title: Length of pregnancy in African Americans: validation of a new predictive rule.
abstract: This study evaluated whether a new predictive rule is more accurate for estimating the length of pregnancy in African Americans than Nägele's rule, the accepted standard. After identifying women in early pregnancy, telephone interviews were conducted to obtain information about 16 previously established determinants of gestational length. Based on these data, a linear multivariate regression model was used to predict an estimated delivery date (EDD) for each mother. In addition, the EDD was determined using Nägele's rule. Later, the actual delivery date was compared with the EDD predicted by the new rule and with the EDD predicted by Nägele's rule. Each pregnancy was assigned to its better prediction group, either the new rule's group or the Nägele's rule group. Fifty-seven pregnancies were identified prospectively and monitored. The new rule predicted the actual delivery date more accurately in 66% (37/56) of pregnancies, Nägele's rule was a better predictor in 34% (19/56) of pregnancies, and both rules were equally accurate in predicting the delivery date for one pregnancy. The new rule was more precise than Nägele's rule (P = .022) when the binomial distribution was used. When using the linear regression model rule, a more accurate EDD can be determined for African-American women. Moreover, it is possible to predict the risk of preterm delivery (those occurring > 3 weeks earlier than the EDD).
authors.affiliation: Department of Obstetrics and Gynecology, Pritzker School of Medicine, University of Chicago, IL, USA.
authors.forename: R
authors.initials: R
authors.lastname: Mittendorf
authors.forename: L M
authors.initials: LM
authors.lastname: Chorzempa
authors.forename: M P
authors.initials: MP
authors.lastname: Quinlan
authors.forename: M
authors.initials: M
authors.lastname: Herschel
authors.forename: M A
authors.initials: MA
authors.lastname: Williams
mesh_terms: D000328:Adult; D001741:Black or African American; D000465:Algorithms; D036861:Delivery, Obstetric; D005260:Female; D005500:Follow-Up Studies; D005544:Forecasting; D005865:Gestational Age; D006801:Humans; D016018:Least-Squares Analysis; D016014:Linear Models; D015999:Multivariate Analysis; D007752:Obstetric Labor, Premature; D011247:Pregnancy; D011446:Prospective Studies; D015203:Reproducibility of Results; D012307:Risk Factors; D013997:Time Factors