Using cluster analysis to describe phenotypical heterogeneity in extremely preterm infants: a retrospective whole-population study

OBJECTIVE: To use cluster analysis to identify discrete phenotypic groups of extremely preterm infants. DESIGN: Secondary analysis of a retrospective whole population study. SETTING: All neonatal units in England between 2014 and 2019. PARTICIPANTS: Infants live-born at less than 28 weeks of gestation and admitted to a neonatal unit. INTERVENTIONS: K-means cluster analysis was performed with the gestational age, Apgar score at 5 min and duration of mechanical ventilation as input variables. PRIMARY AND SECONDARY OUTCOME MEASURES: Bronchopulmonary dysplasia, discharge on home oxygen, intraventricular haemorrhage, death before discharge from neonatal care. RESULTS: Ten thousand one hundred and ninety-seven infants (53% male) were classified into four clusters: Cluster 1 contained infants with intermediate gestation and duration of ventilation and had an intermediate mortality and incidence of bronchopulmonary dysplasia. Cluster 2 contained infants with the highest gestation, a shorter duration of ventilation and the lowest mortality. Cluster 3 contained infants with the lowest Apgar score and highest mortality and incidence of intraventricular haemorrhage. Cluster 4 contained infants with the lowest gestation, longest duration of ventilation and highest incidence of bronchopulmonary dysplasia. CONCLUSION: Clinical parameters can classify extremely preterm infants into discrete phenotypic groups with differing subsequent neonatal outcomes.