Labor Dystocia: Rethinking the Labor Curve in a Changing Obstetric Population

Labor dystocia remains the leading indication for primary cesarean delivery in the United States (US), yet its definition and management have remained largely unchanged, despite shifts in obstetric population characteristics and clinical practice. This review examines current evidence on the diagnosis, predictors, intrapartum assessment and management of labor dystocia, with particular attention to how maternal obesity, intrapartum ultrasound, and racial and ethnic disparities in cesarean rates challenge and complicate our existing framework.

Time-based thresholds for dystocia were built using patient populations that no longer reflect the demographics of pregnant people in the US. These historic datasets excluded cesarean deliveries and thus may systematically over-diagnose arrest in normal labors. Maternal obesity, now present in nearly a third of pregnant people in the US, is a physiologically distinct context in which standard uterine activity benchmarks and augmentation protocols may not apply. Intrapartum ultrasound offers a more objective approach to characterizing mechanical contributors to dystocia that digital examination may not reliably identify. Racial and ethnic disparities in cesarean rates persist after adjustment for clinical and socioeconomic factors, suggesting that provider decision-making and structural drivers may be an underappreciated contributor to high cesarean rates in the US.

A more individualized approach to diagnosis and management of labor dystocia may include integration of objective intrapartum data and accounting for population and individual level differences in labor physiology. This is needed to reduce unnecessary cesarean delivery and address persistent disparities in its use. Emerging machine learning models incorporating multiple labor parameters show promise in improving predictive accuracy beyond time-based approaches alone.