five

Characteristics of the included studies.

收藏
NIAID Data Ecosystem2026-05-01 收录
下载链接:
https://figshare.com/articles/dataset/Characteristics_of_the_included_studies_/24641106
下载链接
链接失效反馈
官方服务:
资源简介:
Background Abdominal tuberculosis (TB) is a severe extrapulmonary TB, which can lead to serious complications. Early diagnosis and treatment are very important for the prognosis and the diagnosis of abdominal TB is still difficult. Methods We searched PubMed, the Cochrane Library, Embase, China National Knowledge Infrastructure, and the Wanfang database for studies evaluating the diagnostic accuracy of NAATs for abdominal TB until August 2020. Any types of study design with full text were sought and included. The risk of bias was assessed using the Quality Assessment of Diagnostic Accuracy Studies tool. Subgroup analysis, meta-regression analysis and sensitivity analysis were used to explore the sources of heterogeneity. Stata version 15.0 with the midas command packages was used to carry out meta-analyses. Results We included a total of 78 independent studies from 53 articles; 64 with CRS as the reference standard, and 14 with culture as the reference standard. The pooled sensitivity, specificity, and the areas under summary receiver operating characteristic (SROC) curves (AUC) were 58% (51%–64%; I2 = 87%), 99% (97%–99%; I2 = 81%), and 0.92 (0.89–0.94) compared with CRS, respectively. The pooled sensitivity, specificity, and the AUC values of the SROC were 80% (66%–90%; I2 = 56%), 96% (92%–98%; I2 = 84%), and 0.97 (0.95–0.98) compared with culture, respectively. The heterogeneity of sensitivity and specificity was significant. Conclusions NAATs had excellent efficacy in the diagnosis of abdominal TB regardless of the reference standard and regardless of the subtype of abdominal TB. Multiplex PCR with multiple target genes may improve diagnostic sensitivity, and stool specimens may also be used for the diagnosis of abdominal TB in addition to tissue and ascites.
创建时间:
2023-11-27
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