The evolution of the labor curve and its implications for clinical practice: the relationship between cervical dilation, station, and time during labor.

ABSTRACT

The assessment of labor progress is germane to every woman in labor. Two labor disorders-arrest of dilation and arrest of descent-are the primary indications for surgery in close to 50% of all intrapartum cesarean deliveries and are often contributing indications for cesarean deliveries for fetal heart rate abnormalities. Beginning in 1954, the assessment of labor progress was transformed by Friedman. He published a series of seminal works describing the relationship between cervical dilation, station of the presenting part, and time. He proposed nomenclature for the classification of labor disorders. Generations of obstetricians used this terminology and normal labor curves to determine expected rates of dilation and fetal descent and to decide when intervention was required. The analysis of labor progress presents many mathematical challenges. Clinical measurements of dilation and station are imprecise and prone to variation, especially for inexperienced observers. Many interrelated factors influence how the cervix dilates and how the fetus descends. There is substantial variability in when data collection begins and in the frequency of examinations. Statistical methods to account for these issues have advanced considerably in recent decades. In parallel, there is growing recognition among clinicians of the limitations of using time alone to assess progress in cervical dilation in labor. There is wide variation in the patterns of dilation over time and most labors do not follow an average dilation curve. Reliable assessment of labor progression is important because uncertainty leads to both over-use and under-use of cesarean delivery and neither of these extremes are desirable. This review traces the evolution of labor curves, describes how limitations are being addressed to reduce uncertainty and to improve the assessment of labor progression using modern statistical techniques and multi-dimensional data, and discusses the implications for obstetrical practice.