Impact of socioeconomics and race on clinical follow-up and trial enrollment and adherence in cerebral cavernous malformation.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association(2023)

引用 0|浏览11
暂无评分
摘要
Cerebral cavernous malformation (CCM) affects more than a million Americans but advanced care for symptomatic lesions and access to research studies is largely limited to referral academic centers MATERIALS AND METHODS: A cohort of CCM patients screened for research studies at an accredited center of excellence for CCM was analyzed. Demographics, lesion location, history of hemorrhage, insurance type and area of deprivation index (ADI) were collected. Primary outcomes were clinical follow-up within a year from initial evaluation, and enrollment and adherence in clinical trials among eligible subjects RESULTS: A majority (52.8%) of CCM patients evaluated had a high socioeconomic status (SES) (ADI 1-3), and only 11.5% were African American. Patients who had a symptomatic bleed were more likely to follow-up (p=0.01), and those with brainstem lesion were more likely to enroll/adhere in a clinical trial (p=0.02). Rates of clinical follow-up were similar across different ADI groups, insurance coverage and race. Patients who were uninsured/self-paying, and African Americans were more likely to decline/drop from clinical trials (OR 2.4, 95% CI 0.46-10.20 and OR 2.2, 95% CI 0.33-10.75, respectively), but differences were not statistically significant CONCLUSIONS: Access of disadvantaged patients to center of excellence care and research remains limited despite geographic proximity to their community. Patients with lower SES and African Americans are as likely to follow-up clinically, but there were trends of differences in enrollment/adherence in clinical trials. Mitigation efforts should target systemic causes of low access to specialized care among uninsured and African American patients.
更多
查看译文
关键词
Cavernous angioma, Cerebral cavernous malformation, Race, Clinical trials, Minority health, Health disparities, Socioeconomics, Health equity
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要