RESUMO
BACKGROUND: Management after cerebral arteriovenous malformation (AVM) rupture aims toward preventing hemorrhagic expansion while maintaining cerebral perfusion to avoid secondary injury. We investigated associations of model-based indices of cerebral autoregulation (CA) and autonomic function (AF) with outcomes after pediatric cerebral AVM rupture. METHODS: Multimodal neurologic monitoring data from the initial 3 days after cerebral AVM rupture were retrospectively analyzed in children (< 18 years). AF indices included standard deviation of heart rate (HRsd), root-mean-square of successive differences in heart rate (HRrmssd), low-high frequency ratio (LHF), and baroreflex sensitivity (BRS). CA indices include pressure reactivity index (PRx), wavelet pressure reactivity indices (wPRx and wPRx-thr), pulse amplitude index (PAx), and correlation coefficient between intracranial pressure pulse amplitude and cerebral perfusion pressure (RAC). Percent time of cerebral perfusion pressure (CPP) below lower limits of autoregulation (LLA) was also computed for each CA index. Primary outcomes were determined using Pediatric Glasgow Outcome Score Extended-Pediatrics (GOSE-PEDs) at 12 months and acquired epilepsy. Association of biomarkers with outcomes was investigated using linear regression, Wilcoxon signed-rank, or Chi-square. RESULTS: Fourteen children were analyzed. Lower AF indices were associated with poor outcomes (BRS [p = 0.04], HRsd [p = 0.04], and HRrmssd [p = 0.00]; and acquired epilepsy (LHF [p = 0.027]). Higher CA indices were associated with poor outcomes (PRx [p = 0.00], wPRx [p = 0.00], and wPRx-thr [p = 0.01]), and acquired epilepsy (PRx [p = 0.02] and wPRx [p = 0.00]). Increased time below LLA was associated with poor outcome (percent time below LLA based on PRx [p = 0.00], PAx [p = 0.04], wPRx-thr [p = 0.03], and RAC [p = 0.01]; and acquired epilepsy (PRx [p = 0.00], PAx [p = 0.00], wPRx-thr [p = 0.03], and RAC [p = 0.01]). CONCLUSIONS: After pediatric cerebral AVM rupture, poor outcomes are associated with AF and CA when applying various neurophysiologic model-based indices. Prospective work is needed to assess these indices of CA and AF in clinical decision support.