A concise method of calculating fetal weight percentile.
OBJECTIVE
Assessment of fetal growth used in clinical decision making for managing pregnancies is based on percentiles relative to normal values for gestational age. Most clinicians utilize visual interpolation of look-up tables or graphs, which is neither accurate nor convenient. Calculation of growth percentile by numerical integration formulas requires digital computers with advanced computational capabilities and/or the storage of large data tables.


METHODS
Using established ultrasound measurement formulas and published fetal weight/gestational age tables, mean weights and standard deviations for gestational ages from 10 to 44 weeks were determined. From this Z-scores were calculated for the gestational ages. Z-scores plotted against 1st through 50th percentiles resulted in a curve. A polynomial equation was derived to fit the curve resulting in an expression for converting the Z-score to percentile: Percentile = 0.0994 * Z score2 - 0.44 * Z score + 0.5026.


RESULTS
Comparing calculated values from this equation against standard percentiles from a Z-score to percentile table, all calculated values varied from the table value by < 1 percentile for Z-scores ranging from 0 to 2.33. Values > 2.33 are assigned to the 99th percentile. The equation performed to the goal of calculating percentile to an accuracy of < or = 1 percentile.


CONCLUSIONS
A method whereby the estimated fetal weight can be used to calculate a percentile using two simple equations and only standard math functions allows implementation on a standard personal digital assistant device commonly available for clinical use. This implementation gives the needed accuracy, ease of interpretation, and portability, making it a useful tool in clinical practice.
Lombano
Frank
F
Department of Obstetrics/Gynecology, San Joaquin General Hospital, French Camp, California 95231, USA. frank@lombano.com
Block
Barry S
BS
D020567:Fetal Weight; D005865:Gestational Age; D006801:Humans; D008432:Mathematical Computing; D008962:Models, Theoretical; D011237:Predictive Value of Tests; D012016:Reference Values; D012680:Sensitivity and Specificity; D016216:Ultrasonography, Prenatal