UCSF

Background

Gestational age (GA) is frequently unknown or inaccurate in pregnancies in low-income countries. Early identification of preterm infants may help link them to potentially life-saving interventions.

Methods

We conducted a validation study in a community-based birth cohort in rural Bangladesh. GA was determined by pregnancy ultrasound (<20 weeks). Community health workers conducted home visits (<72 hours) to assess physical/neuromuscular signs and measure anthropometrics. The distribution, agreement, and diagnostic accuracy of different clinical methods of GA assessment were determined compared with early ultrasound dating.

Results

In the live-born cohort (n = 1066), the mean ultrasound GA was 39.1 weeks (SD 2.0) and prevalence of preterm birth (<37 weeks) was 11.4%. Among assessed newborns (n = 710), the mean ultrasound GA was 39.3 weeks (SD 1.6) (8.3% preterm) and by Ballard scoring the mean GA was 38.9 weeks (SD 1.7) (12.9% preterm). The average bias of the Ballard was -0.4 weeks; however, 95% limits of agreement were wide (-4.7 to 4.0 weeks) and the accuracy for identifying preterm infants was low (sensitivity 16%, specificity 87%). Simplified methods for GA assessment had poor diagnostic accuracy for identifying preterm births (community health worker prematurity scorecard [sensitivity/specificity: 70%/27%]; Capurro [5%/96%]; Eregie [75%/58%]; Bhagwat [18%/87%], foot length <75 mm [64%/35%]; birth weight <2500 g [54%/82%]). Neonatal anthropometrics had poor to fair performance for classifying preterm infants (areas under the receiver operating curve 0.52-0.80).

Conclusions

Newborn clinical assessment of GA is challenging at the community level in low-resource settings. Anthropometrics are also inaccurate surrogate markers for GA in settings with high rates of fetal growth restriction.