Dataset Information

Neighborhood Differences in Post-Stroke Mortality.

ABSTRACT: BACKGROUND:Post-stroke mortality is higher among residents of disadvantaged neighborhoods, but it is not known whether neighborhood inequalities are specific to stroke survival or similar to mortality patterns in the general population. We hypothesized that neighborhood disadvantage would predict higher poststroke mortality, and neighborhood effects would be relatively larger for stroke patients than for individuals with no history of stroke. METHODS AND RESULTS:Health and Retirement Study participants aged ?50 years without stroke at baseline (n=15?560) were followed ?12 years for incident stroke (1715 events over 159?286 person-years) and mortality (5325 deaths). Baseline neighborhood characteristics included objective measures based on census tracts (family income, poverty, deprivation, residential stability, and percent white, black, or foreign-born) and self-reported neighborhood social ties. Using Cox proportional hazard models, we compared neighborhood mortality effects for people with versus people without a history of stroke. Most neighborhood variables predicted mortality for both stroke patients and the general population in demographic-adjusted models. Neighborhood percent white predicted lower mortality for stroke survivors (hazard ratio, 0.75 for neighborhoods in highest 25th percentile versus below, 95% confidence interval, 0.62-0.91) more strongly than for stroke-free adults (hazard ratio, 0.92; 95% confidence interval, 0.83-1.02; P=0.04 for stroke-by-neighborhood interaction). No other neighborhood characteristic had different effects for people with versus without stroke. Neighborhood-mortality associations emerged within 3 months after stroke, when associations were often stronger than among stroke-free individuals. CONCLUSIONS:Neighborhood characteristics predict mortality, but most effects are similar for individuals without stroke. Eliminating disparities in stroke survival may require addressing pathways that are not specific to traditional poststroke care.

SUBMITTER: Osypuk TL

PROVIDER: S-EPMC5328121 | biostudies-literature | 2017 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Neighborhood Differences in Post-Stroke Mortality.

Osypuk Theresa L TL Ehntholt Amy A Moon J Robin JR Gilsanz Paola P Glymour M Maria MM

Circulation. Cardiovascular quality and outcomes 20170222 2

<h4>Background</h4>Post-stroke mortality is higher among residents of disadvantaged neighborhoods, but it is not known whether neighborhood inequalities are specific to stroke survival or similar to mortality patterns in the general population. We hypothesized that neighborhood disadvantage would predict higher poststroke mortality, and neighborhood effects would be relatively larger for stroke patients than for individuals with no history of stroke.<h4>Methods and results</h4>Health and Retirem ...[more]

PMID: 28228449

Similar Datasets

Project description:IntroductionControversies remain on whether post-stroke complications represent an independent predictor of poor outcome or just a reflection of stroke severity. We aimed to identify which post-stroke complications have the highest impact on in-hospital mortality by using machine learning techniques. Secondary aim was identification of patient's subgroups in which complications have the highest impact.Patients and methodsRegistro Nacional de Ictus de la Sociedad Española de Neurología is a stroke registry from 42 centers from the Spanish Neurological Society. Data from ischemic stroke patients were used to build a random forest by combining 500 classification and regression trees, to weight up the impact of baseline characteristics and post-stroke complications on in-hospital mortality. With the selected variables, a logistic regression analysis was performed to test for interactions.Results12,227 ischemic stroke patients were included. In-hospital mortality was 5.9% and median hospital stay was 7(4-10) days. Stroke severity [National Institutes of Health Stroke Scale > 10, OR = 5.54(4.55-6.99)], brain edema [OR = 18.93(14.65-24.46)], respiratory infections [OR = 3.67(3.02-4.45)] and age [OR = 2.50(2.07-3.03) for >77 years] had the highest impact on in-hospital mortality in random forest, being independently associated with in-hospital mortality. Complications have higher odds ratios in patients with baseline National Institutes of Health Stroke Scale <10.DiscussionOur study identified brain edema and respiratory infections as independent predictors of in-hospital mortality, rather than just markers of more severe strokes. Moreover, its impact was higher in less severe strokes, despite lower frequency.ConclusionBrain edema and respiratory infections were the complications with a greater impact on in-hospital mortality, with the highest impact in patients with mild strokes. Further efforts on the prediction of these complications could improve stroke outcome.

Project description:Background and objectivesPost-stroke epilepsy (PSE) is a significant concern in the elderly population, with stroke being a leading cause of epilepsy in this demographic. Several factors have shown consistent associations with the risk of developing PSE, including cortical lesions, initial stroke severity, younger age, and the occurrence of early seizures. The primary objectives of this study were two-fold: (1) to determine the incidence of PSE and (2) to identify the risk factors associated with PSE in a prospective cohort of post-stroke patients.MethodsA prospective single-hospital study was conducted, involving patients diagnosed with acute ischemic and hemorrhagic stroke. The patients were followed up for 2 years (or until death) from the time of admission. Data about seizure occurrence and recurrent stroke were collected. Kaplan-Meyer curves were used for the assessment of PSE incidence and mortality. Possible predictors of PSE and mortality were selected from between-group analysis and tested in multivariable regressions.ResultsOur study enrolled a total of 424 patients diagnosed with acute stroke. Among them, 97 cases (23%) experienced early post-stroke seizures, and 28 patients (6.6%) developed PSE. The cumulative risks of developing PSE were found to be 15.4% after hemorrhagic stroke and 8.7% after ischemic stroke. In multivariable fine and gray regression with competitive risk of death, significant predictors for developing PSE in the ischemic cohort were watershed infarction (HR 6.01, 95% CI 2.29-15.77, p < 0.001) and low Barthel index at discharge (HR 0.98, CI 0.96-0.99, p = 0.04). Furthermore, patients who eventually developed PSE showed slower recovery and presented a worse neurologic status at the time of discharge. The in-hospital dynamics of the National Institutes of Health Stroke Scale (NIHSS) were significantly worse in the PSE group compared to the non-PSE group (p = 0.01).DiscussionA higher proportion of cases experienced early seizures compared to what has been commonly reported in similar studies. Watershed stroke and low Barthel index at discharge were both identified as independent risk factors of PSE in ischemic strokes, which sheds light on the underlying mechanisms that may predispose individuals to post-stroke epilepsy after experiencing an ischemic stroke.

Dataset Information

Neighborhood Differences in Post-Stroke Mortality.

Publications

Neighborhood Differences in Post-Stroke Mortality.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets