Heart rate fluctuation after birth predicts subsequent cardiorespiratory stability in preterm infants.


Journal

Pediatric research
ISSN: 1530-0447
Titre abrégé: Pediatr Res
Pays: United States
ID NLM: 0100714

Informations de publication

Date de publication:
09 2019
Historique:
received: 14 02 2019
accepted: 18 04 2019
revised: 27 03 2019
pubmed: 16 5 2019
medline: 20 8 2020
entrez: 16 5 2019
Statut: ppublish

Résumé

Cardiorespiratory stability of preterm infants is a prerequisite for discharge from the neonatal intensive care unit (NICU) but very difficult to predict. We aimed to assess whether characterizing heart rate fluctuation (HRF) within the first days of life has prognostic utility. We conducted a prospective cohort study in 90 preterm infants using a previously validated surface diaphragmatic electromyography (sEMG) method to derive interbeat intervals. We characterized HRF by time series parameters including sample entropy (SampEn) and scaling exponent alpha (ScalExp) obtained from daily 3-h measurements. Data were analyzed by multivariable, multilevel linear regression. We obtained acceptable raw data from 309/330 sEMG measurements in 76/90 infants born at a mean (range) of 30.2 (24.7-34.0) weeks gestation. We found a significant negative association of SampEn with duration of respiratory support (R Baseline SampEn calculated over the first 5 days of life carries prognostic utility for an estimation of subsequent respiratory support and pre-discharge cardiorespiratory stability in preterm infants, both important for planning of treatment and utilization of health care resources.

Sections du résumé

BACKGROUND
Cardiorespiratory stability of preterm infants is a prerequisite for discharge from the neonatal intensive care unit (NICU) but very difficult to predict. We aimed to assess whether characterizing heart rate fluctuation (HRF) within the first days of life has prognostic utility.
METHODS
We conducted a prospective cohort study in 90 preterm infants using a previously validated surface diaphragmatic electromyography (sEMG) method to derive interbeat intervals. We characterized HRF by time series parameters including sample entropy (SampEn) and scaling exponent alpha (ScalExp) obtained from daily 3-h measurements. Data were analyzed by multivariable, multilevel linear regression.
RESULTS
We obtained acceptable raw data from 309/330 sEMG measurements in 76/90 infants born at a mean (range) of 30.2 (24.7-34.0) weeks gestation. We found a significant negative association of SampEn with duration of respiratory support (R
CONCLUSIONS
Baseline SampEn calculated over the first 5 days of life carries prognostic utility for an estimation of subsequent respiratory support and pre-discharge cardiorespiratory stability in preterm infants, both important for planning of treatment and utilization of health care resources.

Identifiants

pubmed: 31086292
doi: 10.1038/s41390-019-0424-6
pii: 10.1038/s41390-019-0424-6
doi:

Types de publication

Journal Article Observational Study Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

348-354

Auteurs

Kerstin Jost (K)

Department of Pediatrics, University Children's Hospital Basel UKBB, Basel, Switzerland.
Department of Biomedical Engineering, University of Basel, Basel, Switzerland.

Alexandre N Datta (AN)

Department of Pediatrics, University Children's Hospital Basel UKBB, Basel, Switzerland.

Urs P Frey (UP)

Department of Pediatrics, University Children's Hospital Basel UKBB, Basel, Switzerland.

Béla Suki (B)

Department of Biomedical Engineering, Boston University, Boston, MA, USA.

Sven M Schulzke (SM)

Department of Pediatrics, University Children's Hospital Basel UKBB, Basel, Switzerland. sven.schulzke@ukbb.ch.

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