Bioreactance-derived haemodynamic parameters in the transitional phase in preterm neonates: a longitudinal study.
Lizelle Van WykJohan SmithJohn LawrensonCarl J LombardWillem Pieter de BoodePublished in: Journal of clinical monitoring and computing (2021)
Bioreactance (BR) is a novel, non-invasive technology that is able to provide minute-to-minute monitoring of cardiac output and additional haemodynamic variables. This study aimed to determine the values for BR-derived haemodynamic variables in stable preterm neonates during the transitional period. A prospective observational study was performed in a group of stable preterm (< 37 weeks) infants in the neonatal service of Tygerberg Children's Hospital, Cape Town, South Africa. All infants underwent continuous bioreactance (BR) monitoring until 72 h of life. Sixty three preterm infants with a mean gestational age of 31 weeks and mean birth weight of 1563 g were enrolled. Summary data and time series graphs were drawn for BR-derived heart rate, non-invasive blood pressure, stroke volume, cardiac output and total peripheral resistance index. All haemodynamic parameters were significantly associated with postnatal age, after correction for clinical variables (gestational age, birth weight, respiratory support mode). To our knowledge, this is the first paper to present longitudinal BR-derived haemodynamic variable data in a cohort of stable preterm infants, not requiring invasive ventilation or inotropic support, during the first 72 h of life. Bioreactance-derived haemodynamic monitoring is non-invasive and offers the ability to simultaneously monitor numerous haemodynamic parameters of global systemic blood flow. Moreover, it may provide insight into transitional physiology and its pathophysiology.
Keyphrases
- gestational age
- birth weight
- preterm infants
- preterm birth
- low birth weight
- south africa
- heart rate
- blood pressure
- blood flow
- healthcare
- heart rate variability
- mental health
- electronic health record
- hiv positive
- left ventricular
- emergency department
- heart failure
- young adults
- machine learning
- big data
- physical activity
- artificial intelligence
- extracorporeal membrane oxygenation
- respiratory tract
- human immunodeficiency virus
- blood glucose
- brain injury
- adipose tissue