Literature DB >> 34006917

Early bradycardia detection and therapeutic interventions in preterm infant monitoring.

Matthieu Doyen1, Alfredo I Hernández2, Cyril Flamant3, Antoine Defontaine4, Géraldine Favrais5, Miguel Altuve6, Bruno Laviolle7, Alain Beuchée1, Guy Carrault1, Patrick Pladys1.   

Abstract

In very preterm infants, cardio-respiratory events and associated hypoxemia occurring during early postnatal life have been associated with risks of retinopathy, growth alteration and neurodevelopment impairment. These events are commonly detected by continuous cardio-respiratory monitoring in neonatal intensive care units (NICU), through the associated bradycardia. NICU nurse interventions are mainly triggered by these alarms. In this work, we acquired data from 52 preterm infants during NICU monitoring, in order to propose an early bradycardia detector which is based on a decentralized fusion of three detectors. The main objective is to improve automatic detection under real-life conditions without altering performance with respect to that of a monitor commonly used in NICU. We used heart rate lower than 80 bpm during at least 10 sec to define bradycardia. With this definition we observed a high rate of false alarms (64%) in real-life and that 29% of the relevant alarms were not followed by manual interventions. Concerning the proposed detection method, when compared to current monitors, it provided a significant decrease of the detection delay of 2.9 seconds, without alteration of the sensitivity (97.6% vs 95.2%) and false alarm rate (63.7% vs 64.1%). We expect that such an early detection will improve the response of the newborn to the intervention and allow for the development of new automatic therapeutic strategies which could complement manual intervention and decrease the sepsis risk.

Entities:  

Year:  2021        PMID: 34006917     DOI: 10.1038/s41598-021-89468-x

Source DB:  PubMed          Journal:  Sci Rep        ISSN: 2045-2322            Impact factor:   4.379


  7 in total

1.  Online apnea-bradycardia detection based on hidden semi-Markov models.

Authors:  Miguel Altuve; Guy Carrault; Alain Beuchée; Patrick Pladys; Alfredo I Hernández
Journal:  Med Biol Eng Comput       Date:  2014-10-10       Impact factor: 2.602

2.  Predicting Bradycardia in Preterm Infants Using Point Process Analysis of Heart Rate.

Authors:  Alan H Gee; Riccardo Barbieri; David Paydarfar; Premananda Indic
Journal:  IEEE Trans Biomed Eng       Date:  2016-11-24       Impact factor: 4.538

3.  Coupled Hidden Markov Model-Based Method for Apnea Bradycardia Detection.

Authors:  N Montazeri Ghahjaverestan; S Masoudi; M B Shamsollahi; A Beuchee; P Pladys; D Ge; A I Hernandez
Journal:  IEEE J Biomed Health Inform       Date:  2015-02-20       Impact factor: 5.772

4.  Apnea is associated with neurodevelopmental impairment in very low birth weight infants.

Authors:  Annie Janvier; May Khairy; Athanasios Kokkotis; Carole Cormier; Denise Messmer; Keith J Barrington
Journal:  J Perinatol       Date:  2004-12       Impact factor: 2.521

5.  Uncorrelated randomness of the heart rate is associated with sepsis in sick premature infants.

Authors:  Alain Beuchée; Guy Carrault; Jean Yves Bansard; Emmanuelle Boutaric; Pierre Bétrémieux; Patrick Pladys
Journal:  Neonatology       Date:  2009-03-12       Impact factor: 4.035

6.  Accurate automated apnea analysis in preterm infants.

Authors:  Brooke D Vergales; Alix O Paget-Brown; Hoshik Lee; Lauren E Guin; Terri J Smoot; Craig G Rusin; Matthew T Clark; John B Delos; Karen D Fairchild; Douglas E Lake; Randall Moorman; John Kattwinkel
Journal:  Am J Perinatol       Date:  2013-04-16       Impact factor: 1.862

7.  Pattern discovery in critical alarms originating from neonates under intensive care.

Authors:  Rohan Joshi; Carola van Pul; Louis Atallah; Loe Feijs; Sabine Van Huffel; Peter Andriessen
Journal:  Physiol Meas       Date:  2016-03-30       Impact factor: 2.833

  7 in total

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