Of the 30,000 Americans who develop SAH each year, 20-40% have a subsequent event of delayed cerebral ischemia (DCI), which triples the risk of poor functional outcome, producing impairment at a relatively young age compared with other stroke subtypes. Because DCI following SAH is commonly detected only after it is irreversible, an accurate tool is needed to identify impending DCI so that therapies can begin before DCI is well established and so that new clinical therapies for DCI prevention have the best opportunity for success. Ideally, monitoring tools should afford real-time assessment of neuronal function impacted by the diverse vascular and metabolic mechanisms leading to DCI. The proposed scientific program aims to examine the accuracy of real-time clinical assessments and continuous EEG for predicting impending DCI by evaluating for early, pre-symptomatic deterioration in brain activity. The principal investigator has three specific research aims: (1) to determine whether incorporating real- time clinical data extending through the postoperative period improves prediction of DCI compared to admission data alone; (2) to determine whether real-time clinical neurophysiologist reporting of pre-specified EEG features improves DCI prediction; and 3) to examine the influence of blood pressure on EEG measures of neuronal dysfunction before and after DCI. The proposed studies build on pilot data collected by the applicant by using real-time clinical data beyond admission, performing blinded assessments for DCI based on NIH Common Data Elements, and extending the study of blood pressure and EEG alpha power to a large cohort with synchronized multimodality monitoring. Under the mentorship of primary mentor Dr. Jonathan Rosand, and co-mentors Drs. Sydney Cash, Hang Lee, and Nazem Atassi, the PI proposes a career development plan leveraging the resources of a world-class environment at Massachusetts General Hospital and Harvard Medical School to develop proficiency in biostatistics, multi-state survival analysis, and signal processing, carry out the project and transition to an independent clinician-scientist studying SAH-related morbidity and its prevention. The overall goal of this project is to develop strategies for detecting early signs of impending DCI to enable preventative therapies to be delivered 1) in a timely manner and 2) to the appropriate patients. This will provide a framework for efficient, successful future clinical trials of DCI prevention. Bringing together cutting-edge clinical neurophysiology, analytic resources at MGH, and a team of mentors with relevant expertise, this project will define the population of SAH patients at greatest risk for DCI, while drawing understanding about the impact of blood pressure on brain function at various stages leading to DCI. The proposed patient-oriented research project, in concert with mentorship and a structured curriculum in methods including biostatistics, multi-state survival analysis, signal processing, and clinical trial design, will provide Dr. Rosenthal with the skills to develop an independent career in subarachnoid hemorrhage research at the cutting edge of science.
/Relevance For over 30,000 Americans and 600,000 patients worldwide who experience subarachnoid hemorrhage each year, there is no clinical tool to accurately predict the complication of delayed cerebral ischemia. The absence of such a prognostic tool results in irreversible neurologic injury commonly occurring despite over 2 weeks of neurocritical care and substantial resources dedicated to current monitoring strategies of limited accuracy. Dr. Rosenthal's proposed career development plan has outstanding potential to advance knowledge about real- time clinical and neurophysiologic predictors of delayed cerebral ischemia and treatment early treatment response, which is a crucial step towards the discovery of novel treatments.
|Rosenthal, Eric S; Biswal, Siddharth; Zafar, Sahar F et al. (2018) Continuous electroencephalography predicts delayed cerebral ischemia after subarachnoid hemorrhage: A prospective study of diagnostic accuracy. Ann Neurol 83:958-969|