Quantitative pupillometry as a sensitive tool for detecting hydrocephalus-related physiologic burden after aSAH: a prospective feasibility study

Hydrocephalus after aneurysmal subarachnoid hemorrhage (aSAH) is common, but bedside markers of its physiological burden are limited. Quantitative pupillometry (QP) is objective and fast; whether it mirrors hydrocephalus severity is uncertain. Single-center cohort of adults with aSAH undergoing ventriculoperitoneal shunting (n = 17). Automated infrared pupillometry (NPi-200) was performed the day before surgery and on post-op day 1, recording Neurological Pupil index (NPi) and constriction/dilation velocities (CV/DV) as overall values (mean of both eyes) and inter-eye asymmetry (|OD–OS|). Pre-op CT markers were combined into a standardized Hydrocephalus Severity Score (HSS; higher=worse). Mean pre-op NPi was 3.81 ± 0.69 and post-op 4.03 ± 0.66; median ΔNPi = + 0.13 (Wilcoxon p = 0.141). Responders (ΔNPi ≥ + 0.5) were 5/14 (35.7%). Cross-sectionally, overall values did not mirror ventricular size: NPi vs. HSS (ρ = 0.37, p = 0.141, q = 0.423) and NPi vs. Evans index (EI) (ρ = 0.09, p = 0.735, q = 0.735) were non-significant; CV/DV vs. HSS were likewise neutral. In contrast, inter-eye CV asymmetry correlated with HSS (ρ = 0.68, p = 0.006, q = 0.017; n = 16) and trended with Evans (ρ = 0.49, p = 0.054, q = 0.161). In age/sex-adjusted models, no radiologic metric, including HSS, reliably explained pathological NPi (< 3). In shunt-dependent aSAH hydrocephalus, pattern matters more than absolute value. Absolute NPi and mean velocities did not reflect ventricular size, whereas inter-eye constriction-velocity asymmetry captured composite radiologic burden, consistent with lateralized parasympathetic stress. Around shunt placement, QP behaved as a dynamic biomarker, revealing patient-level gains despite flat cohort averages. Findings support trend- and asymmetry-based pupillometry to complement imaging for CSF-pathway reassessment and early post-shunt surveillance, warranting prospective validation.