4.5 Article

Can ultrasound measurements replace digitally assessed elements of the Bishop score?

Journal

ACTA OBSTETRICIA ET GYNECOLOGICA SCANDINAVICA
Volume 88, Issue 3, Pages 325-331

Publisher

WILEY
DOI: 10.1080/00016340902730417

Keywords

Bishop score; fetal head-perineum distance; cervical length; posterior cervical angle; cervical dilatation; ultrasound; induction of labor

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Objective. To compare elements of the Bishop score and corresponding sonographic measurements before induction of labor, and assess how predictive factors can be used in a clinical setting. Design. Prospective comparative clinical study. Setting. Secondary referral center, university hospital. Population. A total of 275 women scheduled for induction of labor. Methods. Fetal head descent to the perineum was assessed with transperineal ultrasound. Cervical length, posterior angle, and dilatation were evaluated with transvaginal ultrasound followed by Bishop score without knowledge of the ultrasound measurements. Results. Univariable regression analyses of successful induction were significant for digital assessment of cervical dilatation, ultrasound measured fetal head-perineum distance 40 mm, ultrasound measured cervical length 25 mm, and ultrasound measured posterior cervical angle 90 degrees. After adjusting for maternal factors in a multivariable model, estimates were significant for previous vaginal birth (OR 5.3; 95% CI 2.1-13.9, p0.01), but borderline for maternal height (OR 1.1; 95% CI 1.0-1.2, p=0.01) and ultrasound measured posterior cervical angle 90 degrees (OR 2.6; 95% CI 1.1-6.1, p=0.03). A scoring model combining ultrasound measured fetal head-perineum distance, cervical length, cervical posterior angle and digitally assessed cervical dilatation, discriminated successful and failed induction at 71% (95% CI 61-80%, p0.01) area under the receiver-operating characteristics curve. Conclusion. Digital assessment of fetal head descent, cervical length and position can possibly be replaced with ultrasound measurements. Dilatation is best evaluated with digital assessment. Combination of these four factors can predict success of labor induction.

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