Abstract
OBJECTIVE: To evaluate the applicability and performance of predictive scoring systems for outcome prediction in a real-world cohort of patients with aneurysmatic Subarachnoid Hemorrhage (aSAH), trying to avoid overtreatment and reducing their impact on Intensive Care Unit (ICU) overcrowding. METHODS: All adult patients diagnosed with aSAH from January 2018 to December 2023 were retrospectively collected in a single centre. Predictive scores such as SAFIRE, HATCH, HAIR, and Nutshell were calculated, and their performance was analyzed using receiver operating characteristic (ROC) analysis. Kaplan-Meier curves were estimated by dividing the cohort according to the calculated scores. RESULTS: Of 274 patients, 72.3% underwent endovascular treatment, 16.1% surgical clipping, and 11.7% received no treatment. The 30-day and overall mortality rates were 27.7% and 41.2%, respectively. ICU admission occurred in 74.1% of cases, with a mortality rate of 38.4%. The HAIR and the Nutshell scores performed well in predicting 30-day mortality (AUC: 0.812 and 0.749, respectively), while the SAFIRE and the HATCH scores demonstrated excellent predictive value for poor functional outcomes (AUC: 0.866 and 0.886 at discharge; 0.825 and 0.83 at one year, respectively). Patients in the worst SAFIRE group (> 15) exhibited mortality rates exceeding 89% at follow-up, with universally poor outcomes. CONCLUSION: The SAFIRE and the HATCH scores are reliable tools for predicting outcomes in aSAH patients, with SAFIRE offering particular value at admission. Their implementation in surgical practice could improve resource allocation, guide ethical decision-making, and reduce ICU burden, especially for patients with severe aSAH and limited potential for recovery.