Performance of machine learning-based models to screen obstructive sleep apnea in pregnancy-Reference-Cited by-同舟云学术

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Performance of machine learning-based models to screen obstructive sleep apnea in pregnancy

Published:2024-08-22 Issue:1 Volume:2 Page:
ISSN:2948-1716
Container-title:npj Women's Health
language:en
Short-container-title:npj Womens Health

Author:

Wang Jingyu,Xiao Wenhan,Hong Haoyang,Zhang Chi,Yu Min,Xu Liyue,Wei Jun,Yang Jingjing,Liu Yanan,Yi Huijie,Zhang Linyan,Bai Rui,Zhou Bing,Zhao Long,Zhang Xueli,Wang Xiaozhi,Dong Xiaosong,Liu Guoli,Hong Shenda

Funder

National Natural Science Foundation of China

Beijing Natural Science Foundation

Publisher

Springer Science and Business Media LLC

Link

https://www.nature.com/articles/s44294-024-00030-2.pdf

Reference58 articles.

1. Jordan, A. S., McSharry, D. G. & Malhotra, A. Adult obstructive sleep apnoea. Lancet 383, 736–747 (2014).

2. Phan, K. et al. Sleep-disordered breathing in high-risk pregnancies is associated with elevated arterial stiffness and increased risk for preeclampsia. Am. J. Obstet. Gynecol. 226, 833.e831–833.e820 (2022).

3. Romero, R. & Badr, M. S. A role for sleep disorders in pregnancy complications: challenges and opportunities. Am. J. Obstet. Gynecol. 210, 3–11 (2014).

4. Bourjeily, G. et al. Obstructive sleep apnea in pregnancy is associated with adverse maternal outcomes: a national set. Sleep Med. 38, 50–57 (2017).

5. Facco, F. L. et al. Association between sleep-disordered breathing and hypertensive disorders of pregnancy and gestational diabetes mellitus. Obstet. Gynecol. 129, 31–41 (2017).

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