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Orthopaedic Proceedings
Vol. 106-B, Issue SUPP_19 | Pages 29 - 29
22 Nov 2024
Trebše N Blas M Kanalec T Angelini K Filipič T Levašic V Trebse R
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Aim

There is limited data on the frequency and impact of untoward events such as glove perforation, contamination of the surgical field (drape perforation, laceration, detachment), the unsterile object in the surgical field (hair, sweat droplet…), defecation, elevated air temperature…that may happen in the operating theatre. These events should influence the surgical site infection rate but it is not clear to what extent. We wanted to calculate the frequency and measure the impact of these events on the infection and general revision rate.

Method

In our institution, scrub nurses prospectively and diligently record untoward events in the theatres. We have an institutional implant registry with close to 100% data completion since 2001, and surgeons register complications before discharge. We analysed the respective databases and compared the revision and infection rate in the group with untoward events with the outcome of all arthroplasty patients within the same period. Two-tailed Z statistical test was used for analysis.


Orthopaedic Proceedings
Vol. 104-B, Issue SUPP_10 | Pages 3 - 3
1 Oct 2022
Trebše N Pokorn M
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Aim

metagenomic next-generation sequencing (mNGS) has shown to be a useful method for pathogen detection in prosthetic joint infections (PJI). The technique promises to minimize the PJIs without the known causative agent. Our study aimed to compare diagnostic accuracies of cultures and mNGS.

Method

In this study, a meta-analysis following PRISMA recommendations was performed. PubMed and OVID Medline databases were used for article search. The studies using mNGS whole-genome sequencing method and the ones where PJI diagnosis was based on one of the currently recognized criteria were included. Studies were excluded if they comprised less than twenty cases, the ones with insufficient data for the analyses (true positive, true negative, false positive and false negative values for both mNGS and culture results) and publications with strong duplication bias. Univariate metanalysis using a random-effect model has been performed in R studio with a “meta” package. Pooled sensitivity and pooled specificity were calculated.


Orthopaedic Proceedings
Vol. 103-B, Issue SUPP_5 | Pages 9 - 9
1 Mar 2021
Trebše N Pokorn M
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Aim

Kingella kingae seems to be the most common cause of osteoarticular infections (OAI) in children under 48 months of age (1). Recent studies had shown that K. kingae is poorly susceptible to anti-staphylococcal penicillin and some isolates produce beta-lactamase (2). This led to the need for new treatment guidelines for OAI in populations in which K. kingae is frequent. Our study aimed to design a model which could predict K. kingae OAI in order to initiate appropriate empirical treatment on hospital admission.

Method

We performed a retrospective cohort study in children from 1 month to 15 years old diagnosed with OAI, hospitalized between 2006 and 2018. Mann-Whitney test and Fisher's exact test were used for data analysis. The model predicting K. kingae OAI was designed using logistic regression.