Validation of a Clinical Tool to Predict Neurological Outcomes in Critically Ill Children

A new study evaluated the performance of the empiric prediction tool developed by Gupta et al. in predicting neurological outcomes in critically ill children and to evaluate the association of biomarkers S100B and neuron-specific enolase (NSE) with neurological outcomes.

This prospective, observational study enrolled 163 critically ill children aged 2 months to 17 years admitted to the pediatric intensive care unit (PICU) from June 2020 to July 2021. The prediction tool was applied at admission and at PICU discharge/death. Biomarkers S100B and NSE were assessed for their association with neurological outcomes.

The results showed that the PICU mortality rate was 28%, and the Gupta et al. tool predicted favorable neurological outcomes for 69% of the children at admission – with an area under the curve (AUC) of 0.72. At discharge/death, the tool exhibited an AUC of 0.99 – indicating excellent calibration. Higher PCPC scores and organ failure were identified as independent factors associated with unfavorable neurological outcomes.

While the sample size for NSE and S100B analyses were limited, the study concludes that Gupta et al.'s tool demonstrates good discrimination, calibration, sensitivity, and specificity, making it a valuable prediction tool. Additionally, biomarkers S100B and NSE show promise and warrant further evaluation.

Source: Bhadani KH, Sankar J, Datta SK, Tungal S, Jat KR, Kabra SK, Lodha R. Indian Journal of Pediatrics. 2024 Jan;91(1):10-6.