An analysis of predictors associated with intrapartum c-section among nulliparous women

Dur-E-Shahwar, Nadeem F. Zuberi

Research output: Contribution to journalArticlepeer-review

Abstract

Objective: To identify risk factors associated with cesarean section among nulliparous women presenting in labor at term with singleton cephalic fetus and to build a multiple logistic regression model for predicting its probability. Study Design: It was a Case Control study. Place and Duration of Study: This study was conducted at the Department of Obstetrics and Gynaecology Aga Khan University Hospital Karachi from April 2010 to January 2011. Materials and Methods: Non-probability purposive sampling technique used, 280 nulliparous women of 18-45 years selected; 140 women who had caesarean section were taken as cases and 140 women who had vaginal delivery were taken as control. Results: We evaluated 14 variables out of these seven (cervical dilatation and length, fetal station, history of miscarriage, maternal age, height and spontaneous rupture of membranes) were found to be statistically significant in Univariate analysis. The final model improved and predicted 70.0% of cases correctly. Of the variables evaluated, 5 variables remained significant in multiple logistic regression model which predicted the women at higher risk of for cesarean section. The receiver operating characteristic curve (ROC) analysis of risk status for predicting the probability of cesarean section had area under the curve of 0.729; suggesting it to be a good predictive model. Conclusion: Final model included maternal history of miscarriage, maternal age and height, cervical dilatation and length at admission; and has the ability to identify women at risk of requiring cesarean section just at the time of presenting in labor.

Original languageEnglish
Pages (from-to)19-23
Number of pages5
JournalMedical Forum Monthly
Volume28
Issue number5
Publication statusPublished - May 2017

Keywords

  • Cesarean delivery
  • Primary emergency cesarean section
  • Risk factors

Fingerprint

Dive into the research topics of 'An analysis of predictors associated with intrapartum c-section among nulliparous women'. Together they form a unique fingerprint.

Cite this