Clinical Features and a Prediction Nomogram for Prognosis in Children with Escherichia coli Meningitis

Abstract

Background We aimed to build a prediction nomogram for early prediction of poor prognosis in children with Escherichia coli meningitis and analyzed the course of treatment and discharge criteria. Methods Eighty-seven pediatric patients with E coli meningitis were retrospectively recruited from the Children's Hospital of Chongqing Medical University between June 2012 and November 2021. Univariate analysis and binary logistic analysis were used to evaluate the risk factors, and the prediction model was built. Results E coli meningitis is more common in children <3 months old in our study (86.2%). Common complications were subdural effusion (39.1%), followed by hydrocephalus (13.8%) and repeated convulsions (12.6%). The mortality rate and sequelae rate of E coli meningitis in children was ∼10.9% and ∼6.3%, respectively. Univariate analysis showed that 13 clinical indicators were associated with poor prognosis of E coli meningitis in children. In binary logistic analysis, risk factors were seizures ( P = .032) and the last cerebrospinal fluid glucose content before discharge ( P = .002). A graphical nomogram was designed. The area under the receiver operating characteristic curve was 0.913. The Hosmer-Lemeshow test showed that the model was a good fit ( P = .648). Internal validation proved the reliability of the prediction nomogram. Conclusions E coli meningitis is more common in children <3 months old in our study. The rate of complications and sequelae are high. The prediction nomogram could be used to assess the risk of poor prognosis in children with E coli meningitis by clinicians.