Clinical phenotypes for risk stratification in small-for-gestational-age fetuses.

OBJECTIVE: This study evaluates whether clinical phenotypes of small for gestational (SGA) fetuses can be identified and used for adverse perinatal outcome risk stratification to facilitate decision-making. METHODS: This multicentre observational cohort study was conducted in two tertiary care university hospitals. It included 17,631 consecutive singleton pregnancies, among which 1274 (7.2%) were defined as SGA at birth according to INTERGROWTH-21st standards. The main outcome was the development of clinical clusters of SGA phenotypes. RESULTS: Nine SGA clinical phenotypes were identified using a predefined conceptual framework. Every delivery and perinatal outcome analysed showed statistically significant differences between phenotypes. The total SGA cohort had a 3 times increased risk of perinatal mortality than non-SGA fetuses (1.4% vs 0.4%; p<0.001). The SGA clinical phenotypes exhibited three patterns of perinatal mortality risk: the highest risk included the congenital anomalies and second- or third-trimester haemorrhage clusters (8.3%; odds ratio [OR] 17.17, 95% confidence interval [CI] 2.17-136.12 for congenital anomalies and OR 9.94, 95% CI 1.23-72.57 for second- or third-trimester haemorrhage); the medium risk included the gestational diabetes (3.8%; OR 9.59, 95% CI 1.27-72.57), preterm birth (3.2%; OR 4.65, 95% CI 0.62-35.01), and intrauterine growth restriction (3.1%; OR 5.93, 95% CI 3.21-10.95) clusters; and the lowest risk included the remaining clusters. Perinatal mortality rate did not differ between SGA fetuses without other clinical conditions (which encompassed 54.1% of SGA fetuses) and appropriate for gestational age fetuses (0.1% vs 0.4%; p=0.27; OR 0.41, 95% CI 0.06-2.94). SGA combined with other obstetric pathologies significantly increased perinatal mortality risk, highlighting in maternal diabetes (OR 24.40, 95% CI 1.31-453.91). CONCLUSIONS: We identified nine SGA clinical phenotypes associated with different patterns of risk for adverse perinatal outcomes. Our results suggest that adding clinical characteristics to ultrasound results would improve risk stratification and decision-making for SGA fetuses. Future clinical trials on the control of fetuses with SGA should take into account, in addition to Doppler and estimated fetal weight, this clinical information. This article is protected by copyright. All rights reserved.