Characterizing uterine responsiveness to oxytocin augmentation across four labor patterns in maternal obesity.
Birth
; 2023 Nov 01.
Article
em En
| MEDLINE
| ID: mdl-37915283
ABSTRACT
BACKGROUND:
Optimizing care during labor protraction is a key strategy for reducing cesareans, especially among people with obesity. The pathophysiology of labor dystocia remains poorly understood, limiting precise interventions targeting the cause of protraction.METHODS:
In this secondary analysis of nulliparas (n = 92) with obesity (BMI ≥ 30 kg/m2 ) and spontaneous labor onset, we classified labor into four phenotypes based on duration of protraction and birth route (1) no protraction, (2) short protraction and vaginal birth, (3) extended protraction meeting criteria for labor arrest, but with eventual progression and vaginal birth, and (4) extended protraction meeting criteria for labor arrest and cesarean birth. Across these phenotypes, we compared MVU, oxytocin dose, and novel measures of uterine responsiveness to oxytocin augmentation (MVU to oxytocin dose ratios).RESULTS:
In our sample, phenotype group 1 comprised 14.1% (n = 13); group 2 comprised 30.4% (n = 28); group 3 comprised 34.8% (n = 32); and group 4 comprised 20.7% (n = 19). Uterine responsiveness to oxytocin, but not MVU, decreased with each labor phenotype. Participants with cesarean birth had the lowest uterine responsiveness to oxytocin.CONCLUSION:
Labor and birth outcomes were associated with measures of uterine responsiveness to oxytocin rather than MVU alone, and thus these may be more clinically appropriate measures for guiding clinical decision-making. Current criteria for labor arrest are likely too stringent for nulliparas with obesity, many of whom appear to progress to safe vaginal birth after longer labor durations. Differences in uterine responsiveness to oxytocin augmentation across the groups suggests underlying physiologic differences in the labor phenotypes, which should drive future research targeting pathophysiology.
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Coleções:
01-internacional
Base de dados:
MEDLINE
Idioma:
En
Ano de publicação:
2023
Tipo de documento:
Article