Prognostic factor identification and model construction in pediatric influenza-associated encephalopathy: A...

Area of Science:

• Pediatric Neurology
• Infectious Diseases
• Biomarkers Research

Background:

• Infectious encephalopathy (IAE) poses a significant risk for poor outcomes in children.
• Identifying early diagnostic and prognostic indicators for IAE is essential for timely intervention.

Purpose of the Study:

• To identify risk factors associated with poor outcomes in pediatric IAE.
• To develop a predictive model for stratifying patients based on outcome severity.

Main Methods:

• Retrospective collection of clinical, laboratory, imaging, and treatment data from pediatric IAE patients.
• Univariate and survival analyses to identify prognostic factors.
• Development of a predictive model using key biomarkers.

Main Results:

• 16 out of 42 children (38.1%) experienced poor outcomes, including 6 deaths (14.3%).
• Poor outcomes correlated with deep coma, structural brain damage on MRI, and EEG abnormalities.
• Elevated CSF IL-10, CSF pro, blood ALT, AST, CK-MB, and LDL-H were significant discriminators.
• AST and CK-MB showed strong predictive value, with CK-MB being an independent mortality risk factor.

Conclusions:

• Elevated biomarkers (CSF IL-10, CSF pro, AST, ALT, CK-MB, LDL-H) at admission are linked to poor outcomes in pediatric IAE.
• Specific cutoffs for AST (≥132 IU/L) and CK-MB (≥136 IU/L) can serve as early warning indicators for severe outcomes.
• Timely recognition and intervention are critical for high-risk pediatric IAE patients.