Key result
Low neonatal heart rate variability predicts cerebral palsy with an AUC of ~0.75.
Why the study?
Low heart rate variability in the first week after birth is associated with increased risk of cerebral palsy in extremely preterm infants, but the added value of higher resolution beat-to-beat HRV metrics and the effect of heartbeat averaging on prediction are unclear.
Does low heart rate variability in the first week after birth predict the subsequent diagnosis of cerebral palsy in extremely preterm infants?
Cohort (n=102)
No
Does low heart rate variability in the first week after birth predict the subsequent diagnosis of cerebral palsy in extremely preterm infants?
Reduced heart rate variability in the first week of life, readily measurable from standard bedside monitors, can identify extremely preterm infants at high risk for subsequent cerebral palsy.
May support early CP risk stratification via routine monitors in extremely preterm infants; extends prior associations but remains hypothesis-generating pending prospective validation.
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 1 Hz was also collected. The data were segmented into 10 min windows, and multiple HRV metrics were calculated including standard deviation (SD), low- and high-frequency HRV (LF, HF) and normalized low- and high-frequency HRV. 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 1 Hz 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 1 Hz heart rate data displayed on standard NICU bedside monitors.
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Govindan et al. (2026) conducted a cohort in Extremely preterm infants at risk of cerebral palsy (n=102). Low heart rate variability (HRV) metrics vs. Higher heart rate variability was evaluated on Prediction of cerebral palsy (AUC of HRSD) (AUC 0.754, 95% CI 0.552-0.916, p=0.006). Low heart rate variability in the first week after birth, measured as HR standard deviation from 1 Hz monitor data, predicted a subsequent diagnosis of cerebral palsy with an AUC of 0.754.
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