Development and validation of a nomogram to predict the risk of cesarean delivery in macrosomia.
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.


METHODS
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.


CONCLUSIONS
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.
Mazouni
Chafika
C
Department of Obstetrics and Gynecology, Conception Hospital, Marseille, France. chafika.mazouni@ap-hm.fr
Rouzier
Roman
R
Collette
Emmanuelle
E
Menard
Jean-Pierre
JP
Magnin
Georges
G
Gamerre
Marc
M
Deter
Russell
R
D019540:Area Under Curve; D002585:Cesarean Section; D005260:Female; D005320:Fetal Macrosomia; D006801:Humans; D007231:Infant, Newborn; D016015:Logistic Models; D049451:Nomograms; D011237:Predictive Value of Tests; D011247:Pregnancy; D012189:Retrospective Studies; D012307:Risk Factors