Low Variability of Blood Pressure Predicts Abnormal Electroencephalogram in Infants with Hypoxic Ischemic Encephalopathy

Abstract

Objective: This study aimed to evaluate the role of an objective physiologic biomarker, arterial blood pressure variability, for the early identification of adverse short-term electroencephalogram (EEG) outcomes in infants with hypoxic-ischemic encephalopathy (HIE).

Study design: In this multicenter observational study, we analyzed blood pressure of infants meeting these criteria: (1) neonatal encephalopathy determined by modified Sarnat exam, (2) continuous mean arterial blood pressure (MABP) data between 18 and 27 hours after birth, and (3) continuous EEG performed for at least 48 hours. Adverse outcome was defined as moderate-severe grade EEG at 48 hours. Standardized signal preprocessing was used; the power spectral density was computed without interpolation. Multivariate binary logistic regression was used to identify which MABP time and frequency domain metrics provided improved predictive power for adverse outcomes compared with standard clinical predictors (5-minute Apgar score and cord pH) using receiver operator characteristic analysis.

Results: Ninety-one infants met inclusion criteria. The mean gestational age was 38.4 ± 1.8 weeks, the mean birth weight was 3,260 ± 591 g, 52/91 (57%) of infants were males, the mean cord pH was 6.95 ± 0.21, and 10/91 (11%) of infants died. At 48 hours, 58% of infants had normal or mildly abnormal EEG background and 42% had moderate or severe EEG backgrounds. Clinical predictor variables (10-minute Apgar score, Sarnat stage, and cord pH) were modestly predictive of 48 hours EEG outcome with area under curve (AUC) of 0.66 to 0.68. A composite model of clinical and optimal time- and frequency-domain blood pressure variability had a substantially improved AUC of 0.86.

Conclusion: Time- and frequency-domain blood pressure variability biomarkers offer a substantial improvement in prediction of later adverse EEG outcomes over perinatal clinical variables in a two-center cohort of infants with HIE.

Key points: · Early outcome prediction in HIE is suboptimal.. · Patterns in blood pressure physiology may be predictive of short-term outcomes.. · Early time- and frequency-domain measures of blood pressure variability predict short-term EEG outcomes in HIE infants better than perinatal factors alone..

Figure 1 –

Time series plot of MABP for infant with good outcome (top left) and adverse outcome (bottom left). The corresponding SD of the 1^st difference of the MABP is shown to the right of each recording.

Figure 2 -

Sequential data cleaning. Top panel is the raw signal, middle panel is the signal after removal of data violating “clinical rules,” bottom panel is the signal after additional cleaning using multithresholding rule.

Figure 3 –

Strength of prediction (measured by AUC) of the standard deviation of the first difference of the MABP over time.

Figure 4 -

Change in relative risk of adverse 48-hour EEG for change in time, frequency, or composite metric.

Figure 5 -

Plot of hourly mean MABP, grouped by 48h EEG outcome.