Predicting mortality and outcomes after a subarachnoid hemorrhage

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A clinical prediction tool successfully forecasts subarachnoid hemorrhage management from ruptured intracranial aneurysms.
A clinical prediction tool successfully forecasts subarachnoid hemorrhage management from ruptured intracranial aneurysms.

New clinical prediction models may help project outcomes for patients with subarachnoid hemorrhage from ruptured intracranial aneurysms (SAH) in a hospital setting, according to a study published in the BMJ.

Blessing NR Jaja, MD, PhD, research associate in the Division of Neurosurgery at St Michael's Hospital in Toronto, and associates conducted a group study using the Subarachnoid Haemorrhage International Trialists' (SAHIT) original results in a logistic regression to examine predictors and treatment methods.

Differentiated patient information was used to generate the clinical prediction models from 10,936 patients. After the models were developed, an additional 3355 patients provided further data, used to authenticate the clinical models.

Prediction model factors for further authentication were age (median age, 55), clinical severity at admission according to the World Federation of Neurosurgical Societies (WFNS) score, hypertension rates, magnitude of subarachnoid hemorrhage at admission, magnitude and loci of ruptured aneurysm, and the manner of treatment.

Using the factors above, three group models were generated to validate the authenticity of the clinical prediction tool based on patient characteristics. The authenticities were calculated using statistical analysis, resulting in different areas under the receiver operator characteristics curve (AUC). The factors in the first validation group model included age, hypertension, and the WFNS score (AUC, 0.80). The second model included clot volume and aneurysm magnitude and loci, resulting in an AUC of 0.81. The final model included the method of treatment (AUC, 0.81).

In both the preliminary and validation groups, the majority of patients were women (71% and 64%, respectively), and mortality rates were 13% and 17%, respectively. Of the living patients, 29% in preliminary group and 28% in the authentication group survived critically.

“An easy to use practical prediction tool was developed with the data from a large multinational population of patients to predict mortality and functional outcomes after subarachnoid haemorrhage,” the authors reported. “The tool performed satisfactorily in a different set of patients who were treated at different regions and settings of care.”

Reference

  1. Jaja BNR, Saposnik G, Lingsma HF, et al. Development and validation of outcome prediction models for aneurysmal subarachnoid haemorrhage: the SAHIT multinational cohort study. BMJ. 2018 Jan 18. doi: 10.1136/bmj.j5745
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