Seizures are underrecognized in preterm infants, and little is known about their impact on brain growth. We aimed to define the association between early seizures and subsequent brain growth.
Infants ...<30 weeks gestation underwent 72 h of prospective amplitude-integrated electroencephalography (aEEG) monitoring, term-equivalent age (TEA) magnetic resonance imaging (MRI), and 2-year neurodevelopmental testing. Seizures were defined as trains of sharp waves >10 s, evolving in frequency/amplitude/morphology, and identified using automated algorithms with manual review. Using T2-weighted images, cortical surface area (CSA) and gyrification index (GI) were calculated and volumes were segmented into five tissue classes: cerebrospinal fluid, gray matter, white matter (WM), deep nuclear gray matter, and cerebellum. Correlations between total seizure burden and tissue-specific volumes were evaluated, controlling for clinical variables of interest.
Ninety-nine infants underwent aEEG/MRI assessments (mean GA = 26.3 weeks, birthweight = 899 g). Seizure incidence was 55% with a median of two events; median length = 66 s and mean burden = 285 s. Greater seizure burden was associated with smaller CSA and volumes across all tissue types, most prominently in WM (R
= -0.603, p < 0.01), even after controlling for confounders. There was no association with GI.
Seizures in preterm infants are common and associated with smaller TEA brain volumes. This relationship was strongest for WM and independent of clinical factors.
Seizures in preterm infants are common. Little is known about the association between early seizures and later brain growth. Greater seizure burden is linked with smaller volumes of all brain tissue types, most prominently the WM. This relationship is true even controlling for other factors. Additional study is needed to identify the optimal EEG monitoring and seizure treatment strategy for improved brain growth and neurodevelopmental outcomes.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Mortality is an unfortunately common outcome of extremely and very preterm birth. Existing clinical prediction models capture mortality risk at birth but fail to account for the remainder of the ...hospital course. Infants born < 32 weeks gestation with complete physiologic and clinical data were included in this retrospective study. Mortality risk was quantified by conventional means (clinical factors) using the CRIB-II score and the optimal logistic regression model. A random forest (RF) model was trained using a subset of the cohort, labeling data within 6 h of death as "worry." The model was then tested using the remaining infants. A total of 275 infants were included in the study with a mean gestational age of 27 weeks, mean birth weight of 929 g, 49% female, and a mortality rate of 21%. The CRIB-II and logistic regression models had acceptable performance with sensitivities of 71% and 80% AUC scores of 0.78 and 0.84, respectively. The RF model had superior performance with a sensitivity of 88% and an AUC of 0.93. A random forest model which incorporates fixed clinical factors with the influence of aberrancies in subsequent physiology has superior performance for mortality prediction compared to conventional models.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Brain injury is one of the most consequential problems facing neonates, with many preterm and term infants at risk for cerebral hypoxia and ischemia. To develop effective neuroprotective strategies, ...the mechanistic basis for brain injury must be understood. The fragile state of neonates presents unique research challenges; invasive measures of cerebral blood flow and oxygenation assessment exceed tolerable risk profiles. Near-infrared spectroscopy (NIRS) can safely and non-invasively estimate cerebral oxygenation, a correlate of cerebral perfusion, offering insight into brain injury-related mechanisms. Unfortunately, lack of standardization in device application, recording methods, and error/artifact correction have left the field fractured. In this article, we provide a framework for neonatal NIRS research. Our goal is to provide a rational basis for NIRS data capture and processing that may result in better comparability between studies. It is also intended to serve as a primer for new NIRS researchers and assist with investigation initiation.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
In this review, we explore race-based disparities in neonatology and their impact on brain injury and neurodevelopmental outcomes. We discuss the historical context of healthcare discrimination, ...focusing on the post-Civil War era and the segregation of healthcare facilities. We highlight the increasing disparity in infant mortality rates between Black and White infants, with premature birth being a major contributing factor, and emphasize the role of prenatal factors such as metabolic syndrome and toxic stress in affecting neonatal health. Furthermore, we examine the geographic and historical aspects of racial disparities, including the consequences of redlining and limited access to healthcare facilities or nutritious food options in Black communities. Finally, we delve into the higher incidence of brain injuries in Black neonates, as well as disparities in adverse neurodevelopmental outcome. This evidence underscores the need for comprehensive efforts to address systemic racism and provide equitable access to healthcare resources.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Child health is defined by a complex, dynamic network of genetic, cultural, nutritional, infectious, and environmental determinants at distinct, developmentally determined epochs from preconception ...to adolescence. This network shapes the future of children, susceptibilities to adult diseases, and individual child health outcomes. Evolution selects characteristics during fetal life, infancy, childhood, and adolescence that adapt to predictable and unpredictable exposures/stresses by creating alternative developmental phenotype trajectories. While child health has improved in the United States and globally over the past 30 years, continued improvement requires access to data that fully represent the complexity of these interactions and to new analytic methods. Big Data and innovative data science methods provide tools to integrate multiple data dimensions for description of best clinical, predictive, and preventive practices, for reducing racial disparities in child health outcomes, for inclusion of patient and family input in medical assessments, and for defining individual disease risk, mechanisms, and therapies. However, leveraging these resources will require new strategies that intentionally address institutional, ethical, regulatory, cultural, technical, and systemic barriers as well as developing partnerships with children and families from diverse backgrounds that acknowledge historical sources of mistrust. We highlight existing pediatric Big Data initiatives and identify areas of future research. IMPACT: Big Data and data science can improve child health. This review highlights the importance for child health of child-specific and life course-based Big Data and data science strategies. This review provides recommendations for future pediatric-specific Big Data and data science research.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Dexmedetomidine is being increasingly used as a primary or adjunctive sedative agent in neonates. There are a paucity of high-quality, high-resolution physiologic data during administration, despite ...significant potential cardiorespiratory effects. Term and preterm infants admitted between January 2018 and July 2020 were screened for dexmedetomidine exposure. Prospectively recorded vital signs (heart rate, oxygenation, arterial blood pressure) were cross-matched with pharmacy records to identify infants with data available 24 h before and 48 h after drug initiation. Vital sign data were processed via a standardized pipeline to (a) remove missing data, (b) obtain baseline averages of vital signs for 24 h preceding dexmedetomidine, and (c) calculate the hourly mean deviation from the baseline for the 48 h following initiation of dexmedetomidine. Infants were clustered by postmenstrual age (preterm ≤ 35 weeks; term > 35 weeks). 72 infants were identified with mean gestational age of 32 weeks and mean ± SD birth weight of 1976 ± 1341 g. Although both groups of infants experienced bradycardia, heart rate in term infants dropped faster and reached a nadir 5 beats per minute lower, before converging at a common deviation of − 10 beats per minute. No hypo- or hypertension was noted in either group. Unexpected instability of oxygenation occurred in a subset of preterm infants, requiring escalation of respiratory support. Administration of dexmedetomidine results in differential timing and magnitude of bradycardia in term and preterm infants, no major impact on blood pressure, and a surprising instability of oxygenation in preterm infants, requiring increased ventilatory support. Further investigation is warranted.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
To use cerebral near-infrared spectroscopy (NIRS) to quantify occult cerebral hypoxia across respiratory support modes in preterm infants.
In this prospective, longitudinal, observational study, ...infants ≤32 weeks gestation underwent serial pulse oximetry (oxygen saturation SpO
) and cerebral NIRS monitoring (4-6 hours per session) following a standardized recording schedule (daily for 2 weeks, every other day for 2 weeks, then weekly until 35 weeks corrected gestational age). Four calculations were made: median cerebral saturation, median cerebral hypoxia burden (proportion of NIRS samples below the hypoxia threshold <67%), median systemic saturation, and median systemic hypoxia burden (proportion of SpO
samples below the desaturation threshold <85%). During each recording session, respiratory support mode was noted (room air, low-flow nasal cannula, high-flow nasal cannula, noninvasive positive pressure ventilation, continuous positive airway pressure, and invasive ventilation).
There were 1013 recording sessions made from 174 infants with a median length of 6.9 hours. Although the systemic (SpO
) hypoxia burden was significantly greater for infants on the highest respiratory support (invasive and noninvasive positive pressure ventilation), the cerebral hypoxia burden was significantly greater during recording sessions made on the lowest respiratory support (8% for room air; 29% for low-flow nasal cannula).
Premature infants on the highest levels of respiratory support have less cerebral hypoxia than those on lower respiratory support. These results raise concern about unrecognized cerebral hypoxia during lower acuity periods of neonatal intensive care unit hospitalization and adverse outcomes.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
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