Background: Understanding the trends of stroke incidence and how those strokes are distributed across race is a critical step to implement trials and programs to decrease the burden caused by stroke nationally. In 2015, we reported that stroke incidence is decreasing in both Black and White adults. We investigated the continued trends in stroke incidence by race in 2020. Methods: In this population-based stroke surveillance study, all cases of stroke within a 5-county population surrounding Cincinnati in adults aged ≥20 years were ascertained during a full year every 5 years from 1993 to 2020. Cases were abstracted by study nurses and adjudicated by trained study physicians. Temporal trends were evaluated by age, race (Black or White), and subtype (ischemic stroke (IS), intracranial hemorrhage (ICH), or subarachnoid hemorrhage (SAH)). Stroke incidence rates per 100,000 individuals from 1993 to 2020 were calculated using US Census data and age-, race-, and sex-standardized as appropriate. Trends were evaluated using linear regression. Disparities were evaluated using risk ratios and reported with 95% CIs. Results: In 2020, we identified 2280 first-ever strokes. Of these, 23% (N=524) were Black adults and 52% (N=1,177) were female. The overall annual incidence of stroke in 2020 was 203/100,000. Table 1 reports the temporal trends of stroke incidence by subtype for both Black and White race from 1993 to 2020. For all races, any stroke increased between 2015 and 2020 (p=0.003, driven largely by an increase in stroke in White adults), while the overall trend since 1993 is no longer declining. Ischemic stroke also increased between 2015 and 2020 (pairwise comparison, p=0.011) in all races. Figure 1 shows the stroke incidence rate of overall stroke (any subtype) over time. The overall risk ratio of any incident stroke between Black and White adults was RR 1.84 (1.66, 2.02; p-value 0.022). Conclusions: Compared to our analysis after our 2015 study, overall stroke incidence over time is no longer decreasing. Between 2015 and 2020, we observed an increasing rate of stroke in our population. For the first time in a 27-year period we report a significant increase in stroke incidence, mostly driven by an increase in ischemic stroke incidence in whites. ICH/SAH rates are stably higher in blacks compared to whites. More work needs to be done to investigate any possible association to COVID or other traditional risk factors to address racial disparities in stroke burden.

Objectives/Goals: We hypothesized that the bulk transcriptomic profiling of blood collected from within the ischemic vasculature during an acute ischemic stroke with large vessel occlusion (LVO) will contain unique biomarkers that are different from the peripheral circulation and may provide much-needed insight into the underlying pathogenesis of LVO in humans. Methods/Study Population: The transcriptomic biomarkers of Inflammation in Large Vessel Ischemic Stroke pilot study prospectively enrolled patients ≥ 18 years of age with an anterior circulation LVO, treated with endovascular thrombectomy (EVT). Two periprocedural arterial blood samples were obtained (DNA/RNA Shield™ tubes, Zymo Research); 1) proximal to the thrombus, from the internal carotid artery and 2) immediately downstream from the thrombus, by puncturing through the thrombus with the microcatheter. Bulk RNA sequencing was performed and differential gene expression was identified using the Wilcoxon signed rank test for paired data, adjusting for age, sex, use of thrombolytics, last known well to EVT, and thrombolysis in cerebral infarction score. Bioinformatic pathway analyses were computed using MCODE and reactome. Results/Anticipated Results: From May to October 2022, 20 patients were screened and 13 were enrolled (median age 68 [SD 10.1], 47% male, 100% white). A total of 608 differentially expressed genes were found to be significant (p-value) Discussion/Significance of Impact: These results provide evidence of significant gene expression changes occurring within the ischemic vasculature of the brain during LVO, which may correlate with larger ischemic infarct volumes and worse functional outcomes at 90 days. Future studies with larger sample sizes are supported by this work.

Introduction: ICD-10 codes are often used for stroke research in administrative databases. Few studies have assessed their reliability in large, representative populations of the United States. We validated ICD-10 codes in a large population-based study of stroke in the Greater Cincinnati/Northern Kentucky (GCNK) region. Methods: We ascertained all acute strokes in the GCNK region during 2020 using validated methodology. All hospitalizations were screened using a comprehensive list of ICD codes in any diagnosis position (G45-46/H34/I60-69). Additional cases were captured through cold pursuit. Each case was adjudicated by a stroke-trained physician. Only acute ischemic stroke (AIS) and hemorrhagic strokes (HS, defined as intracerebral hemorrhage or subarachnoid hemorrhage) were included in this analysis. We examined how many AIS cases were identified using the standard codes used for administrative studies (G46/I63), assessing their sensitivity and positive predictive value (PPV) in the primary or secondary positions. A similar analysis was conducted using standard HS codes (I60/I61). Differences in the demographics of cases identified with standard codes in the primary position, standard codes in the secondary position, or through other methods were then evaluated with Chi-squared and Kruskal-Wallis tests. Results: We identified 3,522 AIS/HS events in 2020. For AIS (Table 1), we found that standard codes in the primary position had a sensitivity of 72.8% and a PPV of 89.1%. When the standard AIS codes were considered in any diagnosis position, sensitivity improved to 89.3%, but PPV decreased to 82.3%. For HS, standard codes in the primary position had a sensitivity of 80.0% and a PPV of 81.0%. When the standard HS codes were considered in any position, the sensitivity improved to 93.4% but the PPV decreased to 54.4%. When looking at baseline characteristics (Table 2), patients identified through a standard code in the primary position had a lower baseline mRS (overall P<0.01); nursing home residence was also more common in patients identified through a standard code in the secondary position (7.8%, overall P<0.01). Conclusion: For AIS, standard codes in the primary position showed only moderate sensitivity but reasonable PPV. For HS, standard codes in the primary position had moderate sensitivity and moderate PPV. Restricting analyses to patients with a standard code in the primary position likely selects against patients with more disability at baseline.

Background and Objectives:The relationship between socioeconomic factors and Parkinson disease (PD) is unclear. Previous literature suggests a potential disconnect between the effect of socioeconomic status (SES) on PD risk and severity. A recent study found that people with PD in the United States were more likely to come from well-resourced communities. Multiple possible explanations were proposed, including that lower SES could be protective against PD risk. Other studies have found worsened PD symptoms and outcomes associated with lower individual SES. If environmental factors associated with lower SES influence PD biology in a way that worsens symptoms, those processes should also increase PD risk. We set out to determine whether community disadvantage, rather than individual SES, is associated with motor or cognitive symptom severity in PD and atypical parkinsonisms. Methods:Community disadvantage was defined using the Material Community Deprivation Index, a compound score of multiple poverty markers. In our Cincinnati Cohort Biomarkers Program, a cohort that includes PD and atypical parkinsonisms, we tested for associations between community disadvantage and motor symptom severity (Movement Disorders Society Unified PD Rating Scale part III; MDS-UPDRS III), motor disability (Hoehn and Yahr stage [HY]), and cognition (Montreal Cognitive Assessment [MoCA]). We considered age, sex, disease duration, levodopa equivalent daily dose, education years, and race as covariates in multiple regression analyses. Results:A total of 565 people with PD or atypical parkinsonisms were included (458 idiopathic PD and 107 atypical parkinsonisms). Their mean age was 69 years, and 65% were men. The mean disease duration was 7 years, and the mean MDS-UPDRS III score was 30. The majority (75%) were HY stage 2, and the mean cognitive screening score was nondemented (MoCA 25/30). Worse community disadvantage was significantly associated with worse MDS-UPDRS III score (β 1.58, p = 0.01; adjusted for age, sex, and disease duration) and HY stage (OR 1.27, p = 0.04, adjusted for age, sex, disease duration, and education years). Community disadvantage was not significantly associated with MoCA score (p = 0.45). Discussion:Community disadvantage was associated with worse motor symptom severity and motor disability in PD, suggesting that there are modifiable social and environmental factors that can affect parkinsonian symptom severity.

BACKGROUND:Intracerebral hemorrhage (ICH) carries a 30-day mortality rate of 40% to 50% and a high burden of disability. Prior studies found that psychosocial stressors are associated with hypertension, ischemic stroke, and important racial/ethnic differences in baseline stress exist. We sought to determine whether stress, including distinct subtypes, predicts risk of ICH after controlling for important risk factors; whether its effect is mediated by hypertension; and whether important racial/ethnic differences in stress-associated ICH exist. METHODS:Data from the ERICH (Ethnic/Racial Variations of Intracerebral Hemorrhage) study, a prospective, multicenter, case-control study of ICH among White, Black, and Hispanic patients were used. Controls matched 1:1 by sex and race or ethnicity. Participants rated 4 stress subtypes (financial, health, emotional well-being, and family) on a 0 to 10 scale for the week before ICH, with 0 signifying no stress and 10 highest stress. Univariate and multivariable logistic regressions to assess each stress type as a risk factor for ICH and mediation analyses to determine whether hypertension mediated the association between stress and ICH were performed. RESULTS:There were 2964 case/control matches (41.4% female, 33.7% Black, and 32.7% Hispanic). Higher levels of each stress subtype increased probability of ICH: financial, health, emotional well-being, family, and total stress. Financial stress was associated with nonlobar ICH and disproportionately affected Black and Hispanic patients. Hypertension was found to mediate the ICH risk effects of health, emotional well-being, and family stress. CONCLUSIONS:Psychosocial stress remains a risk factor for ICH after controlling for hypertension. Novel mechanisms underlying this association warrant further study and offer a new target for ICH risk mitigation. REGISTRATION:URL: clinicaltrials.gov; Unique Identifier: NCT01202864.

Background: Hemorrhagic transformation (HT) of ischemic stroke after intravenous thrombolytics is the most feared complication of treatment, occurring in 2-7% of patients. Patients with the most severe hemorrhage have an 18-fold increased risk of 24-hour deterioration and an 11-fold increase in 3-month mortality. Predicting those at higher risk of HT would allow more individualized care, potentially reducing the risk of harm. Utilizing only non-contrast computed tomography (NCCT) of the head, we sought to create a deep learning model to predict those at higher risk of HT from within a large, population-based study. Methods: Utilizing the Greater Cincinnati/Northern Kentucky Stroke Study, we identified patients in the 2015 study epoch who presented with acute ischemic stroke and received intravenous thrombolytics. Images were obtained, visually checked for quality, brain extracted, aligned to a template, windowed to 10-100 HU, and cropped to maximize the ratio of brain-specific voxels in the image. Data were input into a 101-layer 3D Convolutional Neural Network with Residual Connections (ResNet-101) with a binary output (HT vs no HT) trained on weighted focal binary cross-entropy loss. Stratified 5-fold cross-validation was used to evaluate model performance. Smoothed salience mapping was used to interpret model output. Results: 194 patients were initially evaluated, with 24 having imaging diagnosed HT. After quality checks, 121 images were used for analysis,17 having HT. Table 1 shows the demographics and clinical data which would be typically available at the time of thrombolytic administration. Cross-validation AUC varied from 0.73 to 0.87, with the full results displayed in Figure 2. Saliency map differences between correctly and incorrectly identified HT suggested the network focused on deep, subcortical structures and ventricles when predicting HT accurately (Figure 1). Conclusions: We report pilot data of an accurate artificial neural network that correctly identifies HT after thrombolytics utilizing only baseline NCCT. Our results are consistent with a previous study suggesting a higher risk of HT after mechanical thrombectomy in patients with subcortical infarcts. More data is required to refine the algorithm, especially to understand why the ventricles were an area of interest to the model. Further work and improvement of this model has the potential to estimate risk of HT in a more individualized manner and provide decision support.

Background: Certain findings on transthoracic echocardiography (TTE) are associated with a recognized cardioembolic stroke mechanism but less is known about the prevalence of those findings in other subtypes, especially cryptogenic stroke patients. We sought to describe the prevalence of these abnormalities reported on TTE in stroke patients in a large, population-based stroke study and compare the findings specifically of cryptogenic stroke patients to those with the other identified subtypes. Methods: In 2015, the Greater Cincinnati/Northern Kentucky Stroke Study identified all stroke cases in the 5-county area surrounding Cincinnati by ICD 9/10 codes. Potential cases were abstracted by trained study nurses and physician adjudicated, which included assigning ischemic stroke etiology based on our epidemiologic criteria. TTE reports were reviewed. Demographic information, medical history, stroke subtype and prespecified TTE features were collected for each patient and compared across stroke subtype groups. We performed a pair-wise post hoc comparison to the cryptogenic group if a difference was found amongst the groups based on the omnibus test. Results: In 2015, there were 2481 ischemic strokes among patients 18 years or older in our 5-county area. Of these, 677 (27%) were cardioembolic, 312 (13%) large artery atherosclerotic (LAA), 419 (17%) small vessel, 154 (6%) other etiology and 919 (37%) cryptogenic. Of these ischemic stroke events, there were 1503 (61%) with TTE reports available. The severity for diastolic dysfunction, left atrial (LA) dilation, left ventricular hypertrophy and valvular abnormalities were not included in the data analysis. Cardioembolic strokes had significantly higher proportions of LA dilation, mitral and aortic regurgitation, greater LA size and area, and lower left ventricular ejection fraction (LVEF) compared to cryptogenic patients. LAA patients had a higher LA size and lower LVEF compared to cryptogenic patients. The only difference found between cryptogenic and small vessel patients was higher LA size in the latter group. Conclusion: In a large population-based study, TTE findings in cryptogenic stroke patients were less similar to cardioembolic stroke and more similar to other subtypes. While our findings suggest it is less likely to have echocardiographic findings concerning for cardioembolic stroke in the cryptogenic population, further studies on novel and comprehensive cardiac markers are needed to confirm this.

Background: Black individuals are at a higher risk of stroke, but little is known about racial disparities in functional outcome. Using a representative population-based study, we examined disparities in outcome over multiple timepoints in the first year after acute ischemic stroke (AIS). Methods: We ascertained all hospitalized AIS events in the Greater Cincinnati Northern Kentucky region from July 2019-December 2020 (Black individuals) and January 2020-December 2020 (White individuals). Potential cases were identified by ICD codes, abstracted, and physician adjudicated. Only patients who survived their initial hospitalization were included. Using a validated approach, modified Rankin Scale (mRS) was determined retrospectively at discharge, 3 months, 6 months, and 1-year post-stroke. Mixed effect ordinal regression was used to investigate the effect of Black race on functional outcome, after adjustment for relevant factors. We collapsed mRS scores of 5 and 6 into one category for the ordinal shift analyses due to the small number of patients with an mRS of 5. A race:time interaction term was considered to assess whether the race-based differences in functional outcome varied by timepoint. Missing data was handled via full information maximum likelihood. Results: Over the study period, we identified 2541 AIS survivors, of whom 816 (32%) were Black and 1306 (51%) were women (Graphic 1). Unadjusted distributions of mRS scores over 1 year of follow-up are shown in Graphic 2. At 12 months, 25.4% of White individuals (434/1707) and 21.2% of Black individuals (169/799) had an mRS of 0 or 1. When adjusted for age and sex, Black race was associated with a shift towards worse ordinal mRS (Graphic 3, cOR 1.48, 95% CI 1.30-1.68). When other potential confounders were added to the model, the effect of Black race was attenuated but remained significant (cOR 1.16, 95% CI 1.02-1.31). There was no significant interaction between Black race and time after stroke in either model (0.10 and 0.09, respectively). Conclusions: Using one of the first population-based studies of long-term post-stroke functional outcomes in the U.S., we found that Black individuals experience worse functional outcomes, and this effect was incompletely attenuated when adjusted for comorbidities and initial management. Further research is needed to understand whether these disparities are driven by modifiable social determinants that impact stroke rehabilitation.

Background and Objectives Food deserts (FDs) are low-income areas with poor access to healthy foods. FD residents have higher rates of several cardiovascular risk factors, but the link between FDs and stroke has not been well studied. We evaluated whether FD residence was associated with incident ischemic stroke within the Greater Cincinnati/Northern Kentucky Stroke Study (GCNKSS) and whether this association was due to low income, poor food access, or both. Methods All hospitalized stroke cases in the GCNK region were ascertained during calendar year 2015 using ICD-9 and ICD-10 codes for screening and confirmed by physician review. Patient home addresses were geocoded using Decentralized Geomarker Assessment for Multi-Site Studies. FD locations were obtained from the US Department of Agriculture Food Access Research Atlas, defined as census tracts with both poor food access and low income according to established definitions based on proximity to healthy food sources as well as area poverty rates and median household income. Population estimates were obtained from the 2015 5-year American Community Survey. Poisson regression models were used to calculate census tract-level incidence rates by FD status, as well as by food access and income categories, adjusting for age, sex, race, and income-by-access interaction. Results A total of 1,802 first-ever ischemic stroke incidents occurred in the region during the study period. Stroke patients had a mean age of 69.7 years, and 53% were female. In unadjusted models, FD residence (vs non-FD) was associated with higher stroke incidence (incidence rate ratio [IRR] 1.23; 95% CI 1.06-1.42; p < 0.01). After adjustment for age, sex, and race, this relationship was attenuated and no longer statistically significant (IRR 1.11; 95% CI 0.96-1.30; p = 0.17). In a model where FD status was replaced by area income and food access (i.e., the 2 components of the FD definition), low income was associated with greater stroke incidence after full adjustment (IRR 1.21; 95% CI 1.05-1.39; p = 0.01) while poor food access was not (IRR 0.91; 95% CI 0.81-1.01; p = 0.08). Discussion FD residents are at increased stroke risk, and this is primarily due to low area income rather than poor food access. Alternative measures of the food environment may help elucidate the links between income, dietary patterns, and stroke risk.

Introduction: Time from stroke symptom onset to emergency department (ED) arrival (OTA) is an important driver of acute stroke functional outcomes and mortality for both acute ischemic stroke (AIS) and intracerebral hemorrhage (ICH). Acute therapies for AIS are time-sensitive, and there are several recently published time-dependent therapeutic trials for ICH, yet little is known about the patterns of symptom onset to ED presentation over time. We sought to analyze trends and predictors of arrival times for AIS and ICH within the Greater Cincinnati/Northern Kentucky Stroke Study. Methods: Patients included those ≥20 years old with physician-adjudicated acute ischemic stroke (AIS) or intracerebral hemorrhage (ICH) from 2010, 2015 and 2020. Study nurses abstracted relevant information from the medical record, including symptom onset and ED arrival times. Median OTA time trends were analyzed for both AIS and ICH using quantile regression and the likelihood ratio test for year. Associations between demographic-, clinical-, and system-factors with early OTA times (less than 4.5 hours) were assessed using logistic regression, stratified by AIS and ICH stroke subtype. Results: There were 6466 AIS events and 950 ICH events among patients ≥20 years old who presented to an ED in the time periods studied. Among all patients with AIS, median age was 70 (IQR 59-82), 23% were black and 54% female, and median NIHSS was 3 (IQR 1-7). Median OTA time for all patients with AIS and onset time known was 483 minutes (IQR 105-1170), 30% arrived with an OTA time ≤4.5 hours, although median OTA times significantly increased over time (Figure 1). Among all patients with ICH, median age was 72 (IQR 58-82), 27% were black and 52% female, and median NIHSS was 7 (IQR 1-22). Median OTA time for patients with ICH and onset time known was 248 minutes (IQR 68-685), 42% arrived with an OTA time ≤4.5 hours, and median OTA times did not significantly change over time. EMS use, presenting symptoms of stroke, and greater stroke severity were associated with better arrival times whereas living alone was associated with worse times (Table 2). Discussion: Only 33% of AIS and 42% of ICH patients arrive to an emergency department within 4.5 hours of a known symptom onset. Several systems-level factors were associated with onset to arrival times. Understanding why symptom onset to ED arrival times are increasing over time is an important area for quality improvement.

Background: Prior literature has reported patterns of racial differences in percutaneous endoscopic gastrostomy (PEG) placement for patients with post-stroke dysphagia. Reasons for this disproportion are not well understood, but critical for clinical decision making. Long-term implications for PEG placement are considerable, given complication rates and that reducing oral intake can significantly impact recovery of swallow function. In this population-based study, we evaluated the influence of patient-related factors and stroke characteristics on PEG placement. Methods: All patients, 18 years or older, hospitalized with either ischemic or hemorrhagic stroke in Greater Cincinnati in 2010, 2015, and 2020 were considered for this study. Patients who died within 3 days or transferred to hospice care were not included. Demographics and clinical characteristics of Black and White individuals were compared. Multivariable logistic regression was then used to examine the association between Black race and PEG placement after adjustment for potential confounders. Univariable and multivariable logistic regression analysis (dependent = PEG) was used to determine influential factors for PEG placement. Patient and stroke characteristics between Black and Non-Black patients were compared using Chi-square tests, two-sample t-tests, or Wilcoxon rank-sum tests. Results: The final sample included 2315 cases, of whom 28.2% were Black (653/2315) and 54.1% were women (1254/2315). Black individuals with stroke were younger (p<0.0001), more likely to have a prior stroke (p=0.0003), had more severe strokes based upon NIHSS (p<.0001), were less likely to be treated at an academic center (p<0.0001), and were more likely to have a PEG placed (p>0.0001).Multivariable analysis revealed that Black race remained associated with PEG placement even after adjustment for potential confounders (aOR 1.47, 95% CI 1.15-1.87). Discussion: Black stroke patients are more likely to receive PEG, even after adjustment for potential confounders. Additional analyses are underway looking at potential influence of socioeconomic characteristics, patient comorbidities, and lesion location. Given the importance of clinical decision making for alternative access to nutrition and hydration, with the goal of recovery of swallowing function, future studies should examine influence of patient-specific factors including health literacy, familial support, and cultural/patient preferences.

Background: Ongoing surveillance of stroke incidence over time by demographic groups is critical to understand trends in disease burden and effective interventions. Our objective was to examine changes in stroke incidence by sex and age over 27 years. Methods: In a population-based stroke surveillance study covering a 5-county region of southern Ohio and northern Kentucky, hospital cases of stroke were ascertained and adjudicated by trained study physicians during six 1-year periods (07/1993–06/1994, 1999, 2005, 2010, 2015, 2020). Temporal trends in stroke incidence were evaluated by sex, age, and subtype (ischemic (IS), hemorrhagic (ICH), subarachnoid hemorrhage (SAH)). Stroke incidence rates per 100,000 people were calculated using U.S. Census data and age-, race-, and sex-standardized as appropriate. Trends in incidence over time were evaluated using linear regression, weighted with the inverse of the standard error of the estimated incidence rate. Female:male risk ratios (RRs) were reported in each of the study periods for the overall population stratified by age, and the trend over time was evaluated using linear regression using inverse weighting of the standard error. Results: 11,813 stroke events occurred in total, 56% in females and 20% in Black patients (Table 1). The trend over time for any stroke (IS, ICH, SAH or unknown) was not significant in females (208 [95%CI 195-221] in 1993/4 to 187 [95%CI 176-198] in 2020, per 100,000, p=0.06) or males (251 [95%CI 233-269] in 1993/4 to 220 [95%CI 207-234] in 2020, per 100,000, p=0.13). The decreasing trend in IS was significant in females (p=0.03) but not males (p=0.07). Trend in ICH was not significant in females (p=0.75) or males (p=0.06), and trend in SAH was not significant in either sex (all trend data in Figure 1). For female: male RRs for any stroke, overall (combined age groups) RRs ranged from 0.83 (95%CI 0.75-0.91) in 1993/4 to 0.97 (95%CI 0.88-1.06) in 2010; trend over time was not significant (p=0.82). RRs varied with age (2020 data in Figure 2) with a U-shaped relationship. Discussion: Over 27 years in a population-based stroke surveillance study, trends over time in any, IS, ICH, and SAH appear to be stabilizing with the only significant decrease seen in females with IS. Though findings suggest that previously reported decreasing incidence rates in stroke appear to be trending upward in 2020, future work is needed to understand the effect of COVID on 2020 rates and to continue surveillance.

Introduction: Recurrent stroke accounts for approximately 1/4 of all strokes and is associated with high morbidity and mortality. Glucagon-like peptide-1 receptor agonists (GLP-1), while originally developed to treat diabetes, have demonstrated efficacy in preventing cardiovascular events in overweight or obese (BMI>27) patients without diabetes. It is unknown whether these agents could also be useful for preventing recurrence in non-diabetic overweight or obese stroke patients. To guide potential trial planning, we sought to characterize the prevalence of overweight or obesity without diabetes among stroke patients and assess the recurrence rate in these patients at 3 years. Methods: Using the Greater Cincinnati/Northern Kentucky Stroke Study (GCNKSS) database from (2015), we identified adult patients with a diagnosis of acute ischemic stroke (AIS) or transient ischemic attack (TIA) and a BMI >27. Patients were separated into two groups based on whether they had a diagnosis of diabetes (either a prior history or a new diagnosis). Demographic information, premorbid mRS, stroke subtype, vascular risk factors and rate of stroke recurrence at 3 years were analyzed. We calculated Kaplan Meier estimates of 3-year recurrence in stroke patients with BMI>27 with and without diabetes. We used a log-rank test to test if there was a difference in the rate of recurrence between the two groups. Results: In 2015, of 3086 patients with an AIS or TIA, 3057 had BMI reported and 1644 (54%) with a BMI>27. 859 (52%) of these patients were female, 370 (23%) were Black, and 754 (46%) of these patients had a prior or new diagnosis of diabetes. Overweight or obese patients without diabetes differed from diabetics in race, baseline stroke severity, baseline disability, frequency of HTN and LVH, CAD, smoking and prior stroke. Unadjusted risk of recurrence in non-diabetic overweight or obese patients was 11% (95% CI: 8%, 15%) at 3 years, which was lower than the rate in diabetic overweight or obese of 20% (95% CI: 16%, 26%) (log-rank test p-value <0.01). Unadjusted survival free of stroke in non-diabetic overweight or obese patients was 71% (95% CI: 66%, 75%) at 3 years, which was higher than in diabetic overweight or obese patients of 59% (95% CI: 53%, 65%). Conclusion: Of all ischemic stroke and TIA patients, 29% have a BMI>27 without diabetes; these patients have a 3-year stroke recurrence rate of 11% and survival free of stroke of 71%. Clinical trials targeting this group are needed.

Introduction: Acute treatment for stroke often requires emergent interhospital transfer for access to advanced therapies not available at the initial hospital. Prolonged transfer times have been associated with worse outcomes. Door-in-door-out time (DIDO: the amount of time a patient spends in the transferring emergency department [ED]) is an important quality metric in acute stroke care, with current recommendations for DIDO times ≤ 120 minutes. We sought to characterize trends and predictors of DIDO times for interhospital stroke transfers using the Greater Cincinnati Northern Kentucky Stroke Study (GCNKSS). Methods: We utilized data from the GCNKSS, a population-based epidemiologic stroke study, from the following time points: 1999, 2005, 2010, 2015, and 2020. Patients ≥18 years with acute ischemic stroke (AIS) or hemorrhagic stroke (HS) who presented to an initial ED and were not admitted but were transferred to another hospital were included. The primary outcome was DIDO time. Temporal trends in DIDO time were tested using the Mann-Kendall trend test. Generalized linear mixed effects models with hospital-specific random intercepts were constructed to evaluate the associations between patient- and hospital-level covariates and DIDO time. Results: Of 13,678 stroke cases over the time periods studied, 1574 patients met inclusion criteria for the overall stroke group (mean age 64.7 [SD: 15.6], 51.6% female), with 851 (54.1%) having AIS and 723 (45.9%) HS. Over the time periods examined, the median DIDO time for the overall stroke group was 213 minutes (IQR 142-305), and DIDO times significantly increased over time (Figure 1; P<.0001). In the overall stroke group, hospital-level factors explained 4.0% of the variation in DIDO time. In the multiple regression model, factors associated with increased DIDO time included: history of prior stroke (+33.6 minutes; P<.0001) and receipt of MRI prior to transfer (+165.7 minutes; P<.0001); whereas EMS transport (-30.0 minutes; P<.001) and increasing NIHSS score (P<.0001) were associated with decreased DIDO time. Results were similar for AIS and HS subgroups (Table 2). Conclusions: In this population-based epidemiologic study, DIDO times exceeded recommended time targets and increased over time. Hospital-level factors accounted for only a minor proportion of the overall variation in DIDO times, suggesting that future quality improvement efforts should target modifiable clinical and systems factors to improve DIDO times.

Background: The Early MiNimally-Invasive Removal of ICH (ENRICH) trial established minimally invasive surgical evacuation as an effective therapy for acute, spontaneous, lobar intracerebral hemorrhage (ICH). We aimed to estimate the annual number of US patients in 2020 eligible for minimally invasive hematoma evacuation by extrapolating Greater Cincinnati Northern Kentucky (GCNK) Stroke Study epidemiologic data to US census data. Methods: We ascertained all adults ( > 18 years) with acute (<24 hours from last known well), spontaneous ICH presenting to the ED in GCNK in 2015. Cases were identified by ICD codes, clinical data abstracted, and physician adjudicated. The location and volume of ICH was centrally adjudicated by neuroradiologists. We calculated conservative and liberal estimates of the number of GCNK patients with acute, spontaneous, lobar ICH that met ENRICH trial eligibility for minimally invasive surgical evacuation. Lobar ICH was analyzed separately given the benefit of surgical hematoma evacuation was attributable to intervention for lobar ICH in ENRICH. Conservative estimates considered all clinically relevant ENRICH trial eligibility criteria. Liberal estimates removed anticoagulant use as exclusion criterion because these patients were included in ENRICH if coagulopathy was rapidly reversed. The derived estimates of ENRICH eligible patients were then extrapolated to the 2020 US adult population using characteristics of ICH patients in GCNK and 2020 US census data. Results: Over the 2015 GCNK study period, 197 patients with acute, spontaneous ICH were identified (median age 74, 55% female, 28% Black). In conservative estimates applying all clinically relevant ENRICH criteria, 5.7% (n=6) of lobar ICH patients were eligible for minimally invasive surgical evacuation. Including those on anticoagulants resulted in 6.7% (n=7) of lobar ICH patients being eligible for minimally invasive surgical evacuation. After extrapolation to the 2020 US population, of an estimated 96,120 ICH cases in 2020, we calculated that 1,972 (conservative) to 2,318 (liberal) patients with acute lobar ICH would be eligible for minimally invasive surgical evacuation based on ENRICH eligibility criteria (Figure 1). Conclusion: It is estimated that 1,972-2,318 acute, spontaneous, lobar ICH patients in the US in 2020 met eligibility for minimally invasive surgical hematoma evacuation. US stroke systems of care should be designed to meet the demand for this new therapy.

Background: Our primary objective was to evaluate if disparities in race, sex, age, and socioeconomic status (SES) exist in utilization of advanced neuroimaging in year 2015 in a population-based study. Our secondary objective was to identify the disparity trends and overall imaging utilization as compared with years 2005 and 2010. Methods: This was a retrospective, population-based study that utilized the GCNKSS (Greater Cincinnati/Northern Kentucky Stroke Study) data. Patients with stroke and transient ischemic attack were identified in the years 2005, 2010, and 2015 in a metropolitan population of 1.3 million. The proportion of imaging use within 2 days of stroke/transient ischemic attack onset or hospital admission date was computed. SES determined by the percentage below the poverty level within a given respondent’s US census tract of residence was dichotomized. Multivariable logistic regression was used to determine the odds of advanced neuroimaging use (computed tomography angiogram/magnetic resonance imaging/magnetic resonance angiogram) for age, race, gender, and SES. Results: There was a total of 10 526 stroke/transient ischemic attack events in the combined study year periods of 2005, 2010, and 2015. The utilization of advanced imaging progressively increased (48% in 2005, 63% in 2010, and 75% in 2015 [P<0.001]). In the combined study year multivariable model, advanced imaging was associated with age and SES. Younger patients (≤55 years) were more likely to have advanced imaging compared with older patients (adjusted odds ratio, 1.85 [95% CI, 1.62–2.12]; P<0.01), and low SES patients were less likely to have advanced imaging compared with high SES (adjusted odds ratio, 0.83 [95% CI, 0.75–0.93]; P<0.01). A significant interaction was found between age and race. Stratified by age, the adjusted odds of advanced imaging were higher for Black patients compared with White patients among older patients (>55 years; adjusted odds ratio, 1.34 [95% CI, 1.15–1.57]; P<0.01), but no racial differences among the young. Conclusions: Racial, age, and SES-related disparities exist in the utilization of advanced neuroimaging for patients with acute stroke. There was no evidence of a change in trend of these disparities between the study periods.

Background: Ischemic stroke is the 5 th leading cause of death in the US. As a measure of stroke severity, initial NIHSS has been used to predict clinical outcome. We sought to identify the optimal cut-points of NIHSS at initial presentation that are associated with higher 30-day mortality. Methods: In 2005, 2010, and 2015 all hospitalized, first acute ischemic stroke events occurring within the Greater Cincinnati area were ascertained. Potential ischemic stroke cases underwent chart abstraction and physician adjudication, including retrospective NIHSS score (range 0 - 42) based on clinical findings at initial presentation. Descriptive statistics for NIHSS were estimated by study year, demographics, and medical history. Data regarding mortality was obtained from the National Death Index. The Contal and O’Quigley method based on a modified log-rank test statistic was used to determine cut-points of the NIHSS score associated with 30-day mortality, and hazard ratios were obtained from Cox models with adjustment for sex, race, and age. Results: In 2005, 2010, and 2015 there were 1704, 1818 and 1852 ischemic stroke events with 30-day mortality rates of 10.5%, 9.6% and 9.0%, respectively. Optimal cut-points of NIHSS <9, 9-16 and >16 were identified. Across all 3 periods, 3431 (84.5%) cases had NIHSS 0-8, 352 (8.7%) had NIHSS 9-16 and 274 (6.8%) >16. Kaplan Meier Survival Curves for the 3 NIHSS groups are shown in the Figure. Strokes with NIHSS >16 at initial presentation were associated with a 15-fold (HR with 95% CI: 13, 19) increase in the risk of death at 30-days compared to those with NIHSS <9. Discussion: NIH Stroke Scale scores are a reliable predictor of mortality, with higher NIHSS scores having higher risk of death. The cut points reported identify subgroups of stroke patients with dramatically different prognoses. Future studies should assess if this excess mortality risk among severe strokes persists after the more widespread implementation of thrombectomy beyond 2015.