Prediction of Outcome After Aneurysmal Subarachnoid Hemorrhage

Abstract

Background and Purpose— Early prediction of clinical outcome after aneurysmal subarachnoid hemorrhage (aSAH) is still lacking accuracy. In this observational cohort study, we aimed to develop and validate an accurate bedside prediction model for clinical outcome after aSAH, to aid decision-making at an early stage. Methods— For the development of the prediction model, a prospectively kept single-center cohort of 1215 aSAH patients, admitted between 1998 and 2014, was used. For temporal validation, a prospective cohort of 224 consecutive aSAH patients from the same center, admitted between 2015 and 2017, was used. External validation was performed using the ISAT (International Subarachnoid Aneurysm Trial) database (2143 patients). Primary outcome measure was poor functional outcome 2 months after aSAH, defined as modified Rankin Scale score 4–6. The model was constructed using multivariate regression analyses. Performance of the model was examined in terms of discrimination and calibration. Results— The final model included 4 predictors independently associated with poor outcome after 2 months: age, World Federation of Neurosurgical Societies grade after resuscitation, aneurysm size, and Fisher grade. Temporal validation showed high discrimination (area under the receiver operating characteristic curve, 0.90; 95% CI, 0.85–0.94), external validation showed fair to good discrimination (area under the receiver operating characteristic curve, 0.73; 95% CI, 0.70–0.76). The model showed satisfactory calibration in both validation cohorts. The SAFIRE grading scale was derived from the final model: size of the aneurysm, age, Fisher grade, world federation of neurosurgical societies after resuscitation. Conclusions— The SAFIRE grading scale is an accurate, generalizable, and easily applicable model for early prediction of clinical outcome after aSAH.

Outcome prediction in aneurysmal subarachnoid hemorrhage: a comparison of machine learning methods and established clinico-radiological scores

“…The majority of previously established aSAH outcome prediction models are based on neurological deficits on admission and radiographic features, such as thickness of subarachnoid blood clots and the presence of IVH or ICH. However, more recent evidence suggests that other factors play a role in precise outcome prediction, such as patient age, pupil status, and aneurysm size and location [21,29]. The inclusion of a high number of variables is one of the main strengths of ML approaches.…”

Initial pupil status is a strong predictor for in-hospital mortality after aneurysmal subarachnoid hemorrhage

“…Other recently published aSAH prognostic models which were based on large-scale aSAH-cohorts include the SAFIRE scale, FRESH score and different scores based on the SAHIT cohort [26][27][28] . The SAFIRE model predicted poor functional outcome with an AUROC of 0.73 in the validation cohort and was based on aneurysm size, age, Fisher grade and WFNS 26 . The FRESH score considered variables H&H, age, APACHE-II Physiologic score and aneurysmal rebleed within 48 hours 27 .…”

Clinical Efficacy and Quality of Life Follow-Up of Reconstructive Endovascular Therapy for Acute Intracranial Vertebral Artery Dissection Aneurysms

“…Subarachnoid hemorrhage Fisher grade was observed as an important factor in our study, being significantly different in the bad QOL group in comparison with the good QOL group with good functional outcome in group H. As we all well-know, the severity of subarachnoid hemorrhage Fisher grade is associated with the rate of occurrence of delayed cerebral vasospasm. Some previous studies demonstrated that Fisher grade was a risk predictor for delayed cerebral infarction (40,41). Therefore, we hypothesized that a higher Fisher grade might contribute to a higher possibility of delayed cerebral infarction, which would result in lower cerebral perfusion and would influence the rehabilitation of patients at follow-up.…”