Prediction of cerebral palsy in extremely preterm infants with beat-to-beat and lower-resolution heart rate variability metrics

OBJECTIVE: To validate previous findings that low heart rate variability (HRV) in the first week after birth is associated increased risk of cerebral palsy (CP). Additionally, to quantify the extent to which higher resolution beat-to-beat HRV metrics improve CP prediction and determine the effect of heartbeat averaging as done in bedside monitors. APPROACH: For infants <29 weeks gestation at a level IV NICU, beat-to-beat heart rate (btbHR) and corresponding RR intervals (btbRR) from standard monitors were retrieved from a data repository. Monitor-displayed HR based on 12-beat averaging and measured at 1Hz was also collected. The data were segmented into 10-minute windows, and multiple HRV metrics were calculated including standard deviation (SD), low-and high-frequency HRV (LF, HF) and normalized low-and highfrequency HRV (nLF, nHF). Additionally, detrended fluctuation analysis (DFA) slope (alpha) and root mean square (RMS) metrics were calculated for both short (alpha1, RMS1) and long range (alpha2, RMS2) fractal scaling exponents. Metrics were averaged over the first week after birth for each infant to provide representative values that were used to quantify CP prediction performance using the area under the receiver operating characteristic curve (AUC). MAIN RESULTS: This study included 102 infants,11 (10.8%) with CP. The SD of the 1Hz monitor HR had AUC 0.754 compared to the highest values of 0.769 and 0.764 for DFA RMS1 and RMS2. Since raw btbHR contains erroneous beats, averaging generally improves performance. With averaging over 12 beats, as is done by most bedside monitors, RMS2 of btbHR and LF of btbRR had highest AUCs of 0.764 and 0.771 respectively. SIGNIFICANCE: We externally validated that, in preterm infants during the first week after birth, reduced HRV predicts subsequent diagnosis of CP. Measures calculated from btbHR data showed slightly superior performance compared with 1Hz heart rate data displayed on standard NICU bedside monitors.

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Journal
Physiological Measurement
Published
2026-09-18
DOI
https://doi.org/10.1088/1361-6579/aea9e9
Primary Topic
Heart Rate Variability and Autonomic Control
Type
article
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article

Prediction of cerebral palsy in extremely preterm infants with beat-to-beat and lower-resolution heart rate variability metrics

Karen D. Fairchild, Rathinaswamy B. Govindan, Venkata C. Chirumamilla, Douglas E. Lake et al.
Physiological Measurement
Heart Rate Variability and Autonomic Control
article

Prediction of cerebral palsy in extremely preterm infants with beat-to-beat and lower-resolution heart rate variability metrics

Karen D. Fairchild, Rathinaswamy B. Govindan, Venkata C. Chirumamilla, Douglas E. Lake, Lisa Letzkus, Adre J du Plessis
article en

Abstract

OBJECTIVE: To validate previous findings that low heart rate variability (HRV) in the first week after birth is associated increased risk of cerebral palsy (CP). Additionally, to quantify the extent to which higher resolution beat-to-beat HRV metrics improve CP prediction and determine the effect of heartbeat averaging as done in bedside monitors. APPROACH: For infants <29 weeks gestation at a level IV NICU, beat-to-beat heart rate (btbHR) and corresponding RR intervals (btbRR) from standard monitors were retrieved from a data repository. Monitor-displayed HR based on 12-beat averaging and measured at 1Hz was also collected. The data were segmented into 10-minute windows, and multiple HRV metrics were calculated including standard deviation (SD), low-and high-frequency HRV (LF, HF) and normalized low-and highfrequency HRV (nLF, nHF). Additionally, detrended fluctuation analysis (DFA) slope (alpha) and root mean square (RMS) metrics were calculated for both short (alpha1, RMS1) and long range (alpha2, RMS2) fractal scaling exponents. Metrics were averaged over the first week after birth for each infant to provide representative values that were used to quantify CP prediction performance using the area under the receiver operating characteristic curve (AUC). MAIN RESULTS: This study included 102 infants,11 (10.8%) with CP. The SD of the 1Hz monitor HR had AUC 0.754 compared to the highest values of 0.769 and 0.764 for DFA RMS1 and RMS2. Since raw btbHR contains erroneous beats, averaging generally improves performance. With averaging over 12 beats, as is done by most bedside monitors, RMS2 of btbHR and LF of btbRR had highest AUCs of 0.764 and 0.771 respectively. SIGNIFICANCE: We externally validated that, in preterm infants during the first week after birth, reduced HRV predicts subsequent diagnosis of CP. Measures calculated from btbHR data showed slightly superior performance compared with 1Hz heart rate data displayed on standard NICU bedside monitors.

Physiological Measurement
Children's National (US), Eckert & Ziegler (United States) (US), University of Virginia Children's Hospital (US), University of Virginia (US)
Good health and well-being
Openalex Percentile: Top 11%
Heart Rate Variability and Autonomic Control
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