Dataset Information

Intraventricular hemorrhage prediction in premature neonates in the era of hemodynamics monitoring: a prospective cohort study.

ABSTRACT: Unstable hemodynamics and prematurity are the main players in intraventricular hemorrhage (IVH) development. Our objective was to study 8 the use of superior vena cava flow (SVCF), left ventricular output (LVO), and right ventricular output (RVO), and anterior cerebral artery (ACA) Doppler measures in prediction of IVH in the first week of life in preterm infant ≤ 32 weeks and birth weight ≤ 1500 g. This prospective cohort study was conducted in 55NICU of Alexandria University maternity hospital. Of 147 enrolled patients, 132 infants born ≤ 32 weeks GA and birth weight ≤ 1500 g were eligible for- the study. One hundred twenty-seven infants completed the study. Infants were scanned for ACA-RI using transfontanellar ultrasound, and SVCF, LVO, and RVO using functional echocardiography in the first 24 h after birth. Patients had another two scans on DOL3 and 7 to detect IVH development. Low SVCF and high ACA-RI significantly increased the risk of IVH using logistic regression models with OR, 3.16; 95%CI, 1.19-8.39; P = 0.02 and OR, 1.64; 95%Cl, 1.10-2.44; P = 0.02, respectively. Low SVCF and high ACA-RI significantly increased risk of catastrophic IVH P = 0.025 and 0.023, respectively. Combined use of low SVCF < 55 ml/kg/min and ACA-RI > 0.75 is predictor of IVH with sensitivity 40.8% and 82.1% specificity.

Conclusions

There are strong relations between both low SVCF and high ACA-RI, and IVH development in premature neonates ≤ 32 weeks and birth weight ≤ 1500 g, with more significance towards catastrophic IVH. Admission RSS and LVO are the strongest factors affecting SVCF. Maternal anemia, patent ductus arteriosus size (mm/kg), and capillary refill time were significantly associated with high ACA-RI. These findings help in more understanding of pathophysiological factors affecting central perfusion that might affect the longer term neurodeveopmental outcome.

Trial registration

This work was registered in clinical trial.gv no NCT05050032.

What is known

•Whether SVCF and RI-ACA can predict IVH in preterm neonates is still debatable.

What is new

•Low SVC flow and high ACA-RI significantly increased risk of IVH, confirming the role of hypoperfusion-reperfusion cycle in IVH development. The most striking result that combined metrics using the cut-off value of < 41 ml/kg/min for SVCF and > 0.85 for ACA-RI "in the first day of life" can correctly reject the presence of IVH in 98% of patients "during the first week of life."

SUBMITTER: Farag MM

PROVIDER: S-EPMC9649466 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature

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Publications

Intraventricular hemorrhage prediction in premature neonates in the era of hemodynamics monitoring: a prospective cohort study.

Farag Marwa Mohamed MM Gouda Mohamed Hazem MH Almohsen Ali Mohamed Abd AMA Khalifa Mohammed Attia MA

European journal of pediatrics 20220928 12

Unstable hemodynamics and prematurity are the main players in intraventricular hemorrhage (IVH) development. Our objective was to study 8 the use of superior vena cava flow (SVCF), left ventricular output (LVO), and right ventricular output (RVO), and anterior cerebral artery (ACA) Doppler measures in prediction of IVH in the first week of life in preterm infant ≤ 32 weeks and birth weight ≤ 1500 g. This prospective cohort study was conducted in 55NICU of Alexandria University maternity hospital ...[more]

PMID: 36171508

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Project description:Importance:Studies of cranial ultrasonography and early childhood outcomes among cohorts of extremely preterm neonates have linked periventricular-intraventricular hemorrhage and cystic periventricular leukomalacia with adverse neurodevelopmental outcomes. However, the association between nonhemorrhagic ventriculomegaly and neurodevelopmental and behavioral outcomes is not fully understood. Objective:To characterize the outcomes of extremely preterm neonates younger than 27 weeks' gestational age who experienced nonhemorrhagic ventriculomegaly that was detected prior to 36 weeks' postmenstrual age. Design, Setting, and Participants:This longitudinal observational study was conducted at 16 centers of the Eunice Kennedy Shriver National Institute of Child Health and Human Development Neonatal Research Network. Infants born prior to 27 weeks' gestational age in any network facility between July 1, 2006, and June 30, 2011, were included if they had a cranial ultrasonogram performed prior to 36 weeks' postmenstrual age. Comparisons were made between those with ventriculomegaly and those with normal cranial sonograms. Data analysis was completed from August 2013 to August 2017. Main Outcomes and Measures:The main outcome was neurodevelopmental impairment, defined as a Bayley Scales of Infant and Toddler Development III cognitive score less than 70, moderate/severe cerebral palsy, a Gross Motor Function Classification System score of level 2 or more, vision impairment, or hearing impairment. Secondary outcomes included Bayley Scales of Infant and Toddler Development III subscores, components of neurodevelopmental impairment, behavioral outcomes, and death/neurodevelopmental impairment. Logistic regression was used to evaluate the association of ventriculomegaly with adverse outcomes while controlling for potentially confounding variables and center differences as a random effect. Linear regression was used similarly for continuous outcomes. Results:Of 4193 neonates with ultrasonography data, 300 had nonhemorrhagic ventriculomegaly (7%); 3045 had normal cranial ultrasonograms (73%), 775 had periventricular-intraventricular hemorrhage (18.5%), and 73 had cystic periventricular leukomalacia (1.7%). Outcomes were available for 3008 of 3345 neonates with ventriculomegaly or normal scans (90%). Compared with normal cranial ultrasonograms, ventriculomegaly was associated with lower gestational age, male sex, and bronchopulmonary dysplasia, late-onset sepsis, meningitis, necrotizing enterocolitis, and stage 3 retinopathy of prematurity. After adjustment, neonates with ventriculomegaly had higher odds of neurodevelopmental impairment (odds ratio [OR], 3.07; 95% CI, 2.13-4.43), cognitive impairment (OR, 3.23; 95% CI, 2.09-4.99), moderate/severe cerebral palsy (OR, 3.68; 95% CI, 2.08-6.51), death/neurodevelopmental impairment (OR, 2.17; 95% CI, 1.62-2.91), but not death alone (OR, 1.09; 95% CI, 0.76-1.57). Behavioral outcomes did not differ. Conclusions and Relevance:Nonhemorrhagic ventriculomegaly is associated with increased odds of neurodevelopmental impairment among extremely preterm neonates.

Project description:Intraventricular hemorrhage (IVH) in preterm neonates presents a high risk for developing posthemorrhagic ventricular dilatation (PHVD), a severe complication that can impact survival and long-term outcomes. Early detection of PHVD before clinical onset is crucial for optimizing therapeutic interventions and providing accurate parental counseling. This study explores the potential of explainable machine learning models based on targeted liquid biopsy proteomics data to predict outcomes in preterm neonates with IVH. In recent years, research has focused on leveraging advanced proteomic technologies and machine learning to improve prediction of neonatal complications, particularly in relation to neurological outcomes. Machine learning (ML) approaches, combined with proteomics, offer a powerful tool to identify biomarkers and predict patient-specific risks. However, challenges remain in integrating large-scale, multiomic datasets and translating these findings into actionable clinical tools. Identifying reliable, disease-specific biomarkers and developing explainable ML models that clinicians can trust and understand are key barriers to widespread clinical adoption. In this prospective longitudinal cohort study, we analyzed 1109 liquid biopsy samples from 99 preterm neonates with IVH, collected at up to six timepoints over 13 years. Various explainable ML techniques-including statistical, regularization, deep learning, decision trees, and Bayesian methods-were employed to predict PHVD development and survival and to discover disease-specific protein biomarkers. Targeted proteomic analyses were conducted using serum and urine samples through a proximity extension assay capable of detecting low-concentration proteins in complex biofluids. The study identified 41 significant independent protein markers in the 1600 calculated ML models that surpassed our rigorous threshold (AUC-ROC of ≥0.7, sensitivity ≥ 0.6, and selectivity ≥ 0.6), alongside gestational age at birth, as predictive of PHVD development and survival. Both known biomarkers, such as neurofilament light chain (NEFL), and novel biomarkers were revealed. These findings underscore the potential of targeted proteomics combined with ML to enhance clinical decision-making and parental counseling, though further validation is required before clinical implementation.

Dataset Information

Intraventricular hemorrhage prediction in premature neonates in the era of hemodynamics monitoring: a prospective cohort study.

Conclusions

Trial registration

What is known

What is new

Publications

Intraventricular hemorrhage prediction in premature neonates in the era of hemodynamics monitoring: a prospective cohort study.

Similar Datasets

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