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

Frontiers in Cardiovascular Medicine

Cardiovascular Medicine

Huijin Wang¹  Xiuyu Pan²  Zheng Zheng²  Mei Zhong³  Xiaohui Guo⁴  Yaosheng Lu⁵  Jieyun Bai⁶ 

[1] College of Information Science and Technology, Jinan University, Guangzhou, China;Department of Obstetrics and Gynecology, Guangzhou Women and Children's Medical Center, Preterm Birth Prevention and Treatment Research Unit, Guangzhou Medical University, Guangzhou, China;Department of Obstetrics, NanFang Hospital of Southen Medical University, Guangzhou, China;Department of Obstetrics, Shenzhen People's Hospital, Shenzhen, China;Guangdong Provincial Key Laboratory of Traditional Chinese Medicine Information Technology, Jinan University, Guangzhou, China;College of Information Science and Technology, Jinan University, Guangzhou, China;Guangdong Provincial Key Laboratory of Traditional Chinese Medicine Information Technology, Jinan University, Guangzhou, China;College of Information Science and Technology, Jinan University, Guangzhou, China;Auckland Bioengnieering Institute, The University of Auckland, Auckland, New Zeanland;

关键词: artificial intelligence;    deep learning;    fetal heart rate;    baseline;    computer analysis;   

DOI  :  10.3389/fcvm.2023.1059211

 received in 2022-10-08, accepted in 2023-07-21,  发布年份 2023

来源: Frontiers

【 摘 要 】

BackgroundThis study aims to compare the fetal heart rate (FHR) baseline predicted by the cardiotocograph network (CTGNet) with that estimated by clinicians.Material and methodsA 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, Mölndal, 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.ResultsThe 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).ConclusionAn excellent agreement was found between CTGNet and clinicians in the baseline estimation from FHR recordings with different signal loss rates.

【 授权许可】

Unknown   
© 2023 Bai, Pan, Lu, Zhong, Wang, Zheng and Guo.