Clinical characteristics, risk factors, and prognostic modeling for poor outcomes in children with influenza-associated encephalopathy: A retrospective cohort study.

Influenza-associated encephalopathy (IAE) in children is a rare but severe complication associated with high morbidity and mortality. Timely identification of high-risk cases remains challenging due to variable clinical presentations and limited pediatric-specific evidence. This retrospective cohort study included 198 children diagnosed with IAE between 2015 and 2022 in a pediatric intensive care unit. Patients were categorized by in-hospital prognosis, defined as either poor (including death, coma, or neurological sequelae at discharge) or favorable outcome. Clinical and laboratory parameters were compared between groups. Logistic regression identified independent risk factors, which were used to construct a prognostic model and corresponding nomogram. Discriminatory performance was evaluated using receiver operating characteristic analysis. Among the 198 patients (median age 26 months), 88 (44.4%) met criteria for poor prognosis. These included death (21.6%) and sequelae such as cognitive impairment (23.9%), motor dysfunction (20.5%), and epilepsy (15.9%). Poor outcome was significantly associated with lower Glasgow Coma Scale scores (median 7 vs 12, P < .001), cranial magnetic resonance imaging abnormalities (71.6% vs 39.1%, P < .001), acute respiratory distress syndrome, hyperglycemia, and elevated brain natriuretic peptide levels. Multivariable logistic regression identified 5 independent predictors: Glasgow Coma Scale ≤ 8 (adjusted odds ratio [aOR] 3.42, 95% confidence interval [CI]: 1.76-6.64), abnormal magnetic resonance imaging (aOR 3.25, 95% CI: 1.59-6.67), acute respiratory distress syndrome (aOR 2.92, 95% CI: 1.46-5.85), glucose > 8.3 mmol/L (aOR 2.51, 95% CI: 1.23-5.12), and brain natriuretic peptide > 100 pg/mL (aOR 1.98, 95% CI: 0.96-4.12). The model showed strong predictive performance (area under the curve = 0.84, sensitivity of 82.3%, and specificity of 88.2% at the optimal cutoff value). Among children with IAE, nearly half experienced poor in-hospital outcomes. A combination of neurological severity, radiologic findings, respiratory status, and metabolic derangements independently predicted prognosis. These findings may aid early risk stratification and clinical decision-making in pediatric critical care.