This systematic review aimed to summarize the full range of complications reported following ankle arthroscopy and the frequency at which they occur. A computer-based search was performed in PubMed, Embase, Emcare, and ISI Web of Science. Two-stage title/abstract and full-text screening was performed independently by two reviewers. English-language original research studies reporting perioperative complications in a cohort of at least ten patients undergoing ankle arthroscopy were included. Complications were pooled across included studies in order to derive an overall complication rate. Quality assessment was performed using the Oxford Centre for Evidence-Based Medicine levels of evidence classification.Aims
Methods
Literature surrounding artificial intelligence (AI)-related applications for hip and knee arthroplasty has proliferated. However, meaningful advances that fundamentally transform the practice and delivery of joint arthroplasty are yet to be realized, despite the broad range of applications as we continue to search for meaningful and appropriate use of AI. AI literature in hip and knee arthroplasty between 2018 and 2021 regarding image-based analyses, value-based care, remote patient monitoring, and augmented reality was reviewed. Concerns surrounding meaningful use and appropriate methodological approaches of AI in joint arthroplasty research are summarized. Of the 233 AI-related orthopaedics articles published, 178 (76%) constituted original research, while the rest consisted of editorials or reviews. A total of 52% of original AI-related research concerns hip and knee arthroplasty (n = 92), and a narrative review is described. Three studies were externally validated. Pitfalls surrounding present-day research include conflating vernacular (“AI/machine learning”), repackaging limited registry data, prematurely releasing internally validated prediction models, appraising model architecture instead of inputted data, withholding code, and evaluating studies using antiquated regression-based guidelines. While AI has been applied to a variety of hip and knee arthroplasty applications with limited clinical impact, the future remains promising if the question is meaningful, the methodology is rigorous and transparent, the data are rich, and the model is externally validated. Simple checkpoints for meaningful AI adoption include ensuring applications focus on: administrative support over clinical evaluation and management; necessity of the advanced model; and the novelty of the question being answered. Cite this article:
Whether to perform hybrid surgery (HS) in contrast to anterior cervical discectomy and fusion (ACDF) when treating patients with multilevel cervical disc degeneration remains a controversial subject. To resolve this we have undertaken a meta-analysis comparing the outcomes from HS with ACDF in this condition. Seven databases were searched for studies of HS and ACDF from inception of the study to 1 September 2019. Both random-effects and fixed-effects models were used to evaluate the overall effect of the C2-C7 range of motion (ROM), ROM of superior/inferior adjacent levels, adjacent segment degeneration (ASD), heterotopic ossification (HO), complications, neck disability index (NDI) score, visual analogue scale (VAS) score, Japanese Orthopaedic Association (JOA) score, Odom’s criteria, blood loss, and operating and hospitalization time. To obtain more credible results contour-enhanced funnel plots, Egger’s and Begg’s tests, meta-regression, and sensitivity analyses were performed.Aims
Methods
The aims of this study were to validate the outcome of total elbow arthroplasty (TEA) in patients with rheumatoid arthritis (RA), and to identify factors that affect the outcome. We searched PubMed, MEDLINE, Cochrane Reviews, and Embase from between January 2003 and March 2019. The primary aim was to determine the implant failure rate, the mode of failure, and risk factors predisposing to failure. A secondary aim was to identify the overall complication rate, associated risk factors, and clinical performance. A meta-regression analysis was completed to identify the association between each parameter with the outcome.Aims
Methods
We performed a meta-analysis investigating the association between preoperative psychological distress and postoperative pain and function after total knee arthroplasty (TKA). Pubmed/Medline, Embase, PsycINFO, and the Cochrane library were searched for studies on the influence of preoperative psychological distress on postoperative pain and physical function after TKA. Two blinded reviewers screened for eligibility and assessed the risk of bias and the quality of evidence. We used random effects models to pool data for the meta-analysis.Aims
Materials and Methods
