OBJECTIVE: No uniform method for calculating growth velocity (GV) (grams per kilogram per day) among extremely low birth weight (ELBW) infants has been reported. Because the calculation of actual GV is so labor intensive, investigators have estimated GV with varying approaches, making comparisons across studies difficult. This study compares the accuracy of 3 mathematical methods used for estimating average GV, namely, 2-point models using the difference between weights at 2 time points divided by time and weight (either birth weight [BW] or average weight), linear regression models that are normalized for either BW or average weight, and an exponential model. The accuracy of all models was compared with actual GVs calculated from daily weight measures for a group of ELBW infants. METHODS: Actual GVs were calculated from daily weights for 83 ELBW infants admitted to the special care nursery and were compared with estimated GVs from each of the 5 models for the same infants. RESULTS: The exponential model, using weights from 2 time points, ie, GV = [1000 x ln(Wn/W1)]/(Dn-D1), was extremely accurate, with mean absolute errors of 0.02% to 0.10%. The 2-point and linear models were highly inaccurate when BW was used in the denominator, with mean absolute errors of 50.3% to 96.4%. The 2-point and linear models were fairly accurate when average weight was used in the denominator, with mean absolute errors of 0.1% to 8.97%. Additional analyses showed that the accuracy of the 2-point and linear model estimates was affected significantly by the combination of BW, length of stay, and chronic lung disease, whereas the exponential model was not affected by these combined factors. CONCLUSIONS: GV estimates calculated with 3 commonly used models varied widely, compared with actual GVs; however, the exponential model estimates were extremely accurate. The exponential model provides the accuracy and ease of use that are lacking in current methods applied to infant growth research.
OBJECTIVE: No uniform method for calculating growth velocity (GV) (grams per kilogram per day) among extremely low birth weight (ELBW) infants has been reported. Because the calculation of actual GV is so labor intensive, investigators have estimated GV with varying approaches, making comparisons across studies difficult. This study compares the accuracy of 3 mathematical methods used for estimating average GV, namely, 2-point models using the difference between weights at 2 time points divided by time and weight (either birth weight [BW] or average weight), linear regression models that are normalized for either BW or average weight, and an exponential model. The accuracy of all models was compared with actual GVs calculated from daily weight measures for a group of ELBW infants. METHODS: Actual GVs were calculated from daily weights for 83 ELBW infants admitted to the special care nursery and were compared with estimated GVs from each of the 5 models for the same infants. RESULTS: The exponential model, using weights from 2 time points, ie, GV = [1000 x ln(Wn/W1)]/(Dn-D1), was extremely accurate, with mean absolute errors of 0.02% to 0.10%. The 2-point and linear models were highly inaccurate when BW was used in the denominator, with mean absolute errors of 50.3% to 96.4%. The 2-point and linear models were fairly accurate when average weight was used in the denominator, with mean absolute errors of 0.1% to 8.97%. Additional analyses showed that the accuracy of the 2-point and linear model estimates was affected significantly by the combination of BW, length of stay, and chronic lung disease, whereas the exponential model was not affected by these combined factors. CONCLUSIONS: GV estimates calculated with 3 commonly used models varied widely, compared with actual GVs; however, the exponential model estimates were extremely accurate. The exponential model provides the accuracy and ease of use that are lacking in current methods applied to infant growth research.
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