Abstract
twin pregnancies were analyzed using different modelling strategies including linear and non-linear two-level mixed effects models throughout the 12–38 weeks range. 90% population prediction intervals as well as individual fits were obtained through MonteCarlo simulations. Results: 409 twin pregnancies were included (329 dichorionic, 80 monochorionic) with a median number of measurements of 5 (IQR = 3–6) and 7 (IQR = 4–11) in dichorionics and monochorionics respectively. Among the different models, a 4parameter non-linear logistic function was found as the best fit. As an external validation of the model, the 90% prediction intervals for the whole population derived from mixed models closely matched the 5–95p interval derived from published cross-sectional studies. The modelling strategy allows for a parsimonious estimation of individual growth trajectories and may easily be used for conditional growth assessment. Conclusions: In twins, because a close biometric follow-up is needed, longitudinal modelling may be an important tool for growth monitoring, though widely used cross-sectional ranges have provided a good reference for serial measurements.
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