人血清白蛋白:早产儿和足月新生儿的预测模型和参考值。

IF 3.1 3区 医学 Q1 PEDIATRICS
Zoë Vander Elst, Annouschka Laenen, Jana Deberdt, Lotte Delemarre, Pieter Vermeersch, Glynis Frans, Gunnar Naulaers, Matthias Gijsen, Erwin Dreesen, Isabel Spriet, Karel Allegaert, Anne Smits
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引用次数: 0

摘要

背景:人血清白蛋白(HSA)浓度可能会改变 HSA 结合药物的分布。本研究旨在描述真实世界中 HSA 的纵向变化趋势,并利用大型新生儿队列建立 HSA 浓度预测模型:方法:回顾性纳入鲁汶大学医院新生儿重症监护室收治的患者(产后年龄 (PNA) ≤28天)。使用线性混合模型探讨了协变量对 HSA 的影响。建立了一个多变量预测模型(后向模型选择程序,1%显著性水平):共纳入 848 名新生儿[胎龄(GA)中位数(四分位数间距)35(32-38)周,出生体重(BW)2400(1640-3130)克]。HSA 浓度中位数为 32.3(28.7-35.6)克/升。纵向分析表明,大多数 GA 组的 HSA 浓度随着 PNA 和 GA 的增加而增加。单变量分析显示,HSA与PNA、GA、体重、当前体重、总胆红素和直接胆红素、血浆总蛋白、呼吸支持、机械通气、败血症、布洛芬使用和C反应蛋白有显著关联(P值2 = 76.3%):结论:结合成熟度和非成熟度协变量,建立了特定人群的 HSA 百分位数和准确的新生儿 HSA 预测模型。这些结果可加强未来的临床护理和药代动力学分析,以改善新生儿 HSA 结合药物的药物治疗:为了改进未来的药代动力学建模计划,我们利用一个大型单中心队列的真实世界数据,为(足月前)新生儿开发了一个高性能人血清白蛋白(HSA)预测模型。该预测模型综合了成熟度和非成熟度协变量,从而准确预测了新生儿的 HSA。此外,还开发了基于产后和胎龄的 HSA 百分位数,便于在临床实践中解释新生儿的 HSA 浓度。一般来说,与年龄较大的人群相比,新生儿的非结合药物组分更高。为了改善新生儿 HSA 结合药物的药物治疗,可将获得的结果纳入未来的药代动力学-药效学分析中。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Human serum albumin: prediction model and reference values for preterm and term neonates.

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 (R2 = 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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来源期刊
Pediatric Research
Pediatric Research 医学-小儿科
CiteScore
6.80
自引率
5.60%
发文量
473
审稿时长
3-8 weeks
期刊介绍: Pediatric Research publishes original papers, invited reviews, and commentaries on the etiologies of children''s diseases and disorders of development, extending from molecular biology to epidemiology. Use of model organisms and in vitro techniques relevant to developmental biology and medicine are acceptable, as are translational human studies
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