Comparison of fetal heart rate baseline estimation by the cardiotocograph network and clinicians: a multidatabase retrospective assessment study

被引:4
作者
Bai, Jieyun [1 ,2 ,3 ]
Pan, Xiuyu [4 ]
Lu, Yaosheng [1 ,2 ]
Zhong, Mei [5 ]
Wang, Huijin [2 ]
Zheng, Zheng [4 ]
Guo, Xiaohui [6 ]
机构
[1] Jinan Univ, Guangdong Prov Key Lab Tradit Chinese Med Informat, Guangzhou, Peoples R China
[2] Jinan Univ, Coll Informat Sci & Technol, Guangzhou, Peoples R China
[3] Univ Auckland, Auckland Bioengnieering Inst, Auckland, New Zealand
[4] Guangzhou Med Univ, Guangzhou Women & Childrens Med Ctr, Dept Obstet & Gynecol, Preterm Birth Prevent & Treatment Res Unit, Guangzhou, Peoples R China
[5] NanFang Hosp Southen Med Univ, Dept Obstet, Guangzhou, Peoples R China
[6] Shenzhen Peoples Hosp, Dept Obstet, Shenzhen, Peoples R China
关键词
artificial intelligence; deep learning; fetal heart rate; baseline; computer analysis; COMPUTERIZED ANALYSIS; CONSENSUS; CTG;
D O I
10.3389/fcvm.2023.1059211
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Background: This study aims to compare the fetal heart rate (FHR) baseline predicted by the cardiotocograph network (CTGNet) with that estimated by clinicians.Material and methods: A total of 1,267 FHR recordings acquired with different electrical fetal monitors (EFM) were collected from five datasets: 84 FHR recordings acquired with F15 EFM (Edan, Shenzhen, China) from the Guangzhou Women and Children's Medical Center, 331 FHR recordings acquired with SRF618B5 EFM (Sanrui, Guangzhou, China), 234 FHR recordings acquired with F3 EFM (Lian-Med, Guangzhou, China) from the NanFang Hospital of Southen Medical University, 552 cardiotocographys (CTG) recorded using STAN S21 and S31 (Neoventa Medical, Molndal, Sweden) and Avalon FM40 and FM50 (Philips Healthcare, Amsterdam, The Netherlands) from the University Hospital in Brno, Czech Republic, and 66 FHR recordings acquired using Avalon FM50 fetal monitor (Philips Healthcare, Amsterdam, The Netherlands) at St Vincent de Paul Hospital (Lille, France). Each FHR baseline was estimated by clinicians and CTGNet, respectively. And agreement between CTGNet and clinicians was evaluated using the kappa statistics, intra-class correlation coefficient, and the limits of agreement.Results: The number of differences <3 beats per minute (bpm), 3-5 bpm, 5-10 bpm and >= 10 bpm, is 64.88%, 15.94%, 14.44% and 4.74%, respectively. Kappa statistics and intra-class correlation coefficient are 0.873 and 0.969, respectively. Limits of agreement are -6.81 and 7.48 (mean difference: 0.36 and standard deviation: 3.64).Conclusion: An excellent agreement was found between CTGNet and clinicians in the baseline estimation from FHR recordings with different signal loss rates.
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页数:8
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