Dataset Information

Systematic review of risk prediction scores for surgical site infection or periprosthetic joint infection following joint arthroplasty.

ABSTRACT: Accurate identification of individuals at high risk of surgical site infections (SSIs) or periprosthetic joint infections (PJIs) influences clinical decisions and development of preventive strategies. We aimed to determine progress in the development and validation of risk prediction models for SSI or PJI using a systematic review. We searched for studies that have developed or validated a risk prediction tool for SSI or PJI following joint replacement in MEDLINE, EMBASE, Web of Science and Cochrane databases; trial registers and reference lists of studies up to September 2016. Nine studies describing 16 risk scores for SSI or PJI were identified. The number of component variables in a risk score ranged from 4 to 45. The C-index ranged from 0·56 to 0·74, with only three risk scores reporting a discriminative ability of >0·70. Five risk scores were validated internally. The National Healthcare Safety Network SSIs risk models for hip and knee arthroplasties (HPRO and KPRO) were the only scores to be externally validated. Except for HPRO which shows some promise for use in a clinical setting (based on predictive performance and external validation), none of the identified risk scores can be considered ready for use. Further research is urgently warranted within the field.

SUBMITTER: Kunutsor SK

PROVIDER: S-EPMC9203287 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BACKGROUND:The number of periprosthetic joint infections (PJI) after total knee arthroplasty (TKA) is increasing annually. Animal models have been used to clarify their clinical characteristics and the infection mechanism of pathogenic bacteria, However, since the prosthesis design of animal models is not uniform, it is difficult to simulate the environment of clinical PJI. OBJECTIVES:To retrospect the progress on the prosthesis design of animal models of PJI after TKA and to summarize the criteria for evaluating a clinically representative model of PJI. METHODS:This systematic review was reported on the basis of Systematic Reviews and Meta-Analyzes (PRISMA). Pubmed, EMbase, Cochrane Library, Web of Science, Wanfang Data and China National Knowledge Infrastructure were researched for animal models of PJI after TKA from database establishment to April 2019 according to Chinese and English retrieval words, including "periprosthetic joint infections and total knee arthroplasty," "periprosthetic joint infections and model," "periprosthetic joint infections and biofilm," and "total knee arthroplasty and model." RESULTS:A total of 12 quantitative studies were enrolled in our study finally: 8 representative studies described prosthesis designs used in PJI animal models, 4 studies described prosthesis designs in non-infected animal models which were suitable for infection models. The major problems need to be dealed with were prosthesis, installation location, material, the function of separating the articular and medullary cavity, fixation manner, and the procedure of preserving the posterior cruciate ligament. CONCLUSION:A highly representative design of the animal prosthesis of PJI should meet the following criteria: the surface of the prosthesis is smooth with the formation of biofilm, composed of titanium-6Al-4V or cobalt-chromium-molybdenum alloy; prosthesis can bear weight and is highly stable; and it can connect the joint cavity and medullary cavity simultaneously. To reach a more reliable conclusion, further experiments and improvements are required.

Project description:BackgroundPeriprosthetic joint infections (PJIs) are dreaded complications of total joint arthroplasties. The risk of developing PJIs is likely to be influenced by several patient factors such as sociodemographic characteristics, body mass index (BMI), and medical and surgical histories. However, the nature and magnitude of the long-term longitudinal associations between these patient-related factors and risk of developing PJIs are uncertain.ObjectiveTo conduct a systematic review and meta-analysis to assess the associations between several patient-related factors and PJI.Data sourcesMEDLINE, EMBASE, Web of Science, Cochrane Library, and reference lists of relevant studies from inception to September 2015.Study selectionLongitudinal studies with at least one-year of follow-up for PJIs after total joint arthroplasty.Data extraction and synthesisTwo investigators extracted data on study characteristics, methods, and outcomes. A consensus was reached with involvement of a third. The relative risk (RR) with 95% confidence intervals was used as the summary measure of association across studies. Study-specific RRs with 95% confidence intervals were meta-analysed using random effect models and were grouped by study-level characteristics.ResultsSixty-six observational (23 prospective cohort and 43 retrospective cohort or case-control) studies with data on 512,508 participants were included. Comparing males to females and smokers to non-smokers, the pooled RRs for PJI were 1.36 (1.18-1.57) and 1.83 (1.24-2.70) respectively. There was no evidence of any significant associations of PJI with age and high alcohol intake. Comparing BMI ≥ 30 versus < 30 kg/m(2); ≥ 35 versus < 35 kg/m(2); and ≥ 40 versus < 40 kg/m(2); the pooled RRs were 1.60 (1.29-1.99); 1.53 (1.22-1.92); and 3.68 (2.25-6.01) respectively. Histories of diabetes, rheumatoid arthritis, depression, steroid use, and previous joint surgery were also associated with increased risk of PJI. The results remained similar when grouped by relevant study level characteristics.ConclusionsSeveral potentially modifiable patient-related factors are associated with the risk of developing PJIs. Identifying patients with these risk factors who are due to have arthroplasty surgery and modulating these risk factors might be essential in reducing the incidence of PJI. Further research is however warranted to assess the potential clinical utility of these risk factors as risk assessment tools for PJI.Systematic review registrationPROSPERO 2015: CRD42015023485.

Dataset Information

Systematic review of risk prediction scores for surgical site infection or periprosthetic joint infection following joint arthroplasty.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets