Preoperative scale proposal based on clinical outcome for elderly patients with ruptured intracranial aneurysms undergoing microsurgery

Introduction Life expectancy in individuals has increased in recent years. There is no consensus in the literature on the best treatment for a ruptured aneurysm in the elderly (> 60 years), but some places only have microsurgery as a therapeutic strategy. This work aims to develop a prognostic scale for ruptured intracranial aneurysms in the elderly. Material and Methods Two thousand five hundred thirty patients with subarachnoid hemorrhage were retrospectively evaluated in the last ten years, and 550 of them were elderly. We developed a prognostic scale from the analysis of medical records, clinical and tomographic features that had statistical significance. Glasgow Coma Outcome (GOS) was the outcome of interest and p value < 0,05 was considered statistically significant. Results Five hundred fifty patients were evaluated, and the comorbidities that were independent variables for poor prognosis were smoking and arterial hypertension; clinical variables were Hunt-Hess, modified Rankin and Glasgow Coma Scale; tomographic was Fisher scale. Poor outcome was defined as GOS <= 3. Poor surgical outcomes were more remarkable in the high-risk factor categories, being 6.41 times higher among individuals who had 3 to 4 risk factors and 8.80 times higher among individuals with 5 to 6 risk factors. Conclusion In some vascular neurosurgery services worldwide, microsurgery is the only therapeutic option. This scale aimed at the elderly patient individualizes the treatment and can predict the clinical outcome in ruptured intracranial aneurysms.

Automated summary

This study aimed to develop a prognostic scale for ruptured intracranial aneurysms in the elderly, and found smoking and arterial hypertension to be comorbidities associated with poor prognosis, while Hunt-Hess grading, Rankin grading, and Glasgow Coma Scale were clinical variables associated with poor prognosis. This study can help individualize treatment and predict clinical outcomes.