The PJI-TNM classification for periprosthetic joint infections.

IF 4.7 2区 医学 Q2 CELL & TISSUE ENGINEERING
Susanne Baertl, Markus Rupp, Maximilian Kerschbaum, Mario Morgenstern, Florian Baumann, Christian Pfeifer, Michael Worlicek, Daniel Popp, Derek F Amanatullah, Volker Alt
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引用次数: 0

Abstract

Aims: This study aimed to evaluate the clinical application of the PJI-TNM classification for periprosthetic joint infection (PJI) by determining intraobserver and interobserver reliability. To facilitate its use in clinical practice, an educational app was subsequently developed and evaluated.

Methods: A total of ten orthopaedic surgeons classified 20 cases of PJI based on the PJI-TNM classification. Subsequently, the classification was re-evaluated using the PJI-TNM app. Classification accuracy was calculated separately for each subcategory (reinfection, tissue and implant condition, non-human cells, and morbidity of the patient). Fleiss' kappa and Cohen's kappa were calculated for interobserver and intraobserver reliability, respectively.

Results: Overall, interobserver and intraobserver agreements were substantial across the 20 classified cases. Analyses for the variable 'reinfection' revealed an almost perfect interobserver and intraobserver agreement with a classification accuracy of 94.8%. The category 'tissue and implant conditions' showed moderate interobserver and substantial intraobserver reliability, while the classification accuracy was 70.8%. For 'non-human cells,' accuracy was 81.0% and interobserver agreement was moderate with an almost perfect intraobserver reliability. The classification accuracy of the variable 'morbidity of the patient' reached 73.5% with a moderate interobserver agreement, whereas the intraobserver agreement was substantial. The application of the app yielded comparable results across all subgroups.

Conclusion: The PJI-TNM classification system captures the heterogeneity of PJI and can be applied with substantial inter- and intraobserver reliability. The PJI-TNM educational app aims to facilitate application in clinical practice. A major limitation was the correct assessment of the implant situation. To eliminate this, a re-evaluation according to intraoperative findings is strongly recommended.

假体周围关节感染的 PJI-TNM 分类。
目的:本研究旨在通过确定观察者内部和观察者之间的可靠性,评估PJI-TNM分类在假体周围关节感染(PJI)中的临床应用。为便于在临床实践中使用,研究人员随后开发并评估了一款教育应用程序:方法:共有 10 名骨科医生根据 PJI-TNM 分类法对 20 例 PJI 病例进行了分类。随后,使用 PJI-TNM 应用程序对分类进行了重新评估。分别计算了每个子类别(再感染、组织和植入物状况、非人类细胞和患者发病率)的分类准确性。弗莱斯卡帕和科恩卡帕分别用于计算观察者间和观察者内的可靠性:总体而言,在 20 个分类病例中,观察者之间和观察者内部的一致性都很高。对变量 "再感染 "的分析表明,观察者间和观察者内的一致性几乎达到了完美的程度,分类准确率为 94.8%。在 "组织和植入物条件 "类别中,观察者间的可靠性和观察者内的可靠性均处于中等水平,分类准确率为 70.8%。非人类细胞 "的准确率为 81.0%,观察者之间的一致性为中等,观察者内部的可靠性几乎为完美。病人发病率 "变量的分类准确率为 73.5%,观察者之间的一致性为中等,而观察者内部的一致性则很高。结论:PJI-TNM 分级系统在所有亚组中的应用结果都具有可比性:结论:PJI-TNM 分类系统捕捉到了 PJI 的异质性,其应用在观察者之间和观察者内部的可靠性都很高。PJI-TNM教育应用程序旨在促进临床实践中的应用。一个主要限制因素是对植入情况的正确评估。为消除这一问题,强烈建议根据术中发现进行重新评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Bone & Joint Research
Bone & Joint Research CELL & TISSUE ENGINEERING-ORTHOPEDICS
CiteScore
7.40
自引率
23.90%
发文量
156
审稿时长
12 weeks
期刊介绍: The gold open access journal for the musculoskeletal sciences. Included in PubMed and available in PubMed Central.
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