Clinical management of open fractures is challenging and frequently requires complex reconstruction procedures. The Gustilo-Anderson classification lacks uniform interpretation, has poor interobserver reliability, and fails to account for injuries to musculotendinous units and bone. The Ganga Hospital Open Injury Severity Score (GHOISS) was designed to address these concerns. The major aim of this review was to ascertain the evidence available on accuracy of the GHOISS in predicting successful limb salvage in patients with mangled limbs. We searched electronic data bases including PubMed, CENTRAL, EMBASE, CINAHL, Scopus, and Web of Science to identify studies that employed the GHOISS risk tool in managing complex limb injuries published from April 2006, when the score was introduced, until April 2021. Primary outcome was the measured sensitivity and specificity of the GHOISS risk tool for predicting amputation at a specified threshold score. Secondary outcomes included length of stay, need for plastic surgery, deep infection rate, time to fracture union, and functional outcome measures. Diagnostic test accuracy meta-analysis was performed using a random effects bivariate binomial model.Aims
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The goal of the current systematic review was to assess the impact of implant placement accuracy on outcomes following total knee arthroplasty (TKA). A systematic review was performed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines using the Ovid Medline, Embase, Cochrane Central, and Web of Science databases in order to assess the impact of the patient-reported outcomes measures (PROMs) and implant placement accuracy on outcomes following TKA. Studies assessing the impact of implant alignment, rotation, size, overhang, or condylar offset were included. Study quality was assessed, evidence was graded (one-star: no evidence, two-star: limited evidence, three-star: moderate evidence, four-star: strong evidence), and recommendations were made based on the available evidence.Aims
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