Sunday, May 5, 2024
5/5/2024
Project Summary/Abstract In the United States, subdural hematomas (SDHs) are projected to become the most common cranial neurosurgical condition by 2030. This has major public health implications, as nearly 50% of SDH patients are dead or severely disabled at three months. Despite its importance, there is very little study of this disease at the population-level, particularly with regard to outcomes after patients leave the hospital. Nearly 1 in 6 patients that survive an initial SDH hospitalization are rehospitalized within 90 days, and this risk may be impacted heavily by social determinants of health (SocDH). Regardless, there is no predictive model available to identify SDH survivors at high risk of rehospitalization. Further, SDHs are tightly associated with premorbid antithrombotic use, and these medications are commonly held at the time of presentation, but there is little evidence about the risks and benefits of antithrombotic resumption in SDH survivors. To address these limitations, we will conduct the first population-level study of SDH outcomes in the United States. We will accomplish this relatively quickly and at low cost by utilizing the well-validated infrastructure of the Greater Cincinnati/Northern Kentucky Stroke Study, which has been studying population-level outcomes in stroke and intracranial hemorrhage for more than 30 years. This infrastructure will allow us to determine the 3-year risk of major ischemic and hemorrhagic events after an SDH and determine the predictors for each outcome. We will also a build a predictive model of 90-day rehospitalization or death among SDH patients that utilizes both clinical and SocDH variables. We will use conventional predictive modeling along with modern machine learning techniques, allowing us to maximize predictive ability and potentially identify new variables and interactions that lead to adverse outcomes in SDH survivors. Through this proposal, Dr. Robinson will become an expert in the epidemiology of SDH and in the use of novel data science techniques to analyze large clinical databases. These skills will prepare him to become the next PI of the overall Greater Cincinnati/Northern Kentucky Stroke Study. Dr. Robinson will conduct this work under the guidance of a distinguished mentorship committee: Dr. Brett Kissela, a stroke epidemiologist with expertise in using big data techniques; Dr. Dan Woo, a clinician scientist that studies disparities in intracerebral hemorrhage; Opeolu Adeoye, a neurointensivist and researcher with expertise in acute care research; and Hooman Kamel, a stroke epidemiologist and neurointensivist with expertise in the population-level study of SDHs.
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