Can Machine Learning Methods Produce Accurate and Easy-to-Use Preoperative Prediction Models of One-Year Improvements in Pain and Functioning After Knee Arthroplasty?

BackgroundApproximately 15%-20% of total knee arthroplasty (TKA) patients do not experience clinically meaningful improvements. We sought to compare the accuracy and parsimony of several machine learning strategies for developing predictive models of failing to experience minimal clinically important differences in patient-reported outcome measures (PROMs) 1 year after TKA.MethodsPatients (N = 587) in 3 large Veteran Health Administration facilities completed PROMs before and 1 year after TKA (92% follow-up). Preoperative PROMs and electronic health record data were used to develop and validate models to predict failing to experience at least a minimal clinically important difference in Knee Injury and Osteoarthritis Outcome Score (KOOS) Total, KOOS JR, and KOOS subscales (Pain, Symptoms, Activities of Daily Living, Quality of Life, and recreation). Several machine learning strategies were used for model development. Ten-fold cross-validation and bootstrapping were used to produce measures of overall accuracy (C-statistic, Brier Score). The sensitivity and specificity of various predicted probability cut-points were examined.ResultsThe most accurate models produced were for the Activities of Daily Living, Pain, Symptoms, and Quality of Life subscales of the KOOS (C-statistics 0.76, 0.72, 0.72, and 0.71, respectively). Strategies varied substantially in terms of the numbers of inputs required to achieve similar accuracy, with none being superior for all outcomes.ConclusionModels produced in this project provide estimates of patient-specific improvements in major outcomes 1 year after TKA. Integrating these models into clinical decision support, informed consent and shared decision making could improve patient selection, education, and satisfaction.Level of EvidenceLevel III, diagnostic study.     

High Rates of Spacer Fracture in the Setting of Extended Trochanteric Osteotomy With a Specific Thin-Core Articulating Antibiotic Hip Spacer

BackgroundTwo-stage revision remains the standard of care for prosthetic joint infection after total hip arthroplasty. However, there are substantial complications associated with articulating antibiotic hip spacers. Handmade and molded spacers have been shown to have higher rates of spacer fracture than antibiotic-coated prostheses (ACPs). The aim of this study is to review outcomes with an implant that is often categorized as an ACP spacer, the Zimmer-Biomet StageOne Select Femoral Spacer (ZBSO).MethodsA retrospective review was performed of 63 patients who underwent placement of a ZBSO. Patients were compared based on whether or not an extended trochanteric osteotomy (ETO) was performed using Fisher’s exact and t-tests.ResultsFive patients were excluded due to lack of follow-up or death shortly after stage 1 surgery, leaving 58 patients. Spacer fracture was noted in 5 of 58 patients (8.6%). Sixteen patients underwent ETO and 25.0% suffered a spacer fracture compared to 2.3% without ETO (odds ratio 13.7, P = .0248). There was no association between patient demographics or ETO length and spacer fracture. Two patients had periprosthetic fractures (3.4%) and 4 had dislocations (6.9%). Forty-nine patients (84.4%) went on to second-stage revision; of those 26.5% failed to clear the infection and required an average of 2.2 additional surgeries.ConclusionThe ZBSO spacer has overall complication rates similar to previously reported spacer series. Although the ZBSO looks like an ACP spacer, in the setting of ETO, it behaves like a molded or handmade spacer with a high rate of spacer fracture (25%) due to the small diameter of the core. This implant should be used with caution in combination with an ETO.     

Resumen ejecutivo del Documento de Consenso de la Sociedad Española de Enfermedades Infecciosas y Microbiología Clínica (SEIMC) y de la Asociación Española de Cirujanos (AEC) en profilaxis antibiótica en cirugía

Antibiotic prophylaxis in surgery is one of the most effective measures for preventing surgical site infection, although its use is frequently inadequate and may even increase the risk of infection, toxicities and antimicrobial resistance. As a result of advances in surgical techniques and the emergence of multidrug-resistant organisms, the current guidelines for prophylaxis need to be revised.The Sociedad Española de Enfermedades Infecciosas (Spanish Society of Infectious Diseases and Clinical Microbiology) (SEIMC) together with the Asociación Española de Cirujanos (Spanish Association of Surgeons) (AEC) have revised and updated the recommendations for antibiotic prophylaxis in surgery to adapt them to any type of surgical intervention and to current epidemiology. This document gathers together the recommendations on antimicrobial prophylaxis in the various procedures, with doses, duration, prophylaxis in special patient groups, and in epidemiological settings of multidrug resistance to facilitate standardized management and the safe, effective and rational use of antibiotics in elective surgery.     

Der neue § 2a im Notfallsanitätergesetz – endlich!

Notfall + Rettungsmedizin -