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Prediction of outcome of hypoxic-ischemic encephalopathy in newborns undergoing therapeutic hypothermia using heart rate variability

Journal of Perinatology (2023)Cite this article

Subjects

Abstract

Objective

To assess the use of continuous heart rate variability (HRV) as a predictor of brain injury severity in newborns with moderate to severe HIE that undergo therapeutic hypothermia.

Study Design

Two cohorts of newborns (n1 = 55, n2 = 41) with moderate to severe hypoxic-ischemic encephalopathy previously treated with therapeutic hypothermia. HRV was characterized by root mean square in the short time scales (RMSS) during therapeutic hypothermia and through completion of rewarming. A logistic regression and Naïve Bayes models were developed to predict the MRI outcome of the infants using RMSS. The encephalopathy grade and gender were used as control variables.

Results

For both cohorts, the predicted outcomes were compared with the observed outcomes. Our algorithms were able to predict the outcomes with an area under the receiver operating characteristic curve of about 0.8.

Conclusions

HRV assessed by RMSS can predict severity of brain injury in newborns with HIE.

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Fig. 1: Variation of RMSS as a function of hours since birth.
Fig. 2: Decision tree of the Naïve Bayes classifier.
Fig. 3: AUC as a function of hours since birth for the logistic regression model and the Naïve Bayes classifier.

Data availability

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

Code availability

Matlab code used to analyze the data is available upon request.

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Acknowledgements

This work was supported by internal special purpose funds available in the Prenatal Pediatrics Institute, by the Award Number P30 HD040677, UL1RR031988, and KL2 RR031987 from the National Center for Research Resources and by the American Heart Association Grant-in-Aid. We want to thank Patricia Saulino for her editorial assistance. We also want to thank Amaya Sinha for assisting in data cleaning.

Author information

Author notes

  1. These authors contributed equally: Alessandro Presacco, Venkata C. Chirumamilla.

Authors and Affiliations

  1. Prenatal Pediatrics Institute, Children’s National Hospital, Washington, DC, USA

    Alessandro Presacco, Venkata C. Chirumamilla, Gilbert Vezina, Adre Du Plessis & Rathinaswamy B. Govindan

  2. Division of Neonatology, Children’s National Hospital, Washington, DC, USA

    Gilbert Vezina & An N. Massaro

  3. Division of Diagnostic Imaging and Radiology, Children’s National Hospital, Washington, DC, USA

    Ruoying Li

  4. Department of Pediatrics, The George Washington University School of Medicine, Washington, DC, USA

    Adre Du Plessis, An N. Massaro & Rathinaswamy B. Govindan

Authors
  1. Alessandro Presacco
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  2. Venkata C. Chirumamilla
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  3. Gilbert Vezina
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  4. Ruoying Li
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  6. An N. Massaro
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  7. Rathinaswamy B. Govindan
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Contributions

AP and VC carried out the analyses and wrote the paper, GV validated the MRI data, RL collected the EKG data, ADP helped conceive, devise and supervise the experiment and critically edited the manuscript, AM conceived and devised the experiment and wrote the paper and RG conceived and devised the experiment, analyzed the data and wrote the paper.

Corresponding author

Correspondence to Alessandro Presacco.

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Presacco, A., Chirumamilla, V.C., Vezina, G. et al. Prediction of outcome of hypoxic-ischemic encephalopathy in newborns undergoing therapeutic hypothermia using heart rate variability. J Perinatol (2023). https://doi.org/10.1038/s41372-023-01754-w

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