Aneurismal subarachnoid hemorrhage in a Chilean population, with emphasis on risk factors

<p>Abstract</p> <p>Background</p> <p>Subarachnoid Hemorrhage (SAH) is caused principally by the rupture of intracranial aneurisms. Important risk factors have been described such as age, sex, hypertension (HT) and season of the year, among others. The objective is to investigate the demographic characteristics and possible risk factors in a population of Chilean patients.</p> <p>Methods</p> <p>This retrospective study was based on the analysis of 244 clinical records of patients diagnosed with aneurismal SAH who were discharged from the Instituto de Neurocirugía ASENJO in Santiago, Chile.</p> <p>Results</p> <p>The mean age of patients was 49.85 years and the male:female ratio was 1:2.7. The signs and symptoms were not different between sexes; cephalea (85.7%) was predominant, followed by loss of consciousness, vomiting/nausea and meningeal signs. Risk factors included sex, age and HT. Concordant with other reports, the incidence of SAH was greatest in spring.</p> <p>Conclusions</p> <p>The demographic characteristics and risk factors observed in patients with aneurismal SAH treated in ASENJO were comparable to those of other populations. We were not able to conclude that tobacco and alcohol consumption were risk factors for this population.</p

Multidisciplinary Consensus on Assessment of Unruptured Intracranial Aneurysms Proposal of an International Research Group

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The unruptured intracranial aneurysm treatment score A multidisciplinary consensus

Objective: We endeavored to develop an unruptured intracranial aneurysm (UIA) treatment score (UIATS) model that includes and quantifies key factors involved in clinical decision-making in the management of UIAs and to assess agreement for this model among specialists in UIA management and research. Methods: An international multidisciplinary (neurosurgery, neuroradiology, neurology, clinical epidemiology) group of 69 specialists was convened to develop and validate the UIATS model using a Delphi consensus. For internal (39 panel members involved in identification of relevant features) and external validation (30 independent external reviewers), 30 selected UIA cases were used to analyze agreement with UIATS management recommendations based on a 5-point Likert scale (5 indicating strong agreement). Interrater agreement (IRA) was assessed with standardized coefficients of dispersion (v(r)*) (v(r)* 5 0 indicating excellent agreement and v(r)* = 1 indicating poor agreement). Results: The UIATS accounts for 29 key factors in UIA management. Agreement with UIATS (mean Likert scores) was 4.2 (95% confidence interval [CI] 4.1-4.3) per reviewer for both reviewer cohorts; agreement per case was 4.3 (95% CI 4.1-4.4) for panel members and 4.5 (95% CI 4.3-4.6) for external reviewers (p = 0.017). Mean Likert scores were 4.2 (95% CI 4.1-4.3) for interventional reviewers (n = 56) and 4.1 (95% CI 3.9-4.4) for noninterventional reviewers (n = 12) (p = 0.290). Overall IRA (v(r)*) for both cohorts was 0.026 (95% CI 0.019-0.033). Conclusions: This novel UIA decision guidance study captures an excellent consensus among highly informed individuals on UIA management, irrespective of their underlying specialty. Clinicians can use the UIATS as a comprehensive mechanism for indicating how a large group of specialists might manage an individual patient with a UIA.Peer reviewe