To map literature on prognostic factors related to outcomes of revision total knee arthroplasty (rTKA), to identify extensively studied factors and to guide future research into what domains need further exploration. We performed a systematic literature search in MEDLINE, Embase, and Web of Science. The search string included multiple synonyms of the following keywords: "revision TKA", "outcome" and "prognostic factor". We searched for studies assessing the association between at least one prognostic factor and at least one outcome measure after rTKA surgery. Data on sample size, study design, prognostic factors, outcomes, and the direction of the association was extracted and included in an evidence map.Aims
Methods
Periprosthetic joint infection (PJI) demonstrates the most feared complication after total joint replacement (TJR). The current work analyzes the demographic, comorbidity, and complication profiles of all patients who had in-hospital treatment due to PJI. Furthermore, it aims to evaluate the in-hospital mortality of patients with PJI and analyze possible risk factors in terms of secondary diagnosis, diagnostic procedures, and complications. In a retrospective, cross-sectional study design, we gathered all patients with PJI (International Classification of Diseases (ICD)-10 code: T84.5) and resulting in-hospital treatment in Germany between 1 January 2019 and 31 December 2022. Data were provided by the Institute for the Hospital Remuneration System in Germany. Demographic data, in-hospital deaths, need for intensive care therapy, secondary diagnosis, complications, and use of diagnostic instruments were assessed. Odds ratios (ORs) with 95% confidence intervals (CIs) for in-hospital mortality were calculated.Aims
Methods
To identify variables independently associated with same-day discharge (SDD) of patients following revision total knee arthroplasty (rTKA) and to develop machine learning algorithms to predict suitable candidates for outpatient rTKA. Data were obtained from the American College of Surgeons National Quality Improvement Programme (ACS-NSQIP) database from the years 2018 to 2020. Patients with elective, unilateral rTKA procedures and a total hospital length of stay between zero and four days were included. Demographic, preoperative, and intraoperative variables were analyzed. A multivariable logistic regression (MLR) model and various machine learning techniques were compared using area under the curve (AUC), calibration, and decision curve analysis. Important and significant variables were identified from the models.Aims
Methods
Patients with proximal femoral fractures (PFFs) are often multimorbid, thus unplanned readmissions following surgery are common. We therefore aimed to analyze 30-day and one-year readmission rates, reasons for, and factors associated with, readmission risk in a cohort of patients with surgically treated PFFs across Austria. Data from 11,270 patients with PFFs, treated surgically (osteosyntheses, n = 6,435; endoprostheses, n = 4,835) at Austrian hospitals within a one-year period (January to December 2021) was retrieved from the Leistungsorientierte Krankenanstaltenfinanzierung (Achievement-Oriented Hospital Financing). The 30-day and one-year readmission rates were reported. Readmission risk for any complication, as well as general medicine-, internal medicine-, and surgery/injury-associated complications, and factors associated with readmissions, were investigated.Aims
Methods
