Brain activity as a biomarker for personalised caffeine treatment in premature neonates
Usman, F.; Zandvoort, C. S.; Robinson, S.; Peck, M.; Cobo, M. M.; Adjei, T.; Baxter, L.; Evans Fry, R.; Hauck, A. G. V.; Rogers, R.; Schmidt Mellado, G.; Scrivens, A.; van der Vaart, M.; De Vos, M.; Adams, E.; van den Anker, J.; Hartley, C.
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BackgroundMedication in hospitalised infants is often prescribed using a one-size-fits-all approach due to lack of clinical biomarkers. Caffeine is one of the most frequently administered medicines in neonatology - prescribed for the management of apnoea of prematurity, to aid extubation and increasingly for conditions such as bronchopulmonary dysplasia. Caffeine guidelines for the management of apnoea of prematurity indicate use based on the age of the infant, but this does not account for individual variation in apnoea rate. Consequently, infants may risk caffeine undertreatment or adverse events due to over-exposure. Apnoea in preterm infants is related to nervous system immaturity, hence, as an essential first step to assess whether brain activity may be a useful biomarker for caffeine treatment, we tested the hypothesis that apnoea rate is related to brain activity. Methods and FindingsIn this single-centre prospective observational cohort study, we simultaneously recorded brain activity using electroencephalography (EEG) and respiration using impedance pneumography in 74 infants aged 31-36 weeks postmenstrual age (PMA) on 138 separate occasions. We demonstrate that apnoea rate in moderate/late preterm infants is dependent on brain age gap (defined as the difference between the infants age assessed from their brain activity and their PMA). In contrast, apnoea rate is not correlated with PMA in this age range. In an exploratory sub-study, we provide initial evidence that when caffeine is discontinued, infants with immature brain activity have more frequent apnoeas and desaturations compared with those with more mature brain function. ConclusionsThese findings provide initial evidence to indicate that brain age gap (assessed automatically using machine learning) is a candidate biomarker for personalised caffeine treatment in preterm infants.
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