Underpowered and Too Heterogenous: A Humbling Assessment of the Literature Supporting Neuroprognostication After Pediatric Cardiac Arrest

Accuracy of Early Neuroprognostication in Pediatric Severe Traumatic Brain Injury

BACKGROUND

Children with severe traumatic brain injury (sTBI) are at risk for neurological sequelae impacting function. Clinicians are tasked with neuroprognostication to assist in decision-making. We describe a single-center study assessing clinicians' neuroprognostication accuracy.

METHODS

Clinicians of various specialties caring for children with sTBI were asked to predict their patients' functioning three to six months postinjury. Clinicians were asked to participate in the study if their patient had survived but not returned to baseline between day 4 and 7 postinjury. The outcome tool utilized was the functional status scale (FSS), ranging from 6 to 30 (best-worst function). Predicted scores were compared with actual scores three to six months postinjury. Lin concordance correlation coefficients were used to estimate agreement between predicted and actual FSS. Outcome was dichotomized as good (FSS 6 to 8) or poor (FSS ≥9). Positive and negative predictive values for poor outcome were calculated. Pessimistic prognostic prediction was defined as predicted worse outcome by ≥3 FSS points. Demographic and clinical variables were collected.

RESULTS

A total of 107 surveys were collected on 24 patients. Two children died. Fifteen children had complete (FSS = 6) or near-complete (FSS = 7) recovery. Mean predicted and actual FSS scores were 10.8 (S.D. 5.6) and 8.6 (S.D. 4.1), respectively. Predicted FSS scores were higher than actual scores (P < 0.001). Eight children had collective pessimistic prognostic prediction.

CONCLUSIONS

Clinicians predicted worse functional outcomes, despite high percentage of patients with near-normal function at follow-up clinic. Certain patient and provider factors were noted to impact accuracy and need to be studied in larger cohorts.

Use of Magnetic Resonance Imaging in Neuroprognostication After Pediatric Cardiac Arrest: Survey of Current Practices

BACKGROUND

Use of magnetic resonance imaging (MRI) as a tool to aid in neuroprognostication after cardiac arrest (CA) has been described, yet details of specific indications, timing, and sequences are unknown. We aim to define the current practices in use of brain MRI in prognostication after pediatric CA.

METHODS

A survey was distributed to pediatric institutions participating in three international studies. Survey questions related to center demographics, clinical practice patterns of MRI after CA, neuroimaging resources, and details regarding MRI decision support.

RESULTS

Response rate was 31% (44 of 143). Thirty-four percent (15 of 44) of centers have a clinical pathway informing the use of MRI after CA. Fifty percent (22 of 44) of respondents reported that an MRI is obtained in nearly all patients with CA, and 32% (14 of 44) obtain an MRI in those who do not return to baseline neurological status. Poor neurological examination was reported as the most common factor (91% [40 of 44]) determining the timing of the MRI. Conventional sequences (T1, T2, fluid-attenuated inversion recovery, and diffusion-weighted imaging/apparent diffusion coefficient) are routinely used at greater than 97% of centers. Use of advanced imaging techniques (magnetic resonance spectroscopy, diffusion tensor imaging, and functional MRI) were reported by less than half of centers.

CONCLUSIONS

Conventional brain MRI is a common practice for prognostication after CA. Advanced imaging techniques are used infrequently. The lack of standardized clinical pathways and variability in reported practices support a need for higher-quality evidence regarding the indications, timing, and acquisition protocols of clinical MRI studies.

Multimodal monitoring including early EEG improves stratification of brain injury severity after pediatric cardiac arrest

AIMS

Assessment of brain injury severity early after cardiac arrest (CA) may guide therapeutic interventions and help clinicians counsel families regarding neurologic prognosis. We aimed to determine whether adding EEG features to predictive models including clinical variables and examination signs increased the accuracy of short-term neurobehavioral outcome prediction.

METHODS

This was a prospective, observational, single-center study of consecutive infants and children resuscitated from CA. Standardized EEG scoring was performed by an electroencephalographer for the initial EEG timepoint after return of spontaneous circulation (ROSC) and each 12-h segment from the time of ROSC up to 48 h. EEG Background Category was scored as: (1) normal; (2) slow-disorganized; (3) discontinuous or burst-suppression; or (4) attenuated-featureless. The primary outcome was neurobehavioral outcome at discharge from the Pediatric Intensive Care Unit. To develop the final predictive model, we compared areas under the receiver operating characteristic curves (AUROC) from models with varying combinations of Demographic/Arrest Variables, Examination Signs, and EEG Features.

RESULTS

We evaluated 89 infants and children. Initial EEG Background Category was normal in 9 subjects (10%), slow-disorganized in 44 (49%), discontinuous or burst suppression in 22 (25%), and attenuated-featureless in 14 (16%). The final model included Demographic/Arrest Variables (witnessed status, doses of epinephrine, initial lactate after ROSC) and EEG Background Category which achieved AUROC of 0.9 for unfavorable neurobehavioral outcome and 0.83 for mortality.

CONCLUSIONS

The addition of standardized EEG Background Categories to readily available CA variables significantly improved early stratification of brain injury severity after pediatric CA.