthopaedic Proceedings
Vol. 96-B, Issue SUPP_11 | Pages 349 - 349
1 Jul 2014
Hyodo K Yoshioka T Akaogi H Sugaya H Aoto K Wada H Sakai S Yamazaki M Mishima H
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Introduction

The goal of joint-preserving surgery for the treatment of osteonecrosis of the femoral head (ONFH) is to delay or prevent osteoarthritic development. Bone marrow is a source of osteogenic progenitors that are key elements in the process of bone formation and fracture healing. We established an easy-to-use method using a conventional manual blood bag centrifugation technique traditionally used for extracting buffy coats, for concentration of nucleated cells and platelets from clinical bone marrow aspirates to obtain osteogenic progenitors and growth factors. However, it is unclear whether the surgical goals are really achieved and if so in which patients. The purpose of this study was to identify demographic, clinical, and radiographic factors predicting total hip arthroplasty (THA) conversion after CABMAT for the treatment of idiopathic ONFH.

Methods

We retrospectively reviewed 123 patients (213 hips) who had CABMAT between 2003 and 2010. Sixty-five subjects (115 hips) were male and 58 (98 hips) were female with an average age at the time of CABMAT of 40.1 years. Of the 213 hips, 143 hips in 78 patients had corticosteroid-induced ONFH, 46 hips in 27 patients had alcohol-associated, and 24 hips in 18 patients had no etiological factors could be detected. The mean follow-up period was 60.5 months. The endpoint of evaluation was set as the time point which the patient required additional surgery (THA) depending on the spontaneous hip pain, x-ray change, and social back ground. The following factors were investigated: age, sex, body mass index (BMI), unilateral or bilateral, etiological factors, preoperative classification and staging, visual analogue scale (VAS), JOA clinical score. The 213 hips were divided into two groups: a THA conversion (THA) group and a non-THA conversion (non-THA) group. A multivariate analysis was performed using a logistic regression model.