Brain-Specific Serum Biomarkers Predict Neurological Morbidity in Diagnostically Diverse Pediatric Intensive Care Unit Patients

Exploratory factor analysis yields grouping of brain injury biomarkers significantly associated with outcomes in neonatal and pediatric ECMO

In this two-center prospective cohort study of children on ECMO, we assessed a panel of plasma brain injury biomarkers using exploratory factor analysis (EFA) to evaluate their interplay and association with outcomes. Biomarker concentrations were measured daily for the first 3 days of ECMO support in 95 participants. Unfavorable composite outcome was defined as in-hospital mortality or discharge Pediatric Cerebral Performance Category > 2 with decline ≥ 1 point from baseline. EFA grouped 11 biomarkers into three factors. Factor 1 comprised markers of cellular brain injury (NSE, BDNF, GFAP, S100β, MCP1, VILIP-1, neurogranin); Factor 2 comprised markers related to vascular processes (vWF, PDGFRβ, NPTX1); and Factor 3 comprised the BDNF/MMP-9 cellular pathway. Multivariable logistic models demonstrated that higher Factor 1 and 2 scores were associated with higher odds of unfavorable outcome (adjusted OR 2.88 [1.61, 5.66] and 1.89 [1.12, 3.43], respectively). Conversely, higher Factor 3 scores were associated with lower odds of unfavorable outcome (adjusted OR 0.54 [0.31, 0.88]), which is biologically plausible given the role of BDNF in neuroplasticity. Application of EFA on plasma brain injury biomarkers in children on ECMO yielded grouping of biomarkers into three factors that were significantly associated with unfavorable outcome, suggesting future potential as prognostic instruments.

High Variability in the Duration of Chest Compression Interruption is Associated With Poor Outcomes in Pediatric Extracorporeal Cardiopulmonary Resuscitation

OBJECTIVES

To determine the association between chest compression interruption (CCI) patterns and outcomes in pediatric patients undergoing extracorporeal cardiopulmonary resuscitation (ECPR).

DESIGN

Cardiopulmonary resuscitation (CPR) data were collected using defibrillator-electrode and bedside monitor waveforms from pediatric ECPR cases between 2013 and 2021. Duration and variability of CCI during cannulation for ECPR was determined and compared with survival to discharge using Fishers exact test and logistic regressions with cluster-robust se s for adjusted analyses.

SETTING

Quaternary care children's hospital.

PATIENTS

Pediatric patients undergoing ECPR.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Of 41 ECPR events, median age was 0.7 years (Q1, Q3: 0.1, 5.4), 37% (15/41) survived to hospital discharge with 73% (11/15) of survivors having a favorable neurologic outcome. Median duration of CPR from start of ECPR cannulation procedure to initiation of extracorporeal membrane oxygenation (ECMO) flow was 21 minutes (18, 30). Median duration of no-flow times associated with CCI during ECMO cannulation was 11 seconds (5, 28). Following planned adjustment for known confounders, survival to discharge was inversely associated with maximum duration of CCI (odds ratio [OR] 0.91 [0.86-0.95], p = 0.04) as well as the variability in the CCI duration (OR 0.96 [0.93-0.99], p = 0.04). Cases with both above-average CCI duration and higher CCI variability ( sd > 30 s) were associated with lowest survival (12% vs. 54%, p = 0.009). Interaction modeling suggests that lower variability in CCI is associated with improved survival, especially in cases where average CCI durations are higher.

CONCLUSIONS

Shorter duration of CCI and lower variability in CCI during cannulation for ECPR were associated with survival following refractory pediatric cardiac arrest.

Multimodal neuromonitoring in the pediatric intensive care unit

Neuromonitoring is used to assess the central nervous system in the intensive care unit. The purpose of neuromonitoring is to detect neurologic deterioration and intervene to prevent irreversible nervous system dysfunction. Neuromonitoring starts with the standard neurologic examination, which may lag behind the pathophysiologic changes. Additional modalities including continuous electroencephalography (CEEG), multiple physiologic parameters, and structural neuroimaging may detect changes earlier. Multimodal neuromonitoring now refers to an integrated combination and display of non-invasive and invasive modalities, permitting tailored treatment for the individual patient. This chapter reviews the non-invasive and invasive modalities used in pediatric neurocritical care.

Validation of a Clinical Tool to Predict Neurological Outcomes in Critically Ill Children-A Prospective Observational Study

OBJECTIVES

To evaluate the performance of the empiric tool by Gupta et al. in predicting neurological outcomes in children admitted to the pediatric intensive care unit (PICU) and to evaluate the association of biomarkers S100B and NSE with neurological outcomes.

METHODS

This prospective observational study was conducted in 163 critically ill children aged 2 mo to 17 y admitted to the PICU from June 2020 to July 2021. The authors used the prediction tool developed by Gupta et al.; the tool was applied at admission and at PICU discharge/death. Samples for NSE and S100B were collected at admission and discharge. The performance of the new tool was assessed through discrimination and calibration. Risk factors for "unfavorable outcomes" (decline in PCPC score by > 1) were evaluated by multivariate analysis.

RESULTS

The PICU mortality was 28% (n = 45). When the tool developed by Gupta et al. was used at the time of admission, favorable neurological outcomes were predicted for 69% (112) children. The area under the curve for the new tool at admission was 0.72 and at discharge/death it was 0.99, and the calibration was excellent at both time points. Independent factors associated with unfavorable neurological outcomes were higher PCPC scores and organ failure. As the number of samples processed for NSE and S100B was less, statistical analysis was not attempted.

CONCLUSIONS

The new tool by Gupta et al. has good discrimination, calibration, sensitivity, and specificity and can be used as a prediction tool. NSE and S100B are promising biomarkers and need further evaluation.

Interoperable and explainable machine learning models to predict morbidity and mortality in acute neurological injury in the pediatric intensive care unit: secondary analysis of the TOPICC study

Background

Acute neurological injury is a leading cause of permanent disability and death in the pediatric intensive care unit (PICU). No predictive model has been validated for critically ill children with acute neurological injury.

Objectives

We hypothesized that PICU patients with concern for acute neurological injury are at higher risk for morbidity and mortality, and advanced analytics would derive robust, explainable subgroup models.

Methods

We performed a secondary subgroup analysis of the Trichotomous Outcomes in Pediatric Critical Care (TOPICC) study (2011-2013), predicting mortality and morbidity from admission physiology (lab values and vital signs in 6 h surrounding admission). We analyzed patients with suspected acute neurological injury using standard machine learning algorithms. Feature importance was analyzed using SHapley Additive exPlanations (SHAP). We created a Fast Healthcare Interoperability Resources (FHIR) application to demonstrate potential for interoperability using pragmatic data.

Results

1,860 patients had suspected acute neurological injury at PICU admission, with higher morbidity (8.2 vs. 3.4%) and mortality (6.2 vs. 1.9%) than those without similar concern. The ensemble regressor (containing Random Forest, Gradient Boosting, and Support Vector Machine learners) produced the best model, with Area Under the Receiver Operating Characteristic Curve (AUROC) of 0.91 [95% CI (0.88, 0.94)] and Average Precision (AP) of 0.59 [0.51, 0.69] for mortality, and decreased performance predicting simultaneous mortality and morbidity (0.83 [0.80, 0.86] and 0.59 [0.51, 0.64]); at a set specificity of 0.995, positive predictive value (PPV) was 0.79 for mortality, and 0.88 for mortality and morbidity. By comparison, for mortality, the TOPICC logistic regression had AUROC of 0.90 [0.84, 0.93], but substantially inferior AP of 0.49 [0.35, 0.56] and PPV of 0.60 at specificity 0.995. Feature importance analysis showed that pupillary non-reactivity, Glasgow Coma Scale, and temperature were the most contributory vital signs, and acidosis and coagulopathy the most important laboratory values. The FHIR application provided a simulated demonstration of real-time health record query and model deployment.

Conclusions

PICU patients with suspected acute neurological injury have higher mortality and morbidity. Our machine learning approach independently identified previously-known causes of secondary brain injury. Advanced modeling achieves improved positive predictive value in this important population compared to published models, providing a stepping stone in the path to deploying explainable models as interoperable bedside decision-support tools.

Brain damage markers neuron-specific enolase (NSE) and S100B in serum in children with Lyme neuroborreliosis-detection and evaluation as prognostic biomarkers for clinical outcome

Lyme borreliosis (LB) is the most common tick-borne infection in Europe, with Lyme neuroborreliosis (LNB) its second most frequent clinical manifestation. Prognostic factors for clinical outcomes in LNB have not been identified. Elevated serum levels of the brain damage markers neuron-specific enolase (NSE) and S100 calcium-binding protein B (S100B) have been associated with poor clinical outcomes in other disorders of the central nervous system. The aim of this study is to assess NSE and S100B in serum as prognostic biomarkers for clinical outcomes in paediatric LNB patients. Children evaluated for LNB (n = 121) in Sweden were prospectively included during 2010–2014, serum samples were collected on admission, and all children underwent a 2-month follow-up. Patients with pleocytosis and anti-Borrelia antibodies in cerebrospinal fluid (CSF) were classified as having LNB (n = 61). Controls were age- and gender-matched non-LNB patients (n = 60). NSE was elevated in 38/61 (62%) LNB patients and in 31/60 (52%) controls. S100B was elevated in 3/60 (5%) LNB patients and 0/59 (0%) controls. NSE and S100B concentrations did not differ significantly when comparing LNB patients with controls. No differences were found in the concentrations when comparing the clinical recovery of LNB patients at the 2-month follow-up. NSE was detectable in the majority of LNB patients and controls, whereas S100B was detectable in only a few LNB patients and no controls. NSE and S100B in serum cannot be recommended as prognostic biomarkers for clinical outcomes in children with LNB.

Real-time seizure detection in paediatric intensive care patients: the RESET child brain protocol

INTRODUCTION

Approximately 20%-40% of comatose children with risk factors in intensive care have electrographic-only seizures; these go unrecognised due to the absence of continuous electroencephalography (EEG) monitoring (cEEG). Utility of cEEG with high-quality assessment is currently limited due to high-resource requirements. New software analysis tools are available to facilitate bedside cEEG assessment using quantitative EEG (QEEG) trends. The primary aim of this study is to describe accuracy of interpretation of QEEG trends by paediatric intensive care unit (PICU) nurses compared with cEEG assessment by neurologist (standard clinical care) in children at risk of seizures and status epilepticus utilising diagnostic test statistics. The secondary aims are to determine time to seizure detection for QEEG users compared with standard clinical care and describe impact of confounders on accuracy of seizure detection.

METHODS AND ANALYSIS

This will be a single-centre, prospective observational cohort study evaluating a paediatric QEEG programme utilising the full 19 electrode set. The setting will be a 36-bed quaternary PICU with medical, cardiac and general surgical cases. cEEG studies in PICU patients identified as 'at risk of seizures' will be analysed. Trained bedside clinical nurses will interpret the QEEG. Seizure events will be marked as seizures if >3 QEEG criteria occur. Post-hoc dedicated neurologists, who remain blinded to the QEEG analysis, will interpret the cEEG. Determination of standard test characteristics will assess the primary hypothesis. To calculate 95% (CIs) around the sensitivity and specificity estimates with a CI width of 10%, the sample size needed for sensitivity is 80 patients assuming each EEG will have approximately 9 to 18 1-hour epochs.

ETHICS AND DISSEMINATION

The study has received approval by the Children's Health Queensland Human Research Ethics Committee (HREC/19/QCHQ/58145). Results will be made available to the funders, critical care survivors and their caregivers, the relevant societies, and other researchers.

TRIAL REGISTRATION NUMBER

Australian New Zealand Clinical Trials Registry (ANZCTR) 12621001471875.

Serum levels of the cold stress hormones FGF21 and GDF-15 after cardiac arrest in infants and children enrolled in single center therapeutic hypothermia clinical trials

OBJECTIVE

Fibroblast Growth Factor 21 (FGF21) and Growth Differentiation Factor-15 (GDF-15) are putative neuroprotective cold stress hormones (CSHs) provoked by cold exposure that may be age-dependent. We sought to characterize serum FGF21 and GDF-15 levels in pediatric cardiac arrest (CA) patients and their association with use of therapeutic hypothermia (TH).

METHODS

Secondary analysis of serum samples from clinical trials. We measured FGF21 and GDF-15 levels in pediatric patients post-CA and compared levels to both pediatric intensive care (PICU) and healthy controls. Post-CA, we compared normothermia (NT) vs TH (33 °C for 72 h) treated cohorts at < 24 h, 24 h, 48 h, 72 h, and examined the change in CSHs over 72 h. We also assessed association between hospital mortality and initial levels.

RESULTS

We assessed 144 samples from 68 patients (27 CA [14 TH, 13 NT], 9 PICU and 32 healthy controls). Median initial FGF21 levels were higher post-CA vs. healthy controls (392 vs. 40 pg/mL, respectively, P < 0.001). Median GDF-15 levels were higher post-CA vs. healthy controls (7,089 vs. 396 pg/mL, respectively, P < 0.001). In the CA group, the median change in FGF21 from PICU day 1-3 (after 72 h of temperature control), was higher in TH vs. NT (231 vs. -20 pg/mL, respectively, P < 0.05), with no difference in GDF-15 over time. Serum GDF-15 levels were higher in CA patients that died vs. survived (19,450 vs. 5,337 pg/mL, respectively, P < 0.05), whereas serum FGF21 levels were not associated with mortality.

CONCLUSION

Serum levels of FGF21 and GDF-15 increased after pediatric CA, and FGF21 appears to be augmented by TH.

Neurological Complications Acquired During Pediatric Critical Illness: Exploratory "Mixed Graphical Modeling" Analysis Using Serum Biomarker Levels

OBJECTIVES

Neurologic complications, consisting of the acute development of a neurologic disorder, that is, not present at admission but develops during the course of illness, can be difficult to detect in the PICU due to sedation, neuromuscular blockade, and young age. We evaluated the direct relationships of serum biomarkers and clinical variables to the development of neurologic complications. Analysis was performed using mixed graphical models, a machine learning approach that allows inference of cause-effect associations from continuous and discrete data.

DESIGN

Secondary analysis of a previous prospective observational study.

SETTING

PICU, single quaternary-care center.

PATIENTS

Individuals admitted to the PICU, younger than18 years old, with intravascular access via an indwelling catheter.

INTERVENTIONS

None.

MEASUREMENTS

About 101 patients were included in this analysis. Serum (days 1-7) was analyzed for glial fibrillary acidic protein, ubiquitin C-terminal hydrolase-L1, and alpha-II spectrin breakdown product 150 utilizing enzyme-linked immunosorbent assays. Serum levels of neuron-specific enolase, myelin basic protein, and S100 calcium binding protein B used in these models were reported previously. Demographic data, use of selected clinical therapies, lengths of stay, and ancillary neurologic testing (head CT, brain MRI, and electroencephalogram) results were recorded. The Mixed Graphical Model-Fast-Causal Inference-Maximum algorithm was applied to the dataset.

MAIN RESULTS

About 13 of 101 patients developed a neurologic complication during their critical illness. The mixed graphical model identified peak levels of the neuronal biomarker neuron-specific enolase and ubiquitin C-terminal hydrolase-L1, and the astrocyte biomarker glial fibrillary acidic protein to be the direct causal determinants for the development of a neurologic complication; in contrast, clinical variables including age, sex, length of stay, and primary neurologic diagnosis were not direct causal determinants.

CONCLUSIONS

Graphical models that include biomarkers in addition to clinical data are promising methods to evaluate direct relationships in the development of neurologic complications in critically ill children. Future work is required to validate and refine these models further, to determine if they can be used to predict which patients are at risk for/or with early neurologic complications.

Diffuse Axonal Injury Grade on Early MRI is Associated with Worse Outcome in Children with Moderate-Severe Traumatic Brain Injury

Background

Traumatic brain injury (TBI) is the leading cause of death and disability in children, but effective tools for predicting outcome remain elusive. Although many pediatric patients receive early magnetic resonance imaging (MRI), data on its utility in prognostication are lacking. Diffuse axonal injury (DAI) is a hallmark of TBI detected on early MRI and was shown previously to improve prognostication in adult patients with TBI. In this exploratory study, we investigated whether DAI grade correlates with functional outcome and improves prognostic accuracy when combined with core clinical variables and computed tomography (CT) biomarkers in pediatric patients with moderate-severe TBI (msTBI).

Methods

Pediatric patients (≤ 19 years) who were admitted to two regional level one trauma centers with a diagnosis of msTBI (Glasgow Coma Scale [GCS] score < 13) between 2011 and 2019 were identified through retrospective chart review. Patients who underwent brain MRI within 30 days of injury and had documented clinical follow-up after discharge were included. Age, pupil reactivity, and initial motor GCS score were collected as part of the International Mission for Prognosis and Analysis of Clinical Trials in TBI (IMPACT) model. Imaging was reviewed to calculate the Rotterdam score (CT) and DAI grade (MRI) and to evaluate for presence of hypoxic-ischemic injury (MRI). The primary outcome measure was the Pediatric Cerebral Performance Category Scale (PCPCS) score at 6 months after TBI, with favorable outcome defined as PCPCS scores 1–3 and unfavorable outcome defined as PCPCS scores 4–6. The secondary outcome measure was discharge disposition to home versus to an inpatient rehabilitation facility.

Result

Of 55 patients included in the study, 45 (82%) had severe TBI. The most common mechanism of injury was motor vehicle collision (71%). Initial head CT scans showed acute hemorrhage in 84% of patients. MRI was acquired a median of 5 days after injury, and hemorrhagic DAI lesions were detected in 87% of patients. Each 1-point increase in DAI grade increased the odds of unfavorable functional outcome by 2.4-fold. When controlling for core IMPACT clinical variables, neither the DAI grade nor the Rotterdam score was independently correlated with outcome and neither significantly improved outcome prediction over the IMPACT model alone.

Conclusions

A higher DAI grade on early MRI is associated with worse 6-month functional outcome and with discharge to inpatient rehabilitation in children with acute msTBI in a univariate analysis but does not independently correlate with outcome when controlling for the GCS score. Addition of the DAI grade to the core IMPACT model does not significantly improve prediction of poor neurological outcome. Further study is needed to elucidate the utility of early MRI in children with msTBI.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12028-021-01336-8.

Blood Biomarkers for Detection of Brain Injury in COVID-19 Patients

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus attacks multiple organs of coronavirus disease 2019 (COVID-19) patients, including the brain. There are worldwide descriptions of neurological deficits in COVID-19 patients. Central nervous system (CNS) symptoms can be present early in the course of the disease. As many as 55% of hospitalized COVID-19 patients have been reported to have neurological disturbances three months after infection by SARS-CoV-2. The mutability of the SARS-COV-2 virus and its potential to directly affect the CNS highlight the urgency of developing technology to diagnose, manage, and treat brain injury in COVID-19 patients. The pathobiology of CNS infection by SARS-CoV-2 and the associated neurological sequelae of this infection remain poorly understood. In this review, we outline the rationale for the use of blood biomarkers (BBs) for diagnosis of brain injury in COVID-19 patients, the research needed to incorporate their use into clinical practice, and the improvements in patient management and outcomes that can result. BBs of brain injury could potentially provide tools for detection of brain injury in COVID-19 patients. Elevations of BBs have been reported in cerebrospinal fluid (CSF) and blood of COVID-19 patients. BB proteins have been analyzed in CSF to detect CNS involvement in patients with infectious diseases, including human immunodeficiency virus and tuberculous meningitis. BBs are approved by the U.S. Food and Drug Administration for diagnosis of mild versus moderate traumatic brain injury and have identified brain injury after stroke, cardiac arrest, hypoxia, and epilepsy. BBs, integrated with other diagnostic tools, could enhance understanding of viral mechanisms of brain injury, predict severity of neurological deficits, guide triage of patients and assignment to appropriate medical pathways, and assess efficacy of therapeutic interventions in COVID-19 patients.

Potential Neurodevelopmental Effects of Pediatric Intensive Care Sedation and Analgesia: Repetitive Benzodiazepine and Opioid Exposure Alters Expression of Glial and Synaptic Proteins in Juvenile Rats

Sedatives are suspected contributors to neurologic dysfunction in PICU patients, to whom they are administered during sensitive neurodevelopment. Relevant preclinical modeling has largely used comparatively brief anesthesia in infant age-approximate animals, with insufficient study of repetitive combined drug administration during childhood. We hypothesized that childhood neurodevelopment is selectively vulnerable to repeated treatment with benzodiazepine and opioid. We report a preclinical model of combined midazolam and morphine in early childhood age-approximate rats.

Intérêt clinique des concentrations sériques de la protéine S100β dans l’évaluation des patients traumatisés crâniens

Les recommandations de la Société française de médecine d’urgence concernant la prise en charge des patients traumatisés crâniens légers ont été éditées en 2012, complétées par des recommandations sur la bonne utilisation du biomarqueur S100β deux ans plus tard. Grâce à son excellente valeur prédictive négative, la protéine S100β utilisée à travers des règles strictes de prescription a été définie comme une alternative solide à la tomodensitométrie. Cependant, plusieurs questions restent en suspens concernant le délai maximum de réalisation du prélèvement par rapport à l’heure du traumatisme, l’impact médicoéconomique, les variations en rapport avec l’âge du patient, l’impact des agents anticoagulants ou antiagrégants plaquettaires et l’utilité du dosage sérique de cette protéine dans d’autres cadres nosologiques.