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髋臼翻修术的决策/治疗算法。

Decision/therapeutic algorithm for acetabular revisions.

机构信息

Università degli studi di Torino.

University of Turin, Turin, Italy.

出版信息

Acta Biomed. 2020 Dec 30;91(14-S):e2020025. doi: 10.23750/abm.v91i14-S.10999.

Abstract

BACKGROUND AND AIM

Paprosky's classification is currently the most used classification for periacetabular bone defects but its validity and reliability are widely discussed in literature. Aim of this study was to introduce a new CT-based Acetabular Revision Algorithm (CT-ARA) and to evaluate its validity. The CT-ARA is based on the integrity of five anatomical structures that support the acetabulum. Classification's groups are defined by the deficiency of one or more of these structures, treatment is based on those groups.

METHODS

In 105 patients the validity of the CT-ARA was retrospectively evaluated using preoperative X-rays, CT-scan and surgery reports. The surgical indications suggested by Paprosky's algorithm and by CT-ARA were compared with the final surgical technique. Patients were divided into two groups according to time of surgery.

RESULTS

We reported concordance of indications in 56,2% of cases with the Paprosky's algorithm and in 63,8% of cases with the CT-ARA. Analysing only the most recent surgeries (group 2), we reported even higher difference of concordance (67,3% Paprosky's algorithm and 83,7% CT-ARA). The concordance of the CT-ARA among Group 1 and Group 2 resulted significantly different.

CONCLUSIONS

the CT-ARA may be a useful tool for the preoperative decision-making process and showed more correlation with performed surgery compared to the Paprosky's algorithm.

摘要

背景与目的

Paprosky 分类法是目前最常用于髋臼骨缺损的分类方法,但文献中广泛讨论了其有效性和可靠性。本研究旨在介绍一种新的基于 CT 的髋臼翻修算法(CT-ARA)并评估其有效性。CT-ARA 基于支撑髋臼的五个解剖结构的完整性。分类的组别由这些结构之一或多个结构的缺陷定义,治疗基于这些组别。

方法

在 105 例患者中,回顾性评估了术前 X 线、CT 扫描和手术报告的 CT-ARA 有效性。比较了 Paprosky 算法和 CT-ARA 提示的手术指征与最终手术技术。根据手术时间将患者分为两组。

结果

我们报告了与 Paprosky 算法的指征一致的病例有 56.2%,与 CT-ARA 的指征一致的病例有 63.8%。仅分析最近的手术(第 2 组),我们报告了更高的一致性差异(Paprosky 算法为 67.3%,CT-ARA 为 83.7%)。第 1 组和第 2 组的 CT-ARA 一致性差异显著。

结论

CT-ARA 可能是术前决策过程的有用工具,与 Paprosky 算法相比,它与实际进行的手术具有更高的相关性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4851/7944694/2f5b559bac66/ACTA-91-25-g001.jpg

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