Understanding spinopelvic mechanics is important for the success of total hip arthroplasty (THA). Despite significant advancements in appreciating spinopelvic balance, numerous challenges remain. It is crucial to recognize the individual variability and postoperative changes in spinopelvic parameters and their consequential impact on prosthetic component positioning to mitigate the risk of dislocation and enhance postoperative outcomes. This review describes the integration of advanced diagnostic approaches, enhanced technology, implant considerations, and surgical planning, all tailored to the unique anatomy and biomechanics of each patient. It underscores the importance of accurately predicting postoperative spinopelvic mechanics, selecting suitable imaging techniques, establishing a consistent nomenclature for spinopelvic stiffness, and considering implant-specific strategies. Furthermore, it highlights the potential of artificial intelligence to personalize care. Cite this article:
Aims. The surgical treatment of tuberculosis (TB) of the
To systematically evaluate whether bracing can effectively achieve curve regression in patients with adolescent idiopathic scoliosis (AIS), and to identify any predictors of curve regression after bracing. Two independent reviewers performed a comprehensive literature search in PubMed, Ovid, Web of Science, Scopus, and Cochrane Library to obtain all published information about the effectiveness of bracing in achieving curve regression in AIS patients. Search terms included “brace treatment” or “bracing,” “idiopathic scoliosis,” and “curve regression” or “curve reduction.” Inclusion criteria were studies recruiting patients with AIS undergoing brace treatment and one of the study outcomes must be curve regression or reduction, defined as > 5° reduction in coronal Cobb angle of a major curve upon bracing completion. Exclusion criteria were studies including non-AIS patients, studies not reporting p-value or confidence interval, animal studies, case reports, case series, and systematic reviews. The GRADE approach to assessing quality of evidence was used to evaluate each publication.Aims
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To determine the major risk factors for unplanned reoperations (UROs) following corrective surgery for adult spinal deformity (ASD) and their interactions, using machine learning-based prediction algorithms and game theory. Patients who underwent surgery for ASD, with a minimum of two-year follow-up, were retrospectively reviewed. In total, 210 patients were included and randomly allocated into training (70% of the sample size) and test (the remaining 30%) sets to develop the machine learning algorithm. Risk factors were included in the analysis, along with clinical characteristics and parameters acquired through diagnostic radiology.Aims
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Spinopelvic pathology increases the risk for instability following total hip arthroplasty (THA), yet few studies have evaluated how pathology varies with age or sex. The aims of this study were: 1) to report differences in spinopelvic parameters with advancing age and between the sexes; and 2) to determine variation in the prevalence of THA instability risk factors with advancing age. A multicentre database with preoperative imaging for 15,830 THA patients was reviewed. Spinopelvic parameter measurements were made by experienced engineers, including anterior pelvic plane tilt (APPT), spinopelvic tilt (SPT), sacral slope (SS), lumbar lordosis (LL), and pelvic incidence (PI). Lumbar flexion (LF), sagittal spinal deformity, and hip user index (HUI) were calculated using parameter measurements.Aims
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