Factors associated with fatal stroke in glioma patients: a population analysis

ImportanceBrain tumour patients have the highest stroke mortality rates among all cancer types, but the factors associated with fatal stroke in brain tumour remain unknown.ObjectiveWe aimed to examine to what extent brain tumour grade, a marker of biological aggressiveness, tumour size and cancer treatment each associated with stroke mortality in glioma. Gliomas include the most common malignant types of brain cancer.Design, setting, participantsA retrospective, observational cohort study using the US National Cancer Institute’s Surveillance Epidemiology and End Results program. We identified adult patients with a primary diagnosis of malignant gliomas in 2000 to 2018 (N=72,252). The primary outcome of interest was death from cerebrovascular disease. Adjusted hazard ratio (aHR) and 95% confidence interval (CI) were calculated using cause-specific Cox regression model to determine associations with tumour characteristics: grades II-IV, tumour size and cancer treatment (surgery, radiotherapy, chemotherapy) associated with stroke mortality after adjustment for age, sex, race, marital status and calendar years.ResultsIn patients with glioma, increased risk for stroke mortality was observed in patients with higher grade (Grade III: aHR=1.19, 95% CI=0.88-1.61, p>0.05; Grade IV: aHR=1.94, 95% CI=1.39-2.71 compared to Grade II, p<0.001), and those with larger brain tumours (size=3-6 cm: aHR=1.93, 95%CI 1.31 -2.85, p<0.001, size>9cm: aHR=2.07, 95% CI=1.40-3.06, p<0.001 compared to size < 3cm). Having treatment was associated with decreased risk: surgery (yes VS no: aHR= 0.65; p<0.01), radiation (yes VS no: aHR= 0.66, p<0.01), chemotherapy (yes VS no: aHR=0.49, p<0.001).ConclusionsHigher grade and tumour size are strongly associated with increased stroke mortality. This implicates tumour biology and/or the systemic tumour response which require further investigation in prospective studies to determine strategies to mitigate this risk.

Examining the Drivers of Racial/Ethnic Disparities in Non-Adherence to Antihypertensive Medications and Mortality Due to Heart Disease and Stroke: A County-Level Analysis

Background: Prior research has identified disparities in anti-hypertensive medication (AHM) non-adherence between Black/African Americans (BAAs) and non-Hispanic Whites (nHWs) but the role of determinants of health in these gaps is unclear. Non-adherence to AHM may be associated with increased mortality (due to heart disease and stroke) and the extent to which such associations are modified by contextual determinants of health may inform future interventions. Methods: We linked the Centers for Disease Control and Prevention (CDC) Atlas of Heart Disease and Stroke (2014–2016) and the 2016 County Health Ranking (CHR) dataset to investigate the associations between AHM non-adherence, mortality, and determinants of health. A proportion of days covered (PDC) with AHM < 80%, was considered as non-adherence. We computed the prevalence rate ratio (PRR)—the ratio of the prevalence among BAAs to that among nHWs—as an index of BAA–nHW disparity. Hierarchical linear models (HLM) were used to assess the role of four pre-defined determinants of health domains—health behaviors, clinical care, social and economic and physical environment—as contributors to BAA–nHW disparities in AHM non-adherence. A Bayesian paradigm framework was used to quantify the associations between AHM non-adherence and mortality (heart disease and stroke) and to assess whether the determinants of health factors moderated these associations. Results: Overall, BAAs were significantly more likely to be non-adherent: PRR = 1.37, 95% Confidence Interval (CI):1.36, 1.37. The four county-level constructs of determinants of health accounted for 24% of the BAA-nHW variation in AHM non-adherence. The clinical care (β = −0.21, p < 0.001) and social and economic (β = −0.11, p < 0.01) domains were significantly inversely associated with the observed BAA–nHW disparity. AHM non-adherence was associated with both heart disease and stroke mortality among both BAAs and nHWs. We observed that the determinants of health, specifically clinical care and physical environment domains, moderated the effects of AHM non-adherence on heart disease mortality among BAAs but not among nHWs. For the AHM non-adherence-stroke mortality association, the determinants of health did not moderate this association among BAAs; the social and economic domain did moderate this association among nHWs. Conclusions: The socioeconomic, clinical care and physical environmental attributes of the places that patients live are significant contributors to BAA–nHW disparities in AHM non-adherence and mortality due to heart diseases and stroke.

Persistent hyperglycemia is a useful glycemic pattern to predict stroke mortality: a systematic review and meta-analysis

Background Glycemic patterns have been reported to be prognostic factors for stroke; however, this remains to be further evaluated. This meta-analysis aimed to evaluate the usefulness of glycemic patterns such as persistent hyperglycemia (PH) including short duration and long duration PH (SPH; LPH), admission hyperglycemia (AH), short-duration hyperglycemia (SH), and persistent normoglycemia (PN) in predicting stroke prognosis using published results. Methods Major scientific databases including but are not limited to PubMed, EMBASE, Web of Science, Ovid, CNKI (Chinese National Knowledge Infrastructure), and Clinicaltrials.gov were searched till 1st March 2021 for clinical trials on the correlation between glycemic patterns and stroke outcomes. The primary outcome was defined as short-term (1- or 3-month) post-stroke mortality, and the secondary outcome was post-stroke hemorrhage at 6 months. Results Ten studies involving 3584 individuals were included in the final analysis. In subgroup analyses, PH patients with no history of diabetes had increased post-stroke mortality (odds ratio [OR]: 4.80, 95% CI: 3.06–7.54) than patients with no PH; and patients with glucose levels > 140 mg/dl had greater mortality (OR: 5.12, 95% CI: 3.21–8.18) than those with glucose levels < 140 mg/dl; compared with AH patients, PH patients had increased short-term mortality (OR: 0.31, 95% CI: 0.16–0.60). In the prediction of stroke mortality among patients without diabetes, SPH (OR: 0.28, 95%CI: 0.12–0.69) seemed to be more related to increased mortality than LPH (OR: 0.35, 95% CI: 0.14–-0.90). Conclusions PH, especially SPH, could predict increased post-stroke mortality in non-diabetic patients. The rank of individual glycemic patterns in predicting stroke mortality in non-diabetic patients was SPH > LPH > AH > PN.

Low Blood Pressure, Comorbidities, and Ischemic Stroke Mortality in US Veterans

Background and Purpose: Low blood pressure (BP) is associated with higher stroke mortality, although the factors underlying this association have not been fully explored. We investigated prestroke BP and long-term mortality after ischemic stroke in a national sample of US veterans. Methods: Using a retrospective cohort study design of veterans hospitalized between 2002 and 2007 with a first ischemic stroke and with ≥1 outpatient BP measurements 1 to 18 months before admission, we defined 6 categories each of average prestroke systolic BP (SBP) and diastolic BP, and 7 categories of pulse pressure. Patients were followed-up to 12 years for primary outcomes of all-cause and cardiovascular mortality. We used Cox models to relate prestroke BP indices to mortality and stratified analyses by the presence of preexisting comorbidities (smoking, myocardial infarction, heart failure, atrial fibrillation/flutter, cancer, and dementia), race and ethnicity. Results: Of 29 690 eligible veterans with stroke (mean±SD age 67±12 years, 98% men, 67% White), 2989 (10%) had average prestroke SBP<120 mm Hg. During a follow-up of 4.1±3.3 years, patients with SBP<120 mm Hg experienced 61% all-cause and 27% cardiovascular mortality. In multivariable analyses, patients with the lowest SBP, lowest diastolic BP, and highest pulse pressure had the highest mortality risk: SBP<120 versus 130 to 139 mm Hg (hazard ratio=1.26 [95% CI, 1.19–1.34]); diastolic BP <60 versus 70 to 79 mm Hg (hazard ratio=1.35 [95% CI, 1.23–1.49]); and pulse pressure ≥90 versus 60 to 69 mm Hg (hazard ratio=1.24 [95% CI, 1.15–1.35]). Patients with average SBP<120 mm Hg and at least one comorbidity (smoking, heart disease, cancer, or dementia) had the highest mortality risk (hazard ratio=1.45 [95% CI, 1.37–1.53]). Conclusions: Compared with normotension, low prestroke BP was associated with mortality after stroke, particularly among patients with at least one comorbidity.

Abstract 1122‐000163: Stroke Center Accessibility Study in the U.S. Using Geospatial Analysis and Machine Learning

Introduction : Background: Several accrediting bodies certify the level of stroke care hospitals provide. The Joint Commission on Hospital Accreditation (JC) is the largest accrediting body in the United States. There is no open source Geographic Information Systems (GIS) dataset showing the distribution of JC accredited centers by ZIP code. Objective: to create a stroke center accessibility and stroke center desert system using geospatial analysis and machine learning which provides real‐time assessment of stroke center availability, distribution and access to care. Methods : Geospatial data layers of JC accredited stroke centers were compiled using data sources including U.S. Census Bureau and CDC. Map layers corresponding to the levels of JC accredited stroke hospitals geolocated using ZIP code were created as follows: 1) Acute Stroke Ready 2) Primary 3) Thrombectomy Capable 4) Comprehensive Stroke Center. A GIS dataset displaying stroke mortality by region was obtained from the ArcGIS Living Atlas. Stroke center deserts are analyzed using a 4.5 hour drive map along with population and diversity. Machine learning models were implemented to estimate stroke mortality as a function of distance to care centers and capability levels of the stroke centers. Results : Stroke centers are highly concentrated within large urban centers. There are geographic regions that have poor access to stroke centers. Such regions include the Gulf Coast States of Louisiana, Mississippi, and Alabama that have large areas with poor stroke center access while having some of the highest stroke mortality in the country. (Figure 1 ‐ Stroke Center Distribution in the United States) Dot Symbols: Blue = Acute Stroke Ready; Green = Primary; Yellow = Thrombectomy Capable; Red = Comprehensive Raster Data: Stroke Mortality by ZIP Code; White to Purple Scale with Purple = Highest Mortality Conclusions : There are regional variations in stroke center availability. There are certain regions with high stroke mortality with very little stroke center access. Geospatial AI tools can be utilized to improve stroke systems of care.

P.076 Hypertensive disorders in pregnancy are strongly associated with future stroke and hypertension: A systematic review and meta-analysis

Background: We aimed to evaluate the association between hypertensive disorders in pregnancy (HDP) and future risk of stroke, stroke death, and hypertension. Methods: Systematic searches were performed in MEDLINE and EMBASE up to April 27th, 2020. Exposure of interest included the different types of HDP. Outcomes of interest included hypertension incidence, stroke incidence, stroke subtype, and stroke mortality. Results: Eighteen cohort and 1 case-control studies involving >10 million women were included in the meta-analysis. Pooled hazard ratios with 95% confidence interval generally adjusted for age at delivery, ethnicity, and vascular risk factors are listed in table 1. Conclusions: Increasing severities of HDP carry higher hazards of hypertension and stroke years later. HDP, including gestational hypertension alone, are also associated with future stroke mortality.