129
Views
18
CrossRef citations to date
0
Altmetric
Original

A scoring system for detection of macrosomia and prediction of shoulder dystocia: A disappointment

, MD, , , , &
Pages 699-705 | Received 09 Feb 2006, Accepted 26 Apr 2006, Published online: 07 Jul 2009
 

Abstract

Objective. To develop a scoring system for the detection of a macrosomic fetus (birth weight (BW) ≥ 4000 g) and predict shoulder dystocia among large for gestational age fetuses.

Study design. We retrospectively identified all singletons with accurate gestational age (GA) that were large for GA (abdominal circumference (AC) or estimated fetal weight (EFW) ≥ 90% for GA) at ≥37 weeks with delivery within three weeks. The scoring system was: 2 points for biparietal diameter, head circumference, AC, or femur length ≥90% for GA, or if the amniotic fluid index (AFI) was ≥24 cm; for biometric parameters <90% or with AFI <24 cm, 0 points. The predictive values for detection of shoulder dystocia were calculated.

Results. Of the 225 cohorts that met the inclusion criteria the rate of macrosomia was 39% and among vaginal deliveries (n = 120) shoulder dystocia occurred in 12% (15/120; 95% confidence interval (CI) 7–20%). The sensitivity of EFW ≥4500 g to identify a newborn with shoulder dystocia was 0% (95% CI 0–21%), positive predictive values 0% (95% CI 0–46%), and likelihood ratio of 0. For a macrosomia score >6, the corresponding values were 20% (4–48%), 25% (5–57%) and 2.3.

Conclusion. Though the scoring system can identify macrosomia, it offers no advantage over EFW. The scoring system and EFW are poor predictors of shoulder dystocia.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access
  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 65.00 Add to cart
* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.