Open AccessDevelopment and validation of a nomogram to predict the risk of cesarean delivery in macrosomia
Author(s) -
MAZOUNI CHAFIKA,
ROUZIER ROMAN,
COLLETTE EMMANUELLE,
MENARD JEANPIERRE,
MAGNIN GEORGES,
GAMERRE MARC,
DETER RUSSELL
Publication year - 2008
Publication title -
acta obstetricia et gynecologica scandinavica
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.401
H-Index - 102
eISSN - 1600-0412
pISSN - 0001-6349
DOI - 10.1080/00016340802012254
Subject(s) - nomogram , medicine , logistic regression , fetal macrosomia , multivariate statistics , obstetrics , multivariate analysis , receiver operating characteristic , parity (physics) , population , pregnancy , statistics , gestation , mathematics , gestational diabetes , physics , environmental health , particle physics , biology , genetics
Objective. To develop and validate a nomogram that predicts individual probability of cesarean delivery in cases of macrosomia (>4,000 g). Methods. The nomogram was built based on the data from 246 patients who delivered macrosomic infants at Conception Hospital (Marseille, France), and was validated on an external population of 206 patients. Logistic regression was used to construct a model to predict the probability of cesarean section. The calculations were based on actual birth weight. Main outcome measures . The accuracy of the model was evaluated by area under the receiver operator curve. Results . In the multivariate analysis performed on the training set, maternal age ( p = 0.002), parity ( p = 0.003), and maternal height <1.65 m ( p = 0.01) were found to be significantly associated with the occurrence of cesarean delivery and included in the nomogram. The final variables included in the nomogram were: age ( p = 0.01), maternal height ( p = 0.02), parity ( p <0.001), and previous cesarean section ( p = 0.009). Area under the ROCs was 0.80 and 0.78 in the training set before and after bootstrapping, respectively, and 0.88 in the validation set. The calibration of the nomogram was good. Conclusion . We have developed a nomogram based on actual birth weight that accurately predicts the risk of cesarean delivery in cases of macrosomia. This tool might be useful for decision‐making.