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Updated: Aug 9, 2025
Comprehensive Endovascular and Open Surgical Management of Cerebral Arteriovenous Malformations
Published on: October 20, 2017
Prediction of outcomes for symptomatic spinal cavernous malformation surgery: a multicenter prospective clinical
Tong Liu1, Lichao Wang2, Shizhong Zhang3
1Department of Neurosurgery, Tianjin Institute of Neurology, Tianjin Medical University General Hospital, 154 Anshan Road in Heping District, Tianjin, 300052, China.
Purpose:
Clinical outcome of spinal cavernous malformation (SCM) varies because of its unclear natural history, and reliable prognostic prediction model for SCM patients is limited. The aim of the present study was to investigate potential factors that predict one-year neurological status in postoperative patients with SCM.
Methods:
This was a multicenter prospective observational study in consecutive patients with SCMs. SCMs treated microsurgically between January 2015 and January 2021 were included. Outcome was defined as the American Spinal Injury Association Impairment Scale (AIS) grade at one year after operation. Multivariable analyses were used to construct the best predictive model for patient outcomes.
Results:
We identified 268 eligible SCM patients. Neurological outcome had worsened from preoperative baseline in 51 patients (19.0%) at one year. In the multivariable logistic regression, the best predictive model for unfavorable outcome included symptom duration ≥ 26 months (95% CI 2.80-16.96, P < 0.001), size ≤ 5 mm (95% CI 1.43-13.50, P = 0.010), complete intramedullary (95% CI 1.69-8.14, P = 0.001), subarachnoid hemorrhage (95% CI 2.92-12.57, P < 0.001), AIS B (95% CI 1.91-40.93, P = 0.005) and AIS C (95% CI 1.12-14.54, P = 0.033).
Conclusions:
Admission size of the lesion, morphology, symptom duration, AIS grade and the presence of subarachnoid hemorrhage were strong outcome predictors regarding prognostication of neurological outcome in postoperative patients with SCMs. A decision to surgically remove a symptomatic SCM should be justified by systematic analysis of all factors potentially affecting outcome.
