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The Bone & Joint Journal
Vol. 106-B, Issue 2 | Pages 151 - 157
1 Feb 2024
Dreyer L Bader C Flörkemeier T Wagner M

Aims

The risk of mechanical failure of modular revision hip stems is frequently mentioned in the literature, but little is currently known about the actual clinical failure rates of this type of prosthesis. The current retrospective long-term analysis examines the distal and modular failure patterns of the Prevision hip stem from 18 years of clinical use. A design improvement of the modular taper was introduced in 2008, and the data could also be used to compare the original and the current design of the modular connection.

Methods

We performed an analysis of the Prevision modular hip stem using the manufacturer’s vigilance database and investigated different mechanical failure patterns of the hip stem from January 2004 to December 2022.


The Bone & Joint Journal
Vol. 102-B, Issue 12 | Pages 1629 - 1635
1 Dec 2020
Wang Q Sheng N Rui B Chen Y

Aims

The aim of this study was to explore why some calcar screws are malpositioned when a proximal humeral fracture is treated by internal fixation with a locking plate, and to identify risk factors for this phenomenon. Some suggestions can be made of ways to avoid this error.

Methods

We retrospectively identified all proximal humeral fractures treated in our institution between October 2016 and October 2018 using the hospital information system. The patients’ medical and radiological data were collected, and we divided potential risk factors into two groups: preoperative factors and intraoperative factors. Preoperative factors included age, sex, height, weight, body mass index, proximal humeral bone mineral density, type of fracture, the condition of the medial hinge, and medial metaphyseal head extension. Intraoperative factors included the grade of surgeon, neck-shaft angle after reduction, humeral head height, restoration of medial support, and quality of reduction. Adjusted binary logistic regression and multivariate logistic regression models were used to identify pre- and intraoperative risk factors. Area under the curve (AUC) analysis was used to evaluate the discriminative ability of the multivariable model.