Takács Anna, Hardi Eszter, Cavalcante Bianca Golzio Navarro, Szabó Bence, Kispélyi Barbara, Joób-Fancsaly Árpád, Mikulás Krisztina, Varga Gábor, Hegyi Péter, Kivovics Márton
Department of Community Dentistry, Semmelweis University, Szentkirályi utca 40. 1088 Budapest, Hungary; Centre for Translational Medicine, Semmelweis University, Üllői út 26. 1085 Budapest, Hungary.
Centre for Translational Medicine, Semmelweis University, Üllői út 26. 1085 Budapest, Hungary; Department of Oro-Maxillofacial Surgery and Stomatology, Semmelweis University, Mária utca 52. 1085 Budapest, Hungary.
J Dent. 2023 Dec;139:104748. doi: 10.1016/j.jdent.2023.104748. Epub 2023 Oct 19.
This meta-analysis aimed to determine the accuracy of currently available computer-assisted implant surgery (CAIS) modalities under in vitro conditions and investigate whether these novel techniques can achieve clinically acceptable accuracy.
In vitro studies comparing the postoperative implant position with the preoperative plan were included. Risk of bias was assessed using the Quality Assessment Tool For In Vitro Studies (QUIN Tool) and a sensitivity analysis was conducted using funnel plots.
A systematic search was performed on April 18, 2023, using the following three databases: MEDLINE (via PubMed), EMBASE, and Cochrane Central Register of Controlled Trials. No filters or restrictions were applied during the search.
A total of 5,894 studies were included following study selection. Robotic- and static CAIS (sCAIS) had the most accurate and clinically acceptable outcomes. sCAIS was further divided according to the guidance level. Among the sCAIS groups, fully guided implant placement had the greatest accuracy. Augmented reality-based CAIS (AR-based CAIS) had clinically acceptable results for all the outcomes except for apical global deviation. Dynamic CAIS (dCAIS) demonstrated clinically safe results, except for horizontal apical deviation. Freehand implant placement was associated with the greatest number of errors.
Fully guided sCAIS demonstrated the most predictable outcomes, whereas freehand sCAIS demonstrated the lowest accuracy. AR-based and robotic CAIS may be promising alternatives.
To our knowledge, this is the first meta-analysis to evaluate the accuracy of robotic CAIS and investigate the accuracy of various CAIS modalities.
本荟萃分析旨在确定目前可用的计算机辅助种植手术（CAIS）模式在体外条件下的准确性，并研究这些新技术是否能达到临床可接受的准确性。
纳入了比较术后种植体位置与术前计划的体外研究。使用体外研究质量评估工具（QUIN工具）评估偏倚风险，并使用漏斗图进行敏感性分析。
于2023年4月18日使用以下三个数据库进行了系统检索：MEDLINE（通过PubMed）、EMBASE和Cochrane对照试验中央注册库。检索过程中未应用任何筛选或限制。
经过研究筛选，共纳入5894项研究。机器人辅助和静态CAIS（sCAIS）的结果最准确且临床可接受。sCAIS根据引导水平进一步细分。在sCAIS组中，完全引导式种植体植入的准确性最高。除根尖整体偏差外，基于增强现实的CAIS（AR-CAIS）在所有结果方面均具有临床可接受的结果。动态CAIS（dCAIS）除水平根尖偏差外，显示出临床安全的结果。徒手种植体植入的误差数量最多。
完全引导式sCAIS显示出最可预测的结果，而徒手sCAIS的准确性最低。基于AR和机器人辅助的CAIS可能是有前景的替代方案。
据我们所知，这是第一项评估机器人辅助CAIS准确性并研究各种CAIS模式准确性的荟萃分析。
