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Orthopaedic Proceedings
Vol. 94-B, Issue SUPP_VIII | Pages 14 - 14
1 Mar 2012
Zhao G Yamamoto T Ikemura S Motomura G Nakashima Y Mawatari T Iwamoto Y
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Introduction. Transtrochanteric curved varus osteotomy is one of the effective joint-preserving operations for osteonecrosis (ON) of the femoral head. We correlated various factors with the radiological outcome of this procedure. Methods. We reviewed 74 hips in 63 patients who had a minimum follow-up of 5 years after transtrochanteric curved varus osteotomy for the treatment of ON. There were 28 men and 35 women who had a mean age of 33 years (range, 15 to 68 years) at the time of surgery. Clinical assessment was made based on the Harris hip score (HHS). Radiographically, we investigated various factors; affected lesion, stage and type (localization of the necrotic lesion) of ON, varus degree, post-operative intact ratio, progression of collapse, and joint-space narrowing. On the basis of postoperative radiographs, the hips were divided into 2 groups (Group I: either the progression of collapse or joint-space narrowing, Group II: neither progression of collapse or joint-space narrowing). The related factors with radiological outcome were analyzed by using multivariate analysis (Stepwise discriminant analysis). Results. Sixty-seven of 74 hips (90.5%) survived without conversion to total hip arthroplasty at final follow-up. The mean preoperative HHS was 60 points (range, 34 to 85 points), which improved to 85 points (range, 51 to 100 points) at final follow-up. Thirteen hips were categorized as Group I and 61 hips as Group II. Both the post-operative intact ratio and type of ON affected the radiological outcome. Regarding post-operative intact ratio, the cutoff point to prevent the progression of collapse was 32.1%, and to prevent both the progression of collapse and joint-space narrowing was 42.6%. Conclusion. The results of this study indicated that the post-operative intact ratio should be at least 32.1%. This critical ratio would be useful for surgical planning in transtrochanteric curved varus osteotomy for ON


Orthopaedic Proceedings
Vol. 92-B, Issue SUPP_I | Pages 202 - 203
1 Mar 2010
Ding C
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Osteoarthritis (OA) is a major public health problem. Plain radiography, which mainly depicts joint-space narrowing and osteophytes, is useful for defining OA, but has weak associations with symptoms, limited sensitivity to change, as well as poor prediction of cartilage loss and the need for joint replacement. MRI, with standard techniques such as fat-saturated, T1-weighted, spoiled gradient echo sequences and T2-weighted, proton-density-weighted fast-spin echo sequences, has been utilized to directly assess knee structural alterations, such as cartilage volume, cartilage defects, subchondral bone changes and meniscal lesions. MRI factors (cartilage defects, bone marrow lesions, meniscal pathology and bone area) as well as clinical risk factors (age, sex, obesity, smoking and muscle strength) can identify subjects at risk of faster cartilage loss. We hypothesize that a combination of genetic factors interacting with environmental factors might establish a cascade of joint changes from subchondral bone expansion to other structural changes, and ultimately, but not inevitably, lead to OA. MRI has, therefore, been invaluable in improving our understanding of early changes in the knee joint


The Bone & Joint Journal
Vol. 104-B, Issue 4 | Pages 486 - 494
4 Apr 2022
Liu W Sun Z Xiong H Liu J Lu J Cai B Wang W Fan C

Aims

The aim of this study was to develop and internally validate a prognostic nomogram to predict the probability of gaining a functional range of motion (ROM ≥ 120°) after open arthrolysis of the elbow in patients with post-traumatic stiffness of the elbow.

Methods

We developed the Shanghai Prediction Model for Elbow Stiffness Surgical Outcome (SPESSO) based on a dataset of 551 patients who underwent open arthrolysis of the elbow in four institutions. Demographic and clinical characteristics were collected from medical records. The least absolute shrinkage and selection operator regression model was used to optimize the selection of relevant features. Multivariable logistic regression analysis was used to build the SPESSO. Its prediction performance was evaluated using the concordance index (C-index) and a calibration graph. Internal validation was conducted using bootstrapping validation.