AI Article Synopsis

  • This study investigates how human serum albumin (HSA) levels affect drug distribution in neonates, aiming to establish trends in HSA over time and create a predictive model for HSA concentrations.
  • A total of 848 neonates were analyzed, revealing that HSA concentrations increase with postnatal age and gestational age, and several factors like birth weight and bilirubin levels significantly influence these concentrations.
  • The resulting prediction model demonstrated a high performance with an accuracy of 76.3%, providing valuable HSA centiles and insights that could improve clinical care and pharmacotherapy for neonatal patients.

Article Abstract

Background: Human serum albumin (HSA) concentrations may alter HSA-bound drug distribution. This study aims to describe longitudinal real-world HSA trends, and to develop a prediction model for HSA concentrations using a large neonatal cohort.

Methods: Patients admitted to the neonatal intensive care unit of the University Hospitals Leuven (postnatal age (PNA) ≤28days) were retrospectively included. Using linear mixed models, covariate effects on HSA were explored. A multivariable prediction model was developed (backward model selection procedure, 1% significance level).

Results: In total, 848 neonates were included [median(interquartile range) gestational age (GA) 35(32-38)weeks, birth weight (BW) 2400(1640-3130)grams]. Median HSA concentration was 32.3(28.7-35.6)g/L. Longitudinal analyses demonstrated increasing HSA concentrations with PNA and GA for most GA groups. Univariable analyses revealed significant associations of HSA with PNA, GA, BW, current weight, total and direct bilirubin, total plasma proteins, respiratory support, mechanical ventilation, sepsis, ibuprofen use, and C-reactive protein (p-values < 0.05). A high-performance (R = 76.3%) multivariable HSA prediction model was developed, and PNA- and GA-dependent HSA centiles were provided.

Conclusion: Population-specific HSA centiles and an accurate neonatal HSA prediction model were developed, incorporating both maturational and non-maturational covariates. These results can enhance future clinical care and pharmacokinetic analyses to improve pharmacotherapy of HSA-bound drugs in neonates, respectively.

Impact: To improve future pharmacokinetic modeling initiatives, a high-performance human serum albumin (HSA) prediction model was developed for (pre)term neonates, using a large, single-center cohort of real-world data. This prediction model integrates both maturational and non-maturational covariates, resulting in accurate HSA predictions in neonates. Additionally, HSA centiles based on postnatal and gestational age were developed, which can be easily applied in clinical practice when interpreting HSA concentrations of neonates. In general, unbound drug fractions are higher in neonates compared to older populations. To improve pharmacotherapy of HSA-bound drugs in neonates, the obtained results can be integrated in future pharmacokinetic-pharmacodynamic analyses.

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Source
http://dx.doi.org/10.1038/s41390-024-03634-1DOI Listing

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