Predicting Weight Using Postmenstrual Age

Objectives: To describe the pattern and variability of body weight with postmenstrual age (PMA) using nonlinear mixed effect modeling (NONMEM) to create a single mathematical function that can be used from prematurity to adulthood.

Background: Postmenstrual age has been shown to predict functional properties of humans such as glomerular filtration rate and drug clearance.  Widely used growth charts use post-natal age to predict weight in an idealized population and are not available as a mathematical function.

Method: We modeled 7164 body weight and postmenstrual age observations from a pooled database of 5031 premature neonates, infants, children and adults. All subjects were participants in pharmacokinetic or renal function studies. Post-menstrual age (PMA) ranged from 23 weeks to 82 years. A mixed effect model was used to describe fixed (PMA, sex) and random between subject variability.

Results: A model based on the sum of three sigmoid hyperbolic and one exponential function described the data. Females were typically 12% lighter in weight. Part of the between subject variability in weight decreased exponentially with a half life of 3.5 postmenstrual age years while the remainder stayed a constant fraction of the weight asymptote for each of the four functions.

Conclusions: The change of weight with post-menstrual age and sex can be described with a simple equation. This is suitable for simulation of typical weight-age distributions and may be useful for evaluation of appropriate weight for age in children requiring medical treatment.

Reference: Sumpter AL, Holford NHG. Predicting weight using postmenstrual age – neonates to adults. Pediatr Anaesth. 2011;Accepted.

Anita Sumpter

  • University of Auckland