全牙弓种植体支撑框架的数字化与传统工作流程的体外准确性 - 范围审查。

IF 1.8
Lea S Prott, Laurel Graham, Petra C Gierthmuehlen, Markus B Blatz
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引用次数: 0

摘要

目的:调查现有证据表明,全牙弓种植体支持骨架的传统和数字化工作流程的准确性。材料和方法:根据 Arksey 和 O'Malley 的 5 阶段框架进行了范围审查。按照 PRISMA 指南进行了系统性文献检索,以确定在制作全牙弓种植体支持骨架时对传统方法和数字化方法进行直接比较的研究。研究纳入了 2000 年至 2024 年间发表的 58 项体外研究,重点是至少有四个种植体的无牙弓。对所报告的结果进行了研究,以确定将单个误差累加为工作流程累积误差的统计分析的价值。结果:有证据表明,全牙弓种植体支持框架的数字化和传统工作流程都可以进行准确性评估。然而,采用相同评估方法和结果单位的研究似乎也过于分散,无法对误差累积进行统计分析。虽然在印模和铸造阶段没有达成共识,但与传统铸造相比,数字化技术在制作全牙弓种植体支持骨架时显示出更高的准确性。结论目前还缺乏对整个工作流程的准确性进行评估并对其临床相关性进行分类的体外研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
In Vitro Accuracy of Digital Versus Conventional Workflows for Complete-Arch Implant- Supported Frameworks-A Scoping Review.

Purpose: To investigate the available evidence on the accuracy of conventional and digital workflows for complete-arch implant-supported frameworks.

Materials and methods: This scoping review was conducted according to the five-stage framework of Arksey and O'Malley. A systematic literature search was performed adhering to the PRISMA guidelines to identify studies with a direct comparison of conventional and digital methods for the fabrication of complete-arch implant-supported frameworks. A total of 58 in vitro studies with a focus on edentulous arches with at least four implants published between 2000 and 2024 were included. The reported outcomes were examined to determine the value of a statistical analysis in estimating the cumulative workflow error from the individual errors at each stage.

Results: Evidence on the accuracy assessment of digital and conventional workflows for complete-arch implant-supported frameworks is available. However, studies with the same assessment methods and outcome units appear to be too heterogeneous to perform a statistical analysis of error accumulation. While there is no consensus in the impression and cast fabrication stage, digital techniques show superior accuracy for the fabrication of complete-arch implant-supported frameworks compared to conventional casting.

Conclusions: In vitro studies assessing the accuracy of entire workflows and classifying their outcomes regarding clinical relevance are lacking.

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