The goal of this observational study is to collect a large and homogeneous case report of periprosthetic infections in megaprostheses in patients with a history of bone sarcoma.
The incidence of periprosthetic infections (PJI) is high in megaprostheses (MP), 3-30% after primary surgery, up to 60% after prosthetic revision. Patients with megaprosthesis implanted in a primary sarcoma of bone have an increased risk of infection, compared with joint prostheses implanted on arthrosis, due to several factors, including treatment with chemotherapy, extensive periarticular soft tissue sacrifice, and duration of surgery. PJI of an MP can result in important consequences: prolonged hospitalizations, expensive treatments, multiple surgeries, risk of amputation and reduced quality of life. Diagnosis and treatment of MP infections are challenging. Surgery is the focus of treatment, and identification of the microorganism responsible for infection is necessary for diagnostic confirmation and to set up targeted antibiotic treatment. Treatment, similar to standard joint replacement, includes surgical cleaning without implant replacement and complete revision of the prosthesis in one or two stages. Data currently available in the Literature about patients with infection of a megaprosthesis implanted after excision of a bone sarcoma is scarce; in particular, most case series are small and heterogeneous. The aim of this study is to obtain more information about this condition by collecting a large and homogeneous data of PJI in MP, in order to identify predictive factors in the treatment of PJI. The treatments to which the patients underwent and thus analyzed for the study are those expected by normal clinical practice.
Study Type
OBSERVATIONAL
Enrollment
22
IRCCS Azienda Ospedaliero-Universitaria di Bologna
Bologna, Italy
A.O.U Città della Salute e della Scienza di Torino
Torino, Italy
Identification of predictive factors for infection recurrence in patients with PJI: analysis of demographic, prognostic and treatment data.
Demographic information on disease definition, prognosis, treatments provided and outcomes will be summarised using descriptive methods. treatments provided and outcomes, will be summarised using descriptive methods. In in particular, categorical variables will be summarised by means of relative frequency estimation and 95% confidence intervals; continuous variables will be summarised by means of mean and standard deviation, median and range. standard deviation, median and interquartile range. Correlations between variables will be investigated: by means of contingency tables and calculation of the chi-square calculation (applying correction for continuity and/or exact test when necessary) for categorical categorical variables; comparison of means (t-test for paired and unpaired data or non-parametric analogues non-parametric when indicated) for variables distributed on an interval scale.
Time frame: Data covering the period 2010-2020.
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