Risk assessment and early prediction of intraventricular hemorrhage in extremely preterm infants
Abstract This study aimed to identify the risk factors associated with intraventricular hemorrhage (IVH) in extremely preterm infants (EPIs), focusing on early-stage prediction to improve clinical outcomes. A retrospective cohort study was conducted at Guangzhou Women and Children’s Medical Center,...
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Nature Portfolio
2025-05-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-025-02061-4 |
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| author | Yueju Cai Xiaolan Li Xiaopeng Zhao Yanyan Song Wei Zhou |
| author_facet | Yueju Cai Xiaolan Li Xiaopeng Zhao Yanyan Song Wei Zhou |
| author_sort | Yueju Cai |
| collection | DOAJ |
| description | Abstract This study aimed to identify the risk factors associated with intraventricular hemorrhage (IVH) in extremely preterm infants (EPIs), focusing on early-stage prediction to improve clinical outcomes. A retrospective cohort study was conducted at Guangzhou Women and Children’s Medical Center, including 189 EPIs born between January 2019 and December 2023. Infants were categorized into IVH and non-IVH groups based on head ultrasound findings. Risk factors were assessed using univariate and multivariate analyses, and a predictive model for IVH was developed. Of the 189 EPIs, 80 (42.3%) developed IVH, with 26 (13.8%) experiencing severe IVH. Gestational age was identified as a significant protective factor (OR = 0.565, p = 0.023), while invasive mechanical ventilation (IMV) was a key risk factor (OR = 2.718, p = 0.012). The predictive model demonstrated good performance, with an AUC of 0.753 (95% CI: 0.681–0.825). Gestational age and IMV are critical factors in the development of IVH in EPIs. Early identification of high-risk infants based on these factors can aid in timely interventions to reduce IVH incidence and improve outcomes. |
| format | Article |
| id | doaj-art-cca7c9917eab4efd8d79e7cc318c8c18 |
| institution | DOAJ |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | Nature Portfolio |
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| series | Scientific Reports |
| spelling | doaj-art-cca7c9917eab4efd8d79e7cc318c8c182025-08-20T03:08:40ZengNature PortfolioScientific Reports2045-23222025-05-0115111010.1038/s41598-025-02061-4Risk assessment and early prediction of intraventricular hemorrhage in extremely preterm infantsYueju Cai0Xiaolan Li1Xiaopeng Zhao2Yanyan Song3Wei Zhou4Department of Neonatology, Guangzhou Women and Children’s Medical Center, Guangzhou Medical UniversityDepartment of Child Health, Guangzhou Women and Children’s Medical Center, Guangzhou Medical UniversityDepartment of Neonatology, Guangzhou Women and Children’s Medical Center, Guangzhou Medical UniversityDepartment of Child Health, Guangzhou Women and Children’s Medical Center, Guangzhou Medical UniversityDepartment of Neonatology, Guangzhou Women and Children’s Medical Center, Guangzhou Medical UniversityAbstract This study aimed to identify the risk factors associated with intraventricular hemorrhage (IVH) in extremely preterm infants (EPIs), focusing on early-stage prediction to improve clinical outcomes. A retrospective cohort study was conducted at Guangzhou Women and Children’s Medical Center, including 189 EPIs born between January 2019 and December 2023. Infants were categorized into IVH and non-IVH groups based on head ultrasound findings. Risk factors were assessed using univariate and multivariate analyses, and a predictive model for IVH was developed. Of the 189 EPIs, 80 (42.3%) developed IVH, with 26 (13.8%) experiencing severe IVH. Gestational age was identified as a significant protective factor (OR = 0.565, p = 0.023), while invasive mechanical ventilation (IMV) was a key risk factor (OR = 2.718, p = 0.012). The predictive model demonstrated good performance, with an AUC of 0.753 (95% CI: 0.681–0.825). Gestational age and IMV are critical factors in the development of IVH in EPIs. Early identification of high-risk infants based on these factors can aid in timely interventions to reduce IVH incidence and improve outcomes.https://doi.org/10.1038/s41598-025-02061-4Extreme preterm infantsIntraventricular hemorrhageRisk factorsPredictive modelNeonatal care |
| spellingShingle | Yueju Cai Xiaolan Li Xiaopeng Zhao Yanyan Song Wei Zhou Risk assessment and early prediction of intraventricular hemorrhage in extremely preterm infants Scientific Reports Extreme preterm infants Intraventricular hemorrhage Risk factors Predictive model Neonatal care |
| title | Risk assessment and early prediction of intraventricular hemorrhage in extremely preterm infants |
| title_full | Risk assessment and early prediction of intraventricular hemorrhage in extremely preterm infants |
| title_fullStr | Risk assessment and early prediction of intraventricular hemorrhage in extremely preterm infants |
| title_full_unstemmed | Risk assessment and early prediction of intraventricular hemorrhage in extremely preterm infants |
| title_short | Risk assessment and early prediction of intraventricular hemorrhage in extremely preterm infants |
| title_sort | risk assessment and early prediction of intraventricular hemorrhage in extremely preterm infants |
| topic | Extreme preterm infants Intraventricular hemorrhage Risk factors Predictive model Neonatal care |
| url | https://doi.org/10.1038/s41598-025-02061-4 |
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