Tamara van Donge

Dynamics of creatinine in ELBW neonates 127 7 Introduction The availability of reference ranges for any specific laboratory test or biomarker to support clinical decision making and tailor therapy to the individual patient will greatly support neonatal care. 1,2 Variability is a key feature in the neonatal population since maturational physiological changes are most prominent during early infancy. This variability is not only related to differences in current weight, gestational age (GA) or postnatal age (PNA), but also to related morbidities, co-medication or nutritional and fluid management. Throughout the neonatal period serum creatinine (Scr) concentrations in preterm neonates vary tremendously due to this large inter- and intra- individual variability. 3,4 Despite its limitations, Scr is a commonly measured and easily accessible biomarker to estimate glomerular filtration rate (GFR). The clearance of Scr defines the volume of blood plasma that is cleared of creatinine per unit of time and approximates the GFR. Many mathematical equations have been proposed to reflect creatinine clearance or estimated GFR in newborn infants, mostly by means of linear regression methods. 4-8 In classical linear regression, there is only one level of unexplained variability (difference between observation and predicted value). In contrast, applying modeling and simulation techniques rather than classical linear regression methods, allows describing and quantifying the maturation processes underlying neonatal physiology with multiple levels of variability. These population models are characterized by the typical individual (the mean) and the random effects, describing the variability of the data. 9 These random effects are divided into two levels: the difference between individuals (inter-individual variability, IIV) and the difference between the individual prediction and the observation (individual prediction error, comprising also analytical imprecision of the observation). Although the developed equations have supported clinicians in the assessment of estimated GFR, the physiology and normative range of Scr in extreme preterm infants is still not fully understood and the accurate assessment of kidney function remains challenging. Until now, we are not aware of any mathematical modeling effort applying modeling and simulation techniques to Scr data in neonates. Traditionally, the dogma has been to ignore elevated Scr in preterm infants during the first days after birth as they are considered uninformative about creatinine clearance, due to maternal Scr transfer. Additionally, passive reabsorption across immature leaky renal tubules contributes to transient accumulation of creatinine during the first days of life, which suggests that part of elevated Scr after birth may still reflect neonatal and not maternal kidney function. 10