# Electroencephalographic signatures of dysfunctional cerebrovascular autoregulation as biomarkers of brain injury in aneurysmal subarachnoid hemorrhage (SAH)

> **NIH NIH R21** · YALE UNIVERSITY · 2023 · $251,250

## Abstract

Abstract
Aneurysmal subarachnoid hemorrhage (aSAH) remains a devastating disease affecting approximately 30,000
adults in the United States per year. Forty percent of aSAH patients die within 30 days, and over one-third of
survivors sustain major neurologic deficits, in part due to feared secondary complications like vasospasm and
delayed cerebral ischemia (DCI). Despite advances in care, few interventions can mitigate the risk of neurologic
worsening after the initial bleed, and current monitoring strategies to identify impending DCI have limited
accuracy. Abnormalities in cerebrovascular autoregulation and flow-metabolism uncoupling in the acute phase
after aSAH have been shown to increase the risk of secondary brain injury and likely represent key players in
the development of DCI. In this proposal, we plan to develop and refine an innovative, personalized approach to
blood pressure management to identify patients most likely to benefit from therapeutic BP manipulation. To carry
out this overarching aim, we will track continuous recordings of intracranial pressure, near-infrared spectroscopy,
and EEG to determine patient-specific blood pressure targets that yield optimal brain blood flow and metabolism.
This research proposal will evaluate if cerebral hemodynamic dysregulation drives EEG deterioration (Aim 1)
and if a deviation from optimized blood pressure targets is associated with DCI and poor outcomes (Aim 2). We
will then prospectively validate our results in a pilot cohort study. This proposal’s feasibility rests on (1) several
years of research conducted by the principal investigators on signal processing, autoregulatory physiology, and
continuous EEG in disease states like SAH and ischemic stroke, and (2) promising preliminary analyses
evaluating the hypotheses being explored in this proposal. In total, this autoregulation-oriented neuroprotective
therapy aims to optimize cerebral perfusion and ultimately improve clinical and functional outcomes. This
research proposal is thus directly aligned with the NIH mission to reduce the burden of neurological disorders
and enhance the quality of life of people with disabilities. The study will leverage Yale’s cutting-edge neuro-
monitoring technologies along with extensive informatics and research resources of the Yale Center for Clinical
Investigation to generate new insights into cerebral hemodynamics after aSAH and identify treatment
opportunities. This line of research is readily translatable to the bedside and also applies to other cerebrovascular
diseases like intracerebral hemorrhage and ischemic stroke, both of which likely encompass dysautoregulation
as a critical physiologic variable. Knowledge gained in this study is anticipated to lead to a significant shift in the
treatment approach for aSAH patients. It may ultimately lead to a clinical trial testing autoregulation-based
treatment strategies, including tailored pharmacologic BP modulation based on patients’ real-time autoregulator...

## Key facts

- **NIH application ID:** 10667162
- **Project number:** 1R21NS128641-01A1
- **Recipient organization:** YALE UNIVERSITY
- **Principal Investigator:** Jennifer A Kim
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2023
- **Award amount:** $251,250
- **Award type:** 1
- **Project period:** 2023-04-15 → 2025-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10667162

## Citation

> US National Institutes of Health, RePORTER application 10667162, Electroencephalographic signatures of dysfunctional cerebrovascular autoregulation as biomarkers of brain injury in aneurysmal subarachnoid hemorrhage (SAH) (1R21NS128641-01A1). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10667162. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*
