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Introduction: Three widely referenced growth curves classify infant birth anthropometric measurements as small (SGA), appropriate (AGA), or large (LGA) for gestational age (GA) differently. We assessed how these differences in assignment affect the identification and prediction of neonatal intensive care unit (NICU) mortality risk in US preterm infants., Methods: Birth data of infants admitted to NICUs from the Pediatrix Clinical Data Warehouse (2013-2018) were analyzed. Birth weight, length, and head circumference of 46,724 singleton infants (24-32 weeks GA) were classified as SGA, AGA, or LGA using the Olsen, Fenton, and INTERGROWTH-21st curves. NICU mortality risk based on birth size classification was analyzed using unadjusted and adjusted logistic regression stratified by GA., Results: Odds of mortality were increased with SGA classification at all GAs, size measurements, and curve sets, compared with AGA infants. LGA classification for weight was associated with lower mortality risk at 24 weeks GA and higher risk at 30 weeks GA. Odds of mortality did not differ significantly across curve sets. Classification of size at birth alone had relatively low predictive ability to identify mortality risk, with unadjusted AUCs near 0.5 for all analyses., Conclusion: There were no significant differences across curve sets in predicting mortality. Classification of size at birth is a relatively imprecise method to identify infants at risk for NICU mortality., (© 2024 S. Karger AG, Basel.)

Background: Longitudinal growth curves, based on repeated measurements from the same group of infants, exist for preterm infant weight and length but not for BMI. Our existing BMI (weight divided by length squared) curves are based on cross-sectional birth data obtained from a different group of infants at each gestational age (GA)., Methods: We calculated BMI over time for 68 693 preterm infants between 24 and 36 weeks GA. Stratifying infants by sex, GA at birth, and quintiles based on birth BMI, we created longitudinal median curves using R and validated the resulting curves for empirical fit, proper classification, and normality of z scores., Results: We created 2 sets of BMI growth charts. The first set displays fitted median curves for all 5 percentile groups in each GA group by sex. The second set displays fitted median curves with their corresponding third and 97th percentiles by percentile group, GA, and sex. In the validation analysis, percentage of daily observations below the median curve approximated the expected 50th percentile after the initial 3 days. Unlike the cross-sectional curves, the longitudinal curves reveal the pattern of change corresponding to nadir; postnadir, these curves remained consistently below the cross-sectional curves and varied by GA and sex as expected. The percentage of observations falling below the 50th percentile for cross-sectional curves (revealing optimal growth) was generally much higher than for longitudinal curves (revealing actual growth)., Conclusions: These new longitudinal curves provide clinicians data on how premature infants' body proportionality changes over time., Competing Interests: POTENTIAL CONFLICT OF INTEREST: The authors have indicated they have no potential conflicts of interest to disclose., (Copyright © 2018 by the American Academy of Pediatrics.)

Objective: Describe the level of registered dietitian (RD) involvement in neonatal intensive care units (NICUs) and associations with NICU nutrition practices., Design: Questionnaires were mailed to 820 NICUs in the United States with two follow-up mailings to nonresponders. Abbreviated phone surveys were conducted with a random sample of 10% of nonresponders. A nutrition care score was devised based on a sum of 10 survey questions (range 0 to 10) to summarize the intensity of reported practices., Subjects/setting: Directors of NICUs in the United States and RDs associated with them., Statistical Analyses: Chi2, analysis of variance, Bonferroni and Duncan multiple range tests, regression., Results: Respondents from 417 (54%) of the 772 NICUs eligible for the study provided completed questionnaires. Among NICUs responding, 76% involved RDs in care (41% employed full- or part-time RDs, 35% employed consult RDs), and 24% had no RD. NICUs with full- or part-time RDs provided fewer kilocalories and more protein parenterally, and more kilocalories and protein enterally. NICUs with less RD involvement were more likely to provide full-term infant feedings (eg, unfortified breast milk, full-term formula) to very-low-birth-weight infants. Mean nutrition care score varied with RD involvement from 4.6+/-1.7 (mean+/-standard deviation) for NICUs with a consult RD and 4.7+/-1.4 for NICUs employing no RD to 5.6+/-1.7 for NICUs with a full- or part-time RD (overall P<.001)., Conclusions: More involvement of RDs in NICUs increased the intensity of important aspects of nutrition care that may improve outcomes of very-low-birth-weight infants in NICUs. These findings highlight the importance of RDs as NICU team members.

Background and Objective: Transfer of infants between hospitals or their discharge home may bias comparisons of the performance across neonatal intensive care units (NICUs). This study attempts to show the potential size of transfer bias in the context of a large cohort study and describe strategies for minimizing this type of bias., Methods: To limit transfer bias in a neonatal growth study of extremely premature infants in six tertiary NICUs, we restricted eligibility to infants <30 weeks gestation at birth and substituted matched replacements for early transfers (infants transferred or discharged prior to day of life 16)., Results: The restriction strategy was successful, reducing the overall early transfer rate from 16.4 to 3.6% and the range of transfer rates among individual NICUs from 0.6-32.7% to 0-11.0%. Replacement by matched substitutes had a much smaller effect because of the small number of early transfers and our inability to match on all factors distinguishing early transfers., Conclusion: Sampling strategies to minimize infants lost to follow-up were more successful than replacement strategies in limiting transfer bias in a NICU growth study. Although complete elimination of bias is likely impossible, valid studies require efforts to minimize, quantify, and test the effect of transfer bias.

Objective: To explain differences in weight growth velocity of extremely premature infants among 6 level III neonatal intensive care units (NICUs)., Methods: In 6 NICUs, we studied 564 infants, stratified by gestational age (GA), who were first admissions, survivors, <30 weeks' GA at birth, and in the NICU at least 16 days. Case mix (eg, birth weight, GA, race, illness severity, prenatal steroids), exposure to medical practices/complications (eg, respiratory support, postnatal steroids, necrotizing enterocolitis, infection), and nutritional intake (kcal/kg/d and protein in g/kg/d) were collected and used to predict weight growth velocity between day 3 and day 28 (or discharge, if transferred early) in multiple linear regression models., Results: Weight growth velocities varied significantly among the 6 NICUs. Adjustment for case mix and medical factors explained little of this variability, but additional control for calorie and especially protein intake accounted for much of the intersite variability. For the average infant, adjusted growth velocity ranged from 10.4 to 14.3 g/kg/d among the sites studied. The final predictive model, including case mix and medical and nutritional factors, explained 53% of the overall variance in growth velocity. Prolonged (> or =15 days) exposure to postnatal steroids and greater severity of illness both decreased growth velocity. The model predicted that adding 1 g/kg/d protein to the mean intake for our sample would increase growth by 4.1 g/kg/d., Conclusions: Variation in nutrition explained much of the difference in growth among the NICUs studied. Mean intake of calories and protein failed to meet recommended levels, and the average growth in only 1 NICU approximated intrauterine growth standards. Increasing nutritional intake into the recommended ranges, in particular of protein, may increase growth of extremely premature infants up to or above intrauterine rates.