Prediction instrument for obstructed labor

Abstract

Background: Obstructed labor is a complication during childbirth that can increase maternal and neonatal mortality and morbidity, making early detection crucial for prevention. However, currently, no instrument is available to predict the occurrence of obstructed labor.

Objectives: This study aims to develop an effective prediction instrument for the early identification of obstructed labor, enabling timely interventions to reduce associated risks.

Methods: The study employs a case-control design for the development of the instrument and a cohort design for its testing. The research is conducted in three phases: Phase I involves a literature review to identify risk factors, Phase II focuses on the initial testing of the instrument, and Phase III includes the validation of the instrument in a clinical setting. The study population consists of 360 women in labor for instrument development and 40 women for instrument testing. Bivariate analysis is conducted using chi-square tests, while multivariate analysis is performed using logistic regression, followed by ROC curve analysis to determine the optimal cutoff point.

Results: The results indicate significant associations between obstructed labor and factors such as infant birth weight, maternal height, age, obesity, upper arm circumference, anemia, history of abdominal surgery, and weight gain during pregnancy. The final predictive model demonstrated an AUC of 0.908, indicating excellent predictive performance with a sensitivity of 85.7% and specificity of 80.8%.

Conclusions: This study highlights the importance of early risk detection and intervention and contributes to the literature by providing an instrument capable of predicting the risk of obstructed labor.