Determining gestational age for public health care users in Brazil: comparison of methods and algorithm creation
1 Escola Nacional de Saúde Pública Sergio Arouca, Fundação Oswaldo Cruz, Rio de Janeiro, Brasil
2 Instituto Fernandes Figueira, Fundação Oswaldo Cruz, Rio de Janeiro, Brasil
3 Pan-american Health Organization, World Health Organization, Brasília, Brasil
BMC Research Notes 2013, 6:60 doi:10.1186/1756-0500-6-60Published: 13 February 2013
A valid, accurate method for determining gestational age (GA) is crucial in classifying early and late prematurity, and it is a relevant issue in perinatology. This study aimed at assessing the validity of different measures for approximating GA, and it provides an insight into the development of algorithms that can be adopted in places with similar characteristics to Brazil. A follow-up study was carried out in two cities in southeast Brazil. Participants were interviewed in the first trimester of pregnancy and in the postpartum period, with a final sample of 1483 participants after exclusions. The distribution of GA estimates at birth using ultrasound (US) at 21–28 weeks, US at 29+ weeks, last menstrual period (LMP), and the Capurro method were compared with GA estimates at birth using the reference US (at 7–20 weeks of gestation). Kappa, sensitivity, and specificity tests were calculated for preterm (<37 weeks of gestation) and post-term (>=42 weeks) birth rates. The difference in days in the GA estimates between the reference US and the LMP and between the reference US and the Capurro method were evaluated in terms of maternal and infant characteristics, respectively.
For prematurity, US at 21–28 weeks had the highest sensitivity (0.84) and the Capurro method the highest specificity (0.97). For postmaturity, US at 21–28 weeks and the Capurro method had a very high sensitivity (0.98). All methods of GA estimation had a very low specificity (≤0.50) for postmaturity. GA estimates at birth with the algorithm and the reference US produced very similar results, with a preterm birth rate of 12.5%.
In countries such as Brazil, where there is less accurate information about the LMP and lower coverage of early obstetric US examinations, we recommend the development of algorithms that enable the use of available information using methodological strategies to reduce the chance of errors with GA. Thus, this study calls into attention the care needed when comparing preterm birth rates of different localities if they are calculated using different methods.