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Pediatr Res ; 86(3): 348-354, 2019 09.
Artigo em Inglês | MEDLINE | ID: mdl-31086292

RESUMO

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 (R2 = 0.53, p < 0.001) and corrected age at discontinuation of caffeine therapy (R2 = 0.35, p < 0.001) after adjusting for sex, gestational age, birth weight z-score, and sepsis. 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.


Assuntos
Eletromiografia , Frequência Cardíaca , Terapia Intensiva Neonatal/métodos , Peso ao Nascer , Feminino , Humanos , Recém-Nascido , Recém-Nascido Prematuro , Unidades de Terapia Intensiva Neonatal , Modelos Lineares , Masculino , Análise Multivariada , Alta do Paciente , Prognóstico , Estudos Prospectivos , Processamento de Sinais Assistido por Computador , Suíça , Resultado do Tratamento
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