Quantitative Modeling of External Ventricular Drain Output to Predict Shunt Dependency in Aneurysmal Subarachnoid Hemorrhage: Cohort Study

Abstract

Background: Acute hydrocephalus is a common complication of aneurysmal subarachnoid hemorrhage (aSAH); however, attempts to predict shunt-dependent chronic hydrocephalus using clinical parameters have been equivocal.

Methods: Cohort study of aSAH is treated with external ventricular drainage (EVD) placement at our institution, 2001-2016, via logistic regression. EVD-related parameters included mean/total EVD output (days 0-2), EVD days, EVD days ≤ 5 mmHg, and wean/clamp fails. aSAH outcomes assessed included ventriculoperitoneal shunt (VPS) placement, delayed cerebral ischemia (DCI), radiographic infarction (RI), symptomatic vasospasm (SV), age, and aSAH grades.

Results: Two hundred and ten aSAH patients underwent EVD treatment for a median 12 days (range 1-54); 85 required VPS (40%). On univariate analysis, EVD output, total EVD days, EVD days ≤ 5 mmHg, and wean/clamp trial failures were significantly associated with VPS placement (p < 0.01 for all parameters). No EVD output parameter demonstrated a significant association with DCI, RI, or SV. On multivariate analysis, EVD output was a significant predictor of VPS placement, after adjusting for age and clinical and radiological grades; the optimal threshold for predicting VPS placement was mean daily output > 204 ml on days 0-2 (OR 2.59, 95% CI 1.31-5.07). Multiple wean failures were associated with unfavorable functional outcome, after adjusting for age, grade, and VPS placement (OR 1.65, 95% CI 1.10-2.47). We developed a score incorporating age, grade and EVD parameters (MAGE) for predicting VPS placement after aSAH.

Conclusions: EVD output parameters and wean/clamp trial failures predicted shunt dependence in an age- and grade-adjusted multivariable model. Early VPS placement may be warranted in patients with MAGE score ≥ 4, particularly following 2 failed wean trials.

Keywords: External ventricular drain; Hydrocephalus; Logistic regression; MAGE; Predictive modeling; Subarachnoid hemorrhage.