A statistical process control (SPC)-based methodology is developed to detect early deviations of fetal biometry from expected normal growth. Using response modeling methodology (RMM), a fetal growth model is dynamically estimated and integrated in a regression-adjusted SPC control scheme, based on a new median control chart and a control chart for residuals variation. Hadlock's reference centiles are also integrated in the monitoring scheme. Longitudinal data from normal pregnancies and those with adverse medical outcomes have been analyzed. Results show that nonsmooth growth trajectory, expressed in exceptionally large absolute deviations from predicted median values, is a good precursor to possible prenatal adverse outcomes.
- customized fetal growth modeling and monitoring
- least absolute deviation
- nonlinear profiles
- response modeling methodology
- short runs
- statistical process control