Published online May 1, 2006
PEDIATRICS Vol. 117 No. 5 May 2006, pp. 1853-1854 (doi:10.1542/peds.2006-0372)

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Physiomarkers of Neonatal Heart Rate

Mohamad El-Khatib, MD
Department of Anesthesiology
American University of Beirut
Beirut 1107-2020, Lebanon

To the Editor.

I read with interest the recent clinical report by Griffin et al, "Heart Rate Characteristics: Novel Physiomarkers to Predict Neonatal Infection and Death."¹ The authors concluded that heart rate characteristics (HRC) are noninvasively monitored physiomarkers that identify infants in the NICU who are at high risk of sepsis, urinary tract infection, and death. Calculation of the HRC index is a rather complicated process. First, it requires the determination of SD, asymmetry, and entropy from a sample of a continuously monitored neonatal heart rate. Second, these statistical measures are further analyzed and combined by a nonlinear and exponential mathematical expression derived from a multivariate logistic regression to calculate the HRC index.

Previous studies^2–4 have shown that simple statistical representation (eg, mean and SD) might not be valuable in characterizing the pattern of a physiologic parameter and that more sophisticated measures such as entropy are needed. Fleisher et al² showed that the changes in approximate entropy of heart rate was associated with postoperative ventricular dysfunction in high-risk noncardiac surgery patients. We recently showed that approximate entropy is a superior indicator for respiratory pattern, reversibility of respiratory failure, and ability to maintain adequate spontaneous efforts after weaning from mechanical ventilation.³ Furthermore, entropy of the electroencephalogram has been used as an indicator of depth of anesthesia levels during surgical procedures.⁴

In the study by Griffin et al,¹ the SD (a nonpowerful statistical tool) was combined with entropy (a powerful statistical tool) toward the characterization of the heart rate pattern and subsequent determination of the HRC index. It would have been interesting if Griffin et al used only the entropy measure to analyze the regularity of the heart rate in their neonatal patients for prediction of infection and death. If applicable, it would decrease the level of complication of the computational analysis and establish entropy as a useful clinical tool in the field of neonatology, as in other fields of medicine.

REFERENCES

1. Griffin MP, Lake DE, Bissonette EA, Harrell FE Jr, O'Shea TM, Moorman JR. Heart rate characteristics: novel physiomarkers to predict neonatal infection and death. Pediatrics. 2005;116 :1070 –1074[Abstract/Free Full Text]
2. Fleisher LA, Pincus SM, Rosenbaum SH. Approximate entropy of heart rate as a correlate of postoperative ventricular dysfunction. Anesthesiology. 1993;78 :683 –692[Web of Science][Medline]
3. El-Khatib M, Jamaleddine G, Soubra R, Muallem M. Pattern of spontaneous breathing: potential marker for weaning outcome. Intensive Care Med. 2001;27 :52 –58[CrossRef][Web of Science][Medline]
4. Hudetz AG, Wood JD, Kampine JP. Cholinergic reversal of isoflurane anesthesia in rats as measured by cross-approximate entropy of the electroencephalogram. Anesthesiology. 2003;99 :1125 –1131[CrossRef][Web of Science][Medline]

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PEDIATRICS (ISSN 1098-4275). ©2006 by the American Academy of Pediatrics

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Physiomarkers of Neonatal Heart Rate: In Reply

M. Pamela Griffin, Douglas E. Lake, and J. Randall Moorman
Pediatrics 2006 117: 1854. [Extract] [Full Text]  

This Article Extract Full Text (PDF) Alert me when this article is cited Alert me when eLetters are posted Alert me if a correction is posted Services E-mail this article to a friend Related articles in Pediatrics Similar articles in this journal Alert me to new issues of the journal Add to My File Cabinet Download to citation manager Request Permissions Citing Articles Citing Articles via CrossRef Citing Articles via Google Scholar Google Scholar Articles by El-Khatib, M. Search for Related Content PubMed Articles by El-Khatib, M. Related Collections Premature & Newborn Social Bookmarking                         What's this?