The clinical usefulness of predictive models for preterm birth with potential benefits: A Korean preterm collaborate network (KOPEN) registry linked data based cohort study

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The clinical usefulness of predictive models for preterm birth with potential benefits: A Korean preterm collaborate network (KOPEN) registry linked data based cohort study

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Preterm birth is strongly associated with increasing mortality, incidence of disability, intensity of neonatal care required, and consequent costs. We examined the clinical utility of the potential preterm birth risk factors from admitted pregnant women with symptomatic preterm labor and developed prediction models to obtain information for prolonging pregnancies.

Int J Med Sci 2020, Vol 17 Ivyspring International Publisher International Journal of Medical Sciences 2020; 17(1): 1-12 doi: 10.7150/ijms.37626 Research Paper The Clinical Usefulness of Predictive Models for Preterm Birth with Potential Benefits: A KOrean Preterm collaboratE Network (KOPEN) Registry-Linked Data-Based Cohort Study Kyung Ju Lee1,2, Jinho Yoo3, Young-Han Kim4, Soo Hyun Kim5, Seung Chul Kim6, Yoon Ha Kim7, Dong Wook Kwak8,9, Kicheol Kil10, Mi Hye Park11, Hyesook Park12, Jae-Yoon Shim13, Ga Hyun Son14, Kyung A Lee15, Soo-young Oh16, Kyung Joon Oh17, Geum Joon Cho18, So-yeon Shim19, Su Jin Cho19, Hee Young Cho20, Hyun-Hwa Cha21, Sae Kyung Choi22, Jong Yun Hwang23, Han-Sung Hwang24, Eun Jin Kwon11, Young Ju Kim11, the KOrean Preterm collaboratE Network (KOPEN) Working Group^ 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Department of Obstetrics and Gynecology, Korea University Medical Center, Seoul, Korea Department of Public Health, Korea University Graduate School, Seoul, Korea YooJin BioSoft Co., Ltd, Goyang-si Gyeonggi-do, Korea Department of Obstetrics and Gynecology, Institute of Women’s Life Medical Science, Yonsei University College of Medicine, Seoul, Korea Department of Obstetrics & Gynecology, CHA Gangnam Medical Center, CHA University, Seoul, Korea Department of Obstetrics and Gynecology, Biomedical Research Institute, Pusan National University College of Medicine, Busan, Korea Department of Obstetrics and Gynecology, Chonnam National University Medical School, Gwangju, Korea Department of Obstetrics and Gynecology, Cheil General Hospital and Woman’s Healthcare Center, Dankook University College of Medicine, Seoul, Korea Department of Obstetrics and Gynecology, Ajou University School of Medicine, Suwon, Korea Department of Obstetrics and Gynecology, College of Medicine, Catholic University of Korea, Seoul, Korea Department of Obstetrics and Gynecology, College of Medicine, Ewha Womans University, Seoul, Korea Department of Preventive Medicine, College of Medicine, Ewha Womans University, Seoul, Korea Department of Obstetrics & Gynecology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea Department of Obstetrics and Gynecology, Kangnam Sacred Heart Hospital, Hallym University College of Medicine, Seoul, Korea Department of Obstetrics and Gynecology, Kyung Hee University School of Medicine, Seoul, Korea Department of Obstetrics and Gynecology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea Department of Obstetrics and Gynecology, Seoul National University Bundang Hospital, Seongnam, Korea Department of Obstetrics and Gynecology, Korea University Medical Center, Seoul, Korea Department of Pediatrics, College of Medicine, Ewha Womans University, Seoul, Korea Department of Obstetrics and Gynecology, CHA Bundang Medical Center, CHA University School of Medicine, Seongnam, Korea Department of Obstetrics & Gynecology, Kyungpook National University Hospital, Kyungpook National University, School of Medicine, Daegu, Korea Department of Obstetrics and Gynecology, College of Medicine, Catholic University of Korea, Seoul, Korea Department of Obstetrics and Gynecology, Kangwon National University School of Medicine, Kangwon-do, Korea Department of Obstetrics and Gynecology, Research Institute of Medical Science, Konkuk University School of Medicine, Seoul, Korea  Corresponding author: Young Ju Kim, MD, PhD Department of Obstetrics and Gynecology, College of Medicine, Ewha Womans University, 1071 Anyangcheon-ro, Yangcheon-gu Seoul, 07985, Republic of Korea Tel: 82-10-3738-7903 Fax: 82-2-2647-9860 Email: kkyj@ewha.ac.kr © The author(s) This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) See http://ivyspring.com/terms for full terms and conditions Received: 2019.06.15; Accepted: 2019.10.25; Published: 2020.01.01 Abstract Background: Preterm birth is strongly associated with increasing mortality, incidence of disability, intensity of neonatal care required, and consequent costs We examined the clinical utility of the potential preterm birth risk factors from admitted pregnant women with symptomatic preterm labor and developed prediction models to obtain information for prolonging pregnancies Methods: This retrospective study included pregnant women registered with the KOrean Preterm collaboratE Network (KOPEN) who had symptomatic preterm labor, between 16 and 34 gestational weeks, in a tertiary care center from March to November 2016 Demographics, obstetric and medical histories, and basic laboratory test results obtained at admission were evaluated The preterm birth probability was assessed using a nomogram and decision tree according to birth gestational age: early preterm, before 32 weeks; late preterm, between 32 and 37 weeks; and term, after 37 weeks http://www.medsci.org Int J Med Sci 2020, Vol 17 Results: Of 879 registered pregnant women, 727 who gave birth at a designated institute were analyzed The rates of early preterm, late preterm, and term births were 18.16%, 44.02%, and 37.83%, respectively With the developed nomogram, the concordance index for early and late preterm births was 0.824 (95% CI: 0.785-0.864) and 0.717 (95% CI: 0.675-0.759) respectively Preterm birth was significantly more likely among women with multiple pregnancy and had water leakage due to premature rupture of membrane The prediction rate for preterm birth based on decision tree analysis was 86.9% for early preterm and 73.9% for late preterm; the most important nodes are watery leakage for early preterm birth and multiple pregnancy for late preterm birth Conclusion: This study aims to develop an individual overall probability of preterm birth based on specific risk factors at critical gestational times of preterm birth using a range of clinical variables recorded at the initial hospital admission Therefore, these models may be useful for clinicians and patients in clinical decision-making and for hospitalization or lifestyle coaching in an outpatient setting Key words: Preterm birth, Prediction model, Risk factor Introduction The overall spontaneous and iatrogenic preterm birth rates showed clinically varied country-specific rates between 5% to 13% per year over the past few decades [1-3] In Korea, preterm birth rates have increased over 1.5 times between 2007 and 2017 [4] The World Health Organization (WHO) categorizes preterm births based on the gestational age as follows: extremely preterm (

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