five

Assessment of certainty of evidence.

收藏
NIAID Data Ecosystem2026-05-02 收录
下载链接:
https://figshare.com/articles/dataset/Assessment_of_certainty_of_evidence_/28771977
下载链接
链接失效反馈
官方服务:
资源简介:
Introduction This systematic review and meta-analysis aimed to evaluate the success rate of pulpotomy in permanent teeth using ProRoot MTA. Methods An unrestricted search was carried out in 6 electronic databases, until August 2024. The selection of studies adhered to the PIOS criteria, encompassing only randomized clinical trials that assessed the success rate of pulpotomy in permanent teeth using ProRoot MTA through clinical and radiographic evaluations. Risk of bias was assessed using the RoB-2 tool, and meta-analyses were conducted through RevMan 5.3 and R software. To determine the quality of evidence, the GRADE tool was employed. Results The initial search yielded 971 studies. After removing duplicates, 468 studies underwent initial screening, and 32 studies were considered for eligibility. In the final selection, 26 studies were included, and among these, 14 were categorized as having high risk of bias. The analysis of pulpotomy in permanent teeth using ProRoot MTA revealed an overall success rate of 96%, 90%, and 96% at 6-, 12-, and 24-month follow-up periods, respectively, and an annual failure rate of 8%. Meta-analyses indicated a significantly higher success rate for pulpotomies in teeth with open apex. Upon applying the GRADE assessment, an overall moderate level of evidence was observed. Conclusion Pulpotomy in permanent teeth using ProRoot MTA yields a success rate exceeding 90%, even up to a 24-month follow-up period. Nonetheless, the certainty of evidence supporting these outcomes is moderate, highlighting the requirement for well-designed randomized clinical trials with extended follow-up durations. Registration This systematic review was registered in the PROSPERO database (registration number CRD42023451466).
创建时间:
2025-04-10
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作