...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>The journal of obstetrics and gynaecology research >Updated meta‐analysis on the diagnostic accuracy of serum anti‐Mullerian hormone in poly cystic ovary syndrome involving 13 509 subjects
【24h】

Updated meta‐analysis on the diagnostic accuracy of serum anti‐Mullerian hormone in poly cystic ovary syndrome involving 13 509 subjects

机译：Updated meta‐analysis on the diagnostic accuracy of serum anti‐Mullerian hormone in poly cystic ovary syndrome involving 13 509 subjects

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相关主题

摘要

Abstract Aim To determine the diagnostic accuracy of anti‐Mullerian hormone (AMH) in the diagnosis of polycystic ovary syndrome (PCOS). Methods Two independent reviewers searched the electronic databases and search engines using PubMed, Cochrane library, and Google Scholar systematically to retrieve relevant articles published from inception to September 2021. The diagnostic efficacy of AMH was computed using the random‐effects model in terms of pooled sensitivity, specificity, and diagnostic odds ratio (DOR) with 95% confidence interval (CI). A meta‐regression and subgroup analysis were performed to check for any source which could explain possible heterogeneity. Risk of bias assessment was conducted using the QUADAS‐2 tool recommended by Cochrane Library. Results This meta‐analysis included a total of 41 studies involving 13?509 subjects. We observed promising pooled sensitivity 0.78 (95% CI 0.74 to 0.81), specificity 0.87 (95% CI 0.84 to 0.90), and diagnostic odds ratio (DOR) 24 (95% CI 15 to 37), for AMH in detecting PCOS and discriminatory power (summary receiver operating characteristic [SROC] curves, 0.89 [95% CI 0.86–0.92]). The most prominent bias was noted in the patient selection and index test assessment. Conclusions With the findings of this current meta‐analysis, we conclude serum AMH to be a promising biomarker for the diagnosis of PCOS, however, substantial heterogeneity among studies needs individual patient data analysis in order to identify an optimal cut‐off value and homogenous findings. Registration Number and Guidelines This meta‐analysis was performed according to constructed protocol registered in the PROSPERO database with registration number CRD42021246910.

著录项

获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号