five

Supplementary Material for: Ablation Surgeries for Treatment-Resistant Depression: A Meta-Analysis and Systematic Review of Reported Case Series

收藏
Figshare2022-08-16 更新2026-04-28 收录
下载链接:
https://figshare.com/articles/dataset/Supplementary_Material_for_Ablation_Surgeries_for_Treatment-Resistant_Depression_A_Meta-Analysis_and_Systematic_Review_of_Reported_Case_Series/20496564
下载链接
链接失效反馈
官方服务:
资源简介:
Background and Objectives: Ablative lesion procedures remain as the last option in treatment of refractory depression. Contemporary ablative psychosurgeries involve producing lesions in the anterior limb of the internal capsule (bilateral anterior capsulotomy – BAC), the supragenual anterior cingulate gyrus and cingulum (bilateral anterior cingulotomy – BACING), and subgenual anterior cingulate gyrus and subcortical orbitofrontal white matter (bilateral subcaudate tractotomy – BST). A combination of BACING and BST is known as limbic leukotomy (bilateral limbic leukotomy – BLL). All procedures claim some success, but cohorts are small, depression assessment instruments differ, and inclusion and outcome criteria and follow-up duration vary. In some cohorts, more than one type of surgery was performed in several patients, further confounding interpreting the available data. Current evidence is equivocal on which surgical target works best. Method and Aim: This systematic review and meta-analysis using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) standard on published cohorts was conducted to review and identify which is the best standalone ablative procedure for treatment-resistant depression (TRD) based on response rate (event rate) and adverse-effect profile using the Comprehensive Meta-Analysis software. Results and Conclusion: As a standalone neurosurgical procedure, we found that BAC appears to be the most effective and safest of all the ablative targets for TRD. A major limitation of this conclusion is the paucity of published case series where sample sizes are small and all are open label.
创建时间:
2022-08-16
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