Development and validation of a model to predict mortality risk among extremely preterm infants during the early postnatal period: a multicentre prospective cohort study
Background Recently, with the rapid development of the perinatal medical system and related life-saving techniques, both the short-term and long-term prognoses of extremely preterm infants (EPIs) have improved significantly. In rapidly industrialising countries like China, the survival rates of EPIs...
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BMJ Publishing Group
2023-12-01
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| author | Qiang Liu Jie Zhang Min Liu Xiaohui Zhang Lili Zhao Yuxin Li Xiaohui Liu Yong-hui Yu Wen-wen Zhang Shaofeng Wang Xiaoyu Dong Zhongliang Li Fengjuan Zhang Guo Yao Guohua Liu Simmy Reddy |
| author_facet | Qiang Liu Jie Zhang Min Liu Xiaohui Zhang Lili Zhao Yuxin Li Xiaohui Liu Yong-hui Yu Wen-wen Zhang Shaofeng Wang Xiaoyu Dong Zhongliang Li Fengjuan Zhang Guo Yao Guohua Liu Simmy Reddy |
| author_sort | Qiang Liu |
| collection | DOAJ |
| description | Background Recently, with the rapid development of the perinatal medical system and related life-saving techniques, both the short-term and long-term prognoses of extremely preterm infants (EPIs) have improved significantly. In rapidly industrialising countries like China, the survival rates of EPIs have notably increased due to the swift socioeconomic development. However, there is still a reasonably lower positive response towards the treatment of EPIs than we expected, and the current situation of withdrawing care is an urgent task for perinatal medical practitioners.Objective To develop and validate a model that is practicable for EPIs as soon as possible after birth by regression analysis, to assess the risk of mortality and chance of survival.Methods This multicentre prospective cohort study used datasets from the Sino-Northern Neonatal Network, including 46 neonatal intensive care units (NICUs). Risk factors including maternal and neonatal variables were collected within 1 hour post-childbirth. The training set consisted of data from 41 NICUs located within the Shandong Province of China, while the validation set included data from 5 NICUs outside Shandong Province. A total of 1363 neonates were included in the study.Results Gestational age, birth weight, pH and lactic acid in blood gas analysis within the first hour of birth, moderate-to-severe hypothermia on admission and adequate antenatal corticosteroids were influencing factors for EPIs’ mortality with important predictive ability. The area under the curve values for internal validation of our prediction model and Clinical Risk Index for Babies-II scores were 0.81 and 0.76, and for external validation, 0.80 and 0.51, respectively. Moreover, the Hosmer-Lemeshow test showed that our model has a constant degree of calibration.Conclusions There was good predictive accuracy for mortality of EPIs based on influencing factors prenatally and within 1 hour after delivery. Predicting the risk of mortality of EPIs as soon as possible after birth can effectively guide parents to be proactive in treating more EPIs with life-saving value.Trial registration number ChiCTR1900025234. |
| format | Article |
| id | doaj-art-ef1c2b05e43b4c19aea0f1ca165cd937 |
| institution | OA Journals |
| issn | 2044-6055 |
| language | English |
| publishDate | 2023-12-01 |
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| spelling | doaj-art-ef1c2b05e43b4c19aea0f1ca165cd9372025-08-20T01:48:37ZengBMJ Publishing GroupBMJ Open2044-60552023-12-01131210.1136/bmjopen-2023-074309Development and validation of a model to predict mortality risk among extremely preterm infants during the early postnatal period: a multicentre prospective cohort studyQiang Liu0Jie Zhang1Min Liu2Xiaohui Zhang3Lili Zhao4Yuxin Li5Xiaohui Liu6Yong-hui Yu7Wen-wen Zhang8Shaofeng Wang9Xiaoyu Dong10Zhongliang Li11Fengjuan Zhang12Guo Yao13Guohua Liu14Simmy Reddy15The Fourth People`s Hospital of Jinan, Jinan, ChinaDepartment of Ophthalmology, National key clinical specialty, Weifang Eye Hospital; Weifang Institute of Ophthalmology; Zhengda Guangming Ophthalmology Group, Weifang, People`s Republic of China1 Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, ChinaWashington University Medical School, St Louis, MO, USA15 Department of Neurology, Changzhi People`s Hospital, Changzhi, ChinaIQVIA Ltd, London, UKDepartment of Critical Care Medicine, Affiliated Hospital of Zunyi Medical University, Zunyi, Guizhou, ChinaShandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, ChinaJinan Maternity and Child Care Hospital Affiliated to Shandong First Medical University, Jinan, ChinaJinan Maternity and Child Care Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, ChinaDepartment of Cardiology, The First Affiliated Hospital with Nanjing Medical University, Nanjing, Jiangsu, ChinaWeifang Maternal and Child Health Hospital, Weifang, ChinaThe First Affiliated Hospital of Shandong First Medical University, Jinan, Shandong, ChinaDepartment of Neonatology, The Affiliated Taian City Central Hospital of Qingdao University, Taian, ChinaLinfen Maternal and Child Health Hospital, Linfen, ChinaCheeloo College of Medicine, Shandong University, Jinan, ChinaBackground Recently, with the rapid development of the perinatal medical system and related life-saving techniques, both the short-term and long-term prognoses of extremely preterm infants (EPIs) have improved significantly. In rapidly industrialising countries like China, the survival rates of EPIs have notably increased due to the swift socioeconomic development. However, there is still a reasonably lower positive response towards the treatment of EPIs than we expected, and the current situation of withdrawing care is an urgent task for perinatal medical practitioners.Objective To develop and validate a model that is practicable for EPIs as soon as possible after birth by regression analysis, to assess the risk of mortality and chance of survival.Methods This multicentre prospective cohort study used datasets from the Sino-Northern Neonatal Network, including 46 neonatal intensive care units (NICUs). Risk factors including maternal and neonatal variables were collected within 1 hour post-childbirth. The training set consisted of data from 41 NICUs located within the Shandong Province of China, while the validation set included data from 5 NICUs outside Shandong Province. A total of 1363 neonates were included in the study.Results Gestational age, birth weight, pH and lactic acid in blood gas analysis within the first hour of birth, moderate-to-severe hypothermia on admission and adequate antenatal corticosteroids were influencing factors for EPIs’ mortality with important predictive ability. The area under the curve values for internal validation of our prediction model and Clinical Risk Index for Babies-II scores were 0.81 and 0.76, and for external validation, 0.80 and 0.51, respectively. Moreover, the Hosmer-Lemeshow test showed that our model has a constant degree of calibration.Conclusions There was good predictive accuracy for mortality of EPIs based on influencing factors prenatally and within 1 hour after delivery. Predicting the risk of mortality of EPIs as soon as possible after birth can effectively guide parents to be proactive in treating more EPIs with life-saving value.Trial registration number ChiCTR1900025234.https://bmjopen.bmj.com/content/13/12/e074309.full |
| spellingShingle | Qiang Liu Jie Zhang Min Liu Xiaohui Zhang Lili Zhao Yuxin Li Xiaohui Liu Yong-hui Yu Wen-wen Zhang Shaofeng Wang Xiaoyu Dong Zhongliang Li Fengjuan Zhang Guo Yao Guohua Liu Simmy Reddy Development and validation of a model to predict mortality risk among extremely preterm infants during the early postnatal period: a multicentre prospective cohort study BMJ Open |
| title | Development and validation of a model to predict mortality risk among extremely preterm infants during the early postnatal period: a multicentre prospective cohort study |
| title_full | Development and validation of a model to predict mortality risk among extremely preterm infants during the early postnatal period: a multicentre prospective cohort study |
| title_fullStr | Development and validation of a model to predict mortality risk among extremely preterm infants during the early postnatal period: a multicentre prospective cohort study |
| title_full_unstemmed | Development and validation of a model to predict mortality risk among extremely preterm infants during the early postnatal period: a multicentre prospective cohort study |
| title_short | Development and validation of a model to predict mortality risk among extremely preterm infants during the early postnatal period: a multicentre prospective cohort study |
| title_sort | development and validation of a model to predict mortality risk among extremely preterm infants during the early postnatal period a multicentre prospective cohort study |
| url | https://bmjopen.bmj.com/content/13/12/e074309.full |
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