Perspective on Cerebral Autoregulation Monitoring in Neonatal Cardiac Surgery Requiring Cardiopulmonary Bypass

Cerebral autoregulation monitoring using the cerebral oximetry index after neonatal cardiac surgery: A single-center retrospective cohort study

OBJECTIVE

To investigate whether cerebral autoregulation is impaired after neonatal cardiac surgery and whether changes in autoregulation metrics are associated with different congenital heart defects or the incidence of postoperative neurologic events.

METHODS

This is a retrospective observational study of neonates undergoing monitoring during the first 72 hours after cardiac surgery. Archived data were processed to calculate the cerebral oximetry index (COx) and derived metrics. Acute neurologic events were identified by an electronic medical record review. The Skillings-Mack test and the Wilcoxon signed-rank test were used to analyze the evolution of autoregulation metrics over time; the Mann-Whitney U test was used for comparison between groups.

RESULTS

We included 28 neonates, 7 (25%) with hypoplastic left heart syndrome and 21 (75%) with transposition of the great arteries. Overall, the median percentage of time spent with impaired autoregulation, defined as percentage of time with a COx >0.3, was 31.6% (interquartile range, 21.1%-38.3%). No differences in autoregulation metrics between different cardiac defects subgroups were observed. Seven patients (25%) experienced a postoperative acute neurologic event. Compared to the neonates without an acute neurologic event, those with an acute neurologic event had a higher COx (0.16 vs 0.07; P = .035), a higher percentage of time with a COx >0.3 (39.4% vs 29.2%; P = .017), and a higher percentage of time with a mean arterial pressure below the lower limit of autoregulation (13.3% vs 6.9%; P = .048).

CONCLUSIONS

COx monitoring after cardiac surgery allowed for the detection of impaired cerebral autoregulation, which was more frequent in neonates with postoperative acute neurologic events.

Advances in pediatric neuroanesthesia practices

The field of pediatric neuroanesthesia has evolved with concurrent changes in pediatric neurosurgical practice. Ongoing pediatric neuroanesthesia investigations provide novel insights into developmental cerebrovascular physiology, neurosurgical technology, and clinical outcomes. Minimally invasive neurosurgical procedures appear to be associated with lower complication rates and length of stay. This review will discuss blood sparing techniques, regional anesthesia, and postoperative disposition. Collectively, these innovations appear to be safe in pediatric neurosurgical patients with potential benefits, but more data is needed for more definitive long-term outcomes.

Determining Optimal Mean Arterial Blood Pressure Based on Cerebral Autoregulation in Children after Cardiac Surgery

To evaluate the feasibility of continuous determination of the optimal mean arterial blood pressure (opt-MAP) according to cerebral autoregulation and to describe the opt-MAP, the autoregulation limits, and the time spent outside these limits in children within 48 h of cardiac surgery. Cerebral autoregulation was assessed using the correlation coefficient (COx) between cerebral oxygenation and MAP in children following cardiac surgery. Plots depicting the COx according to the MAP were used to determine the opt-MAP using weighted multiple time windows. For each patient, we estimated (1) the time spent with MAP outside the autoregulation limits and (2) the burden of deviation, defined as the area between the MAP curve and the autoregulation limits when the MAP was outside these limits. Fifty-one patients with a median age of 7.1 (IQR 0.7-52.0) months old were included. The opt-MAP was calculated for 94% (IQR 90-96) of the monitored time. The opt-MAP was significantly lower in neonates < 1 month old. The patients spent 24% (18-31) of the time outside of the autoregulation limits, with no significant differences between age groups. Continuous determination of the opt-MAP is feasible in children within the first 48 h following cardiac surgery.

Predicting Cardiac Arrest in Children with Heart Disease: A Novel Machine Learning Algorithm

BACKGROUND

Children with congenital and acquired heart disease are at a higher risk of cardiac arrest compared to those without heart disease. Although the monitoring of cardiopulmonary resuscitation quality and extracorporeal resuscitation technologies have advanced, survival after cardiac arrest in this population has not improved. Cardiac arrest prevention, using predictive algorithms with machine learning, has the potential to reduce cardiac arrest rates. However, few studies have evaluated the use of these algorithms in predicting cardiac arrest in children with heart disease.

METHODS

We collected demographic, laboratory, and vital sign information from the electronic health records (EHR) of all the patients that were admitted to a single-center pediatric cardiac intensive care unit (CICU), between 2010 and 2019, who had a cardiac arrest during their CICU admission, as well as a comparator group of randomly selected non-cardiac-arrest controls. We compared traditional logistic regression modeling against a novel adaptation of a machine learning algorithm (functional gradient boosting), using time series data to predict the risk of cardiac arrest.

RESULTS

A total of 160 unique cardiac arrest events were matched to non-cardiac-arrest time periods. Using 11 different variables (vital signs and laboratory values) from the EHR, our algorithm's peak performance for the prediction of cardiac arrest was at one hour prior to the cardiac arrest (AUROC of 0.85 [0.79,0.90]), a performance that was similar to our previously published multivariable logistic regression model.

CONCLUSIONS

Our novel machine learning predictive algorithm, which was developed using retrospective data that were collected from the EHR and predicted cardiac arrest in the children that were admitted to a single-center pediatric cardiac intensive care unit, demonstrated a performance that was similar to that of a traditional logistic regression model. While these results are encouraging, future research, including prospective validations with multicenter data, is warranted prior to the implementation of this algorithm as a real-time clinical decision support tool.

Declining Incidence of Postoperative Neonatal Brain Injury in Congenital Heart Disease

BACKGROUND

Brain injury is common in neonates with complex neonatal congenital heart disease (CHD) and affects neurodevelopmental outcomes.

OBJECTIVES

Given advancements in perioperative care, we sought to determine if the rate of preoperative and postoperative brain injury detected by using brain magnetic resonance imaging (MRI) and associated clinical risk factors have changed over time in complex CHD.

METHODS

A total of 270 term newborns with complex CHD were prospectively enrolled for preoperative and postoperative brain MRIs between 2001 and 2021 with a total of 466 MRI scans. Brain injuries in the form of white matter injury (WMI) or focal stroke and clinical factors were compared across 4 epochs of 5-year intervals with logistic regression.

RESULTS

Rates of preoperative WMI and stroke did not change over time. After adjusting for timing of the postoperative MRI, site, and cardiac group, the odds of newly acquired postoperative WMI were significantly lower in Epoch 4 compared with Epoch 1 (OR: 0.29; 95% CI: 0.09-1.00; P = 0.05). The adjusted probability of postoperative WMI declined significantly by 18.7% from Epoch 1 (24%) to Epoch 4 (6%). Among clinical risk factors, lowest systolic, mean, and diastolic blood pressures in the first 24 hours after surgery were significantly higher in the most recent epoch.

CONCLUSIONS

The prevalence of postoperative WMI has declined, whereas preoperative WMI rates remain constant. More robust postoperative blood pressures may explain these findings by minimizing periods of ischemia and supporting cerebral perfusion. These results suggest potential modifiable clinical targets in the postoperative time period to minimize the burden of WMI.

The brain in pediatric critical care: unique aspects of assessment, monitoring, investigations, and follow-up

As survival after pediatric intensive care unit (PICU) admission has improved over recent years, a key focus now is the reduction of morbidities and optimization of quality of life for survivors. Neurologic disorders and direct brain injuries are the reason for 11-16% of admissions to PICU. In addition, many critically ill children are at heightened risk of brain injury and neurodevelopmental difficulties affecting later life, e.g., complex heart disease and premature birth. Hence, assessment, monitoring and protection of the brain, using fundamental principles of neurocritical care, are crucial to the practice of pediatric intensive care medicine. The assessment of brain function, necessary to direct appropriate care, is uniquely challenging amongst children admitted to the PICU. Challenges in assessment arise in children who are unstable, or pharmacologically sedated and muscle relaxed, or who have premorbid abnormality in development. Moreover, the heterogeneity of diseases and ages in PICU patients, means that high caliber evidence is harder to accrue than in adult practice, nonetheless, great progress has been made over recent years. In this 'state of the art' paper about critically ill children, we discuss (1) patient types at risk of brain injury, (2) new standardized clinical assessment tools for age-appropriate, clinical evaluation of brain function, (3) latest evidence related to cranial imaging, non-invasive and invasive monitoring of the brain, (4) the concept of childhood 'post intensive are syndrome' and approaches for neurodevelopmental follow-up. Better understanding of these concepts is vital for taking PICU survivorship to the next level.

Cerebral Blood Flow Monitoring in High-Risk Fetal and Neonatal Populations

Cerebrovascular pressure autoregulation promotes stable cerebral blood flow (CBF) across a range of arterial blood pressures. Cerebral autoregulation (CA) is a developmental process that reaches maturity around term gestation and can be monitored prenatally with both Doppler ultrasound and magnetic resonance imaging (MRI) techniques. Postnatally, there are key advantages and limitations to assessing CA with Doppler ultrasound, MRI, and near-infrared spectroscopy. Here we review these CBF monitoring techniques as well as their application to both fetal and neonatal populations at risk of perturbations in CBF. Specifically, we discuss CBF monitoring in fetuses with intrauterine growth restriction, anemia, congenital heart disease, neonates born preterm and those with hypoxic-ischemic encephalopathy. We conclude the review with insights into the future directions in this field with an emphasis on collaborative science and precision medicine approaches.