OBJECTIVE
The goal of this study was to investigate and identify the predictors associated with the incidence of hydrocephalus requiring shunt insertion in patients with encephalocele (EC), and to develop a scoring system to estimate the probability of hydrocephalus occurrence over time in these patients.
METHODS
A retrospective analysis was undertaken on data from patients treated for EC at a tertiary medical center between 2010 and 2021. Data including patient age at presentation, sex, sac location, sac size, contents, presence of ventriculomegaly/hydrocephalus, CSF leakage, and other associated intracranial/extracranial anomalies were among the variables evaluated for their predictive value. In addition, logistic regression analyses were performed to identify the independent predictors. A predictive scoring system was developed based on regression coefficients.
RESULTS
A total of 102 cases of EC were identified. The patient group consisted of 52 boys and 50 girls. Seventy-one patients (69.6%) had posterior ECs. Forty-three (42.2%) of the ECs contained neural tissue. Thirty-three patients presented with ventriculomegaly (32.4%), 30 of whom (90.9%) underwent ventriculoperitoneal shunt placement for hydrocephalus. Multivariate analysis revealed that the presence of other associated anomalies (OR 2.8, 95% CI 1.1–7.4, p = 0.027), larger EC sac size (OR 1.3, 95% CI 1.01–1.6, p = 0.042), and infections (OR 6.8, 95% CI 1.3–34.8, p = 0.034) were associated with ventriculomegaly. The logistic regression model consisted of 5 variables including the patients’ history of meningitis, their sex, sac location, sac size, and presence of other other associated anomalies; analysis resulted in the maximum accuracy of 86% for the prediction of hydrocephalus occurrence.
CONCLUSIONS
According to the findings, the presence of other associated anomalies, a larger sac, and infections are significant independent predictors of hydrocephalus. By considering these 3 predictors as well as sac location and the patient’s sex, it will be possible to predict hydrocephalus occurrence in patients with EC with significant accuracy.