Differences between real-world and score-based decision-making in the microsurgical management of patients with unruptured intracranial aneurysms.

Abstract

Background: Management of unruptured intracranial aneurysms (UIAs) is complex, balancing the risk of rupture and risk of treatment. Therefore, prediction scores have been developed to support clinicians in the management of UIAs. We analyzed the discrepancies between interdisciplinary cerebrovascular board decision-making factors and the results of the prediction scores in our cohort of patients who received microsurgical treatment of UIAs.

Methods: Clinical, radiological, and demographical data of 221 patients presenting with 276 microsurgically treated aneurysms were collected, from January 2013 to June 2020. UIATS, PHASES, and ELAPSS were calculated for each treated aneurysm, resulting in subgroups favoring treatment or conservative management for each score. Cerebrovascular board decision-factors were collected and analyzed.

Results: UIATS, PHASES, and ELAPSS recommended conservative management in 87 (31.5%) respectively in 110 (39.9%) and in 81 (29.3%) aneurysms. The cerebrovascular board decision-factors leading to treatment in these aneurysms (recommended to manage conservatively in the three scores) were: high life expectancy/young age (50.0%), angioanatomical factors (25.0%), multiplicity of aneurysms (16.7%). Analysis of cerebrovascular board decision-making factors in the "conservative management" subgroup of the UIATS showed that angioanatomical factors (P=0.001) led more frequently to surgery. PHASES and ELAPSS subgroups "conservative management" were more frequently treated due to clinical risk factors (P=0.002).

Conclusions: Our analysis showed more aneurysms were treated based on "real-world" decision-making than recommended by the scores. This is because these scores are models trying to reproduce reality, which is yet not fully understood. Aneurysms, which were recommended to manage conservatively, were treated mainly because of angioanatomy, high life expectancy, clinical risk factors, and patient's treatment wish. The UIATS is suboptimal regarding assessment of angioanatomy, the PHASES regarding clinical risk factors, complexity, and high life expectancy, and the ELAPSS regarding clinical risk factors and multiplicity of aneurysms. These findings support the need to optimize prediction models of UIAs.