OC20.01: Twin versus singleton growth charts in the diagnosis of small for gestational age in twin pregnancy: systematic review and meta‐analysis

When singleton charts are used to assess fetal growth in twins, a high proportion of fetuses are diagnosed as SGA, but whether this approach is a good predictor of adverse outcomes is controversial. This meta-analysis aims to evaluate the perinatal outcomes of SGA twins diagnosed with singleton or twin charts. MEDLINE, EMBASE, Scopus and the Web of Science were searched up to October 2023. Studies including twin pregnancies assessed with both singleton and twin charts of estimated fetal weight for diagnosis of SGA were included. We performed a random-effect meta-analysis of proportion of perinatal outcomes: we compared SGA fetuses diagnosed with twin versus singleton charts and SGA diagnosed with singleton charts versus non-SGA diagnosed with twin charts. Four studies including 13623 twins were included. The rate of SGA diagnosed with singleton charts was 32.5%, whereas twin charts classified 5.5% of twins as SGA. In the group of SGA defined using twin charts, the rate of composite adverse neonatal outcomes was significantly higher than in the group of singleton charts (OR 3.24, 95% CI 1.62-6.49). Other perinatal outcomes showed the same trend: NICU admission (OR 2.95 95% CI 1.30-6.68), RDS (OR 2.18, 95% CI 1.69-2.82), neonatal sepsis (OR 2.55, 95% CI 1.83-3.56), neonatal mortality (OR 4.03, 95% CI 2.46-6.60). When we compared all outcomes between SGA fetuses diagnosed with singleton charts and non-SGA fetuses classified using the twin charts, no significant differences were noted between the two groups in terms of neonatal morbidity and mortality (p>0.05 for all). Twin charts are more specific than singleton charts in identifying SGA at higher risk of adverse outcomes. The outcomes of cases not classified as SGA with twin charts did not differ from SGA fetuses diagnosed with singletons. Large prospective studies are needed to investigate the most accurate method for growth assessment and prediction of adverse outcomes in twins.