New tool tracks weight loss in breastfed newborns

December 11, 2014

Newly developed neonatal nomograms enable healthcare providers and parents to follow weight changes in exclusively breastfed babies during the first days of life and identify abnormal weight loss patterns, as described in a recent study.

 

Newly developed neonatal nomograms enable healthcare providers and parents to follow weight changes in exclusively breastfed babies during the first days of life and identify abnormal weight loss patterns, as described in a recent study.

The online Newborn Weight Tool, or Newt, is a neonatal growth chart on which parents and healthcare providers can input an infant’s birth weight and subsequent weights from 6 hours to 3 or 4 days after birth. They can then see where the weights fall on estimated percentile weight loss curves. The nomograms can provide reassurance that a newborn’s weight loss is in the normal range for breastfed infants or warn of a trend toward greater weight loss associated with morbidity.

Newt is based on hourly weight data for 161,471 infants born at 36 weeks’ or longer gestation between 2009 and 2013 at Northern California Kaiser Permanente hospitals. Of this sample, 108,907 newborns had their weights recorded while exclusively breastfeeding. Because weight loss differs substantially over time for babies born vaginally and by cesarean delivery, the researchers developed separate nomograms for the 2 delivery methods. 

The nomograms show weight trends as colored lines for the 50th (green), 75th (yellow), 90th (orange), and 95th (red) percentiles. The significance of weight loss depends on when it occurs and at what rate. For example, an infant at the 50th percentile loses around 7% of body weight during the first 60 hours or so after birth then starts to gain, whereas a baby at the 95th percentile loses 7% of body weight in the first 30 hours.

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The study also found that losses of 10% or more of birth weight are common and occur sooner after birth than previously recognized. The size and diversity of the sample population suggest that the nomogram data may have broad clinical applicability and strong generalizability, the researchers note.


 

 

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