Introduction: Subarachnoid hemorrhage (SAH) is a disease that has been the target of several investigations and discussions because of its high mortality and significant morbidity. We aimed to develop and validate a practical prognostic model for death at 28 days and for unfavorable neurological outcome (death or severe disability) six months after subarachnoid hemorrhage.

Methods: Prospectively collected individual patient data were analyzed. We considered predictors available at admission in logistic regression models to predict mortality and unfavorable outcome according to the Glasgow Outcome Scale at 6 months after SAH. The performance, precision, accuracy and prediction power of the model were assessment through the area under the receiver operating characteristic curve (AUC), sensitivity and specificity with probability cutoff graph, proportion of correctly classified and detection of specification error.

Results: The model included nine predictors: age, sex, pupil reactivity, glucose, shift midline over 5mm and hydrocephaly, we also included three SAH scales: Hunt and Hess, Modified Fisher and WFNS scale. The model showed excellent discrimination (area under ROC curve= 0.9284), overall correct classification of 90.48%, with a sensibility of 88% and specificity of 92%.

Conclusions: Our prognostic model showed an excellent performance with a great precision, accuracy and prediction power and can be used to obtain valid predictions of relevant outcomes in patients with SAH.

Patient Care: To Predicting outcome after subarachnoid hemorrhage: prognostic model based on admission characteristics

Learning Objectives: By the conclusion of this session, participants should be able to: learn that Our prognostic model showed an excellent performance with a great precision

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