The objective of this study is to describe the properties of dosing weight in the neonatal intensive care unit (NICU). Infants were identified from a database of very low birth weight infants. Before regaining birth weight (BW), dosing and birth weight% difference was described. After regaining BW, dosing and measured weight% difference and frequency of dosing weight updates were described. Associations with infant characteristics including comorbid conditions, serum biochemistries, fluid intake, and urine output were evaluated. There were 115 infants over 4,643 infant-days with a median BW of 1060 g (interquartile range [IQR]: 750, 1300) and median time to regain BW of 10 days (IQR: 8, 13). After regaining BW, dosing weight was 4.2% less than measured weight. The gap widened with increasing creatinine and narrowed with increasing urine output. The only factor associated with the frequency of dosing weight updates was day of the week. Dosing weights in the NICU appear to fall into one of three categories: BW prior to regaining BW, practical weight to facilitate medication and nutrition ordering, and "dry" weight, adjusting for fluid overloaded states. We recommend using measured weight to avoid a 4% daily loss in nutrition intake once BW is regained.
Objective To estimate associations of exclusive human milk (EHM) feedings with growth and neurodevelopment through 18 months corrected age (CA) in extremely low birth weight (ELBW) infants. Study Design ELBW infants admitted from July 2011 to June 2013 who survived were reviewed. Infants managed from July 2011 to June 2012 were fed with bovine milk-based fortifiers and formula (BOV). Beginning in July 2012, initial feedings used a human milk-based fortifier to provide EHM feedings. Infants were grouped on the basis of feeding regimen. Primary outcomes were the Bayley-III cognitive scores at 6, 12, and 18 months and growth. Results Infants (n = 85; 46% received EHM) were born at 26 ± 1.9 weeks (p = 0.92 between groups) weighing 776 ± 139 g (p = 0.67 between groups). Cognitive domain scores were similar at 6 months (BOV: 96 ± 7; EHM: 95 ± 14; p = 0.70), 12 months (BOV: 97 ± 10; EHM: 98 ± 9; p = 0.86), and 18 months (BOV: 97 ± 16; EHM: 98 ± 14; p = 0.71) CA. Growth velocity prior to discharge (BOV: 12.1 ± 5.2 g/kg/day; EHM: 13.1 ± 4.0 g/kg/day; p = 0.33) and subsequent growth was similar between groups. Conclusion EHM feedings appear to support similar growth and neurodevelopment in ELBW infants as compared with feedings containing primarily bovine milk-based products.
Extremely preterm infants are among the populations receiving the highest levels of transfusions. Erythropoietin has not been recommended for premature infants because most studies have not demonstrated a decrease in donor exposure.
Objectives
To determine whether high-dose erythropoietin given within 24 hours of birth through postmenstrual age of 32 completed weeks will decrease the need for blood transfusions.
Design, Setting, and Participants
The Preterm Erythropoietin Neuroprotection Trial (PENUT) is a randomized, double-masked clinical trial with participants enrolled at 19 sites consisting of 30 neonatal intensive care units across the United States. Participants were born at a gestational age of 24 weeks (0-6 days) to 27 weeks (6-7 days). Exclusion criteria included conditions known to affect neurodevelopmental outcomes. Of 3266 patients screened, 2325 were excluded, and 941 were enrolled and randomized to erythropoietin (n = 477) or placebo (n = 464). Data were collected from December 12, 2013, to February 25, 2019, and analyzed from March 1 to June 15, 2019.
Interventions
In this post hoc analysis, erythropoietin, 1000 U/kg, or placebo was given every 48 hours for 6 doses, followed by 400 U/kg or sham injections 3 times a week through postmenstrual age of 32 weeks.
Main Outcomes and Measures
Need for transfusion, transfusion numbers and volume, number of donor exposures, and lowest daily hematocrit level are presented herein.
Results
A total of 936 patients (488 male [52.1%]) were included in the analysis, with a mean (SD) gestational age of 25.6 (1.2) weeks and mean (SD) birth weight of 799 (189) g. Erythropoietin treatment (vs placebo) decreased the number of transfusions (unadjusted mean [SD], 3.5 [4.0] vs 5.2 [4.4]), with a relative rate (RR) of 0.66 (95% CI, 0.59-0.75); the cumulative transfused volume (mean [SD], 47.6 [60.4] vs 76.3 [68.2] mL), with a mean difference of −25.7 (95% CI, 18.1-33.3) mL; and donor exposure (mean [SD], 1.6 [1.7] vs 2.4 [2.0]), with an RR of 0.67 (95% CI, 0.58-0.77). Despite fewer transfusions, erythropoietin-treated infants tended to have higher hematocrit levels than placebo-treated infants, most noticeable at gestational week 33 in infants with a gestational age of 27 weeks (mean [SD] hematocrit level in erythropoietin-treated vs placebo-treated cohorts, 36.9% [5.5%] vs 30.4% [4.6%] (P < .001). Of 936 infants, 160 (17.1%) remained transfusion free at the end of 12 postnatal weeks, including 43 in the placebo group and 117 in the erythropoietin group (P < .001).
Conclusions and Relevance
These findings suggest that high-dose erythropoietin as used in the PENUT protocol was effective in reducing transfusion needs in this population of extremely preterm infants.
To evaluate adherence to a delayed cord clamping protocol for preterm births in the first 2 years after its introduction, perform a quality improvement assessment, and determine neonatal outcomes associated with protocol implementation and adherence.
BACKGROUND AND OBJECTIVE: Preterm neonates with intraventricular hemorrhage (IVH) are at risk for posthemorrhagic ventricular dilatation (PHVD).In recent years targeted proteomics has developed into a powerful protein quantifi cation tool in biomedical research, systems biology, and clinical applications.This study aims to inform therapeutic decision-making and parental counseling using proteomics in this high-risk group. METHODS:In this prospective study, we investigated preterm neonates born <34 weeks of gestation between 2011 to 2023 with intraventricular hemorrhage (IVH).We performed targeted proteomics analysis on different biological matrices (blood, urine, and CSF), derived from a longitudinal neonatal cohort spanning a decade.We employed explainable machine learning (ML) algorithms
