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.
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.
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).
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.