Racial and Socioeconomic Status among a Patient Population Presenting with Aneurysmal Subarachnoid Hemorrhage versus Unruptured Intracranial Aneurysm: A Single-Center Study.
Ashia M HackettChristopher O AderetiAriel P WalkerElsa NicoLea ScherschinskiEmmajane G RhodenhiserAdam T EberleAnant NaikJuan P GiraldoJoelle N HartkeRedi RahmaniEthan A WinklerJoshua S CatapanoMichael T LawtonPublished in: Brain sciences (2024)
Racial and socioeconomic health disparities are well documented in the literature. This study examined patient demographics, including socioeconomic status (SES), among individuals presenting with aneurysmal subarachnoid hemorrhage (aSAH) and unruptured intracranial aneurysm (UIA) to identify factors associated with aSAH presentation. A retrospective assessment was conducted of all patients with aSAH and UIA who presented to a large-volume cerebrovascular center and underwent microsurgical treatment from January 2014 through July 2019. Race and ethnicity, insurance type, and SES data were collected for each patient. Comparative analysis of the aSAH and UIA groups was conducted. Logistic regression models were also employed to predict the likelihood of aSAH presentation based on demographic and socioeconomic factors. A total of 640 patients were included (aSAH group, 251; UIA group, 389). Significant associations were observed between race and ethnicity, SES, insurance type, and aneurysm rupture. Non-White race or ethnicity, lower SES, and having public or no insurance were associated with increased odds of aSAH presentation. The aSAH group had poorer functional outcomes and higher mortality rates than the UIA group. Patients who are non-White, have low SES, and have public or no insurance were disproportionately affected by aSAH, which is historically associated with poorer functional outcomes.
Keyphrases
- case report
- end stage renal disease
- healthcare
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- chronic kidney disease
- coronary artery
- ejection fraction
- affordable care act
- mental health
- health insurance
- systematic review
- prognostic factors
- peritoneal dialysis
- type diabetes
- internal carotid artery
- emergency department
- middle cerebral artery
- cardiovascular disease
- long term care
- machine learning
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- artificial intelligence
- data analysis
- optical coherence tomography
- human health