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Is there a correlation between socioeconomic disparity and functional outcome after acute ischemic stroke?

ABSTRACT: To investigate the impact of low socioeconomic status (SES), indicated by low level of education, occupation and income, on 3 months functional outcome after ischemic stroke.We analyzed data from the China National Stroke Registry (CNSR), a multicenter and prospective registry of consecutive patients with acute cerebrovascular events occurred between September 2007 and August 2008. 11226 patients with ischemic stroke had SES and clinical characteristics data collected at baseline and mRS measured as indicator of functional outcome in 3 months follow up. Multinomial and ordinal logistic regression models were performed to examine associations between SES and the functional outcome.At 3 months after stroke, 5.3% of total patients had mRS scored at 5, 11.3% at score 4, 11.1% at score 3, 14.4% at score 2, 34.2% at score 1 and 23.7% at score 0. Compared to patients with educational level of ? 6 years and non-manual laboring, those < 6 years and manual laboring tended to have higher mRS score (P<0.001). Multinomial adjusted odds ratios (ORs) of outcome in manual workers were significantly increased (ORs from1.38 to 1.87), but OR in patients with less income was not significant. There were similar patterns of association The impact may be stronger in patients aged <65 years (P = 0.003, P<0.001 respectively) and being male (P = 0.001, P<0.001 respectively).Our study provides evidence that people who are relatively more deprived in socioeconomic status suffer poorer outcome after ischemic stroke. The influence of low educational level and manual laboring can be more intensive than low income level on 3-month outcome. Health policy and service should target the deprived populations to reduce the public health burden in the society.

SUBMITTER: Song T

PROVIDER: S-EPMC5528884 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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Is there a correlation between socioeconomic disparity and functional outcome after acute ischemic stroke?

Song Tian T Pan Yuesong Y Chen Ruoling R Li Hao H Zhao Xingquan X Liu Liping L Wang Chunxue C Wang Yilong Y Wang Yongjun Y

PloS one 20170726 7

<h4>Background</h4>To investigate the impact of low socioeconomic status (SES), indicated by low level of education, occupation and income, on 3 months functional outcome after ischemic stroke.<h4>Methods</h4>We analyzed data from the China National Stroke Registry (CNSR), a multicenter and prospective registry of consecutive patients with acute cerebrovascular events occurred between September 2007 and August 2008. 11226 patients with ischemic stroke had SES and clinical characteristics data co ...[more]

PMID: 28746347

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Project description:Background and purpose: Previous studies have shown that Hypoperfusion Intensity Ratio (HIR) derived from Perfusion Imaging (PWI) associated with collateral status in large-vessel occlusion (LVO) acute ischemic stroke (AIS) and could predict the rate of collateral flow, speed of infarct growth, and clinical outcome after endovascular treatment (EVT). We hypothesized that HIR derived from CT Perfusion (CTP) imaging could relatively accurately predict the functional outcome in LVO AIS patients receiving different types of treatment. Methods: Imaging and clinical data of consecutive patients with LVO AIS were retrospectively reviewed. Multi-phase CT angiography (mCTA) scoring was performed by 2 blinded neuroradiologists. CTP images were processed using an automatic post-processing analysis software. Correlation between the HIR and the functional outcome was calculated using the Spearman correlation. The efficacy of the HIR and the CTA collateral scores for predicting prognosis were compared. The optimal threshold of the HIR for predicting favorable functional outcome was determined using receiver operating characteristic (ROC) curve analysis. Results: 235 patients with LVO AIS were included. Patients with favorable functional outcome had lower HIR (0.1 [interquartile range (IQR), 0.1-0.2]) vs. 0.4 (IQR, 0.4-0.5)) and higher mCTA collateral scores (3 [IQR, 3-4] vs. 3 [IQR, 2-3]; p < 0.001) along with smaller infarct core volume (2.1 [IQR, 1.0-4.5]) vs. (15.2 [IQR, 5.5-39.3]; p < 0.001), larger mismatch ratio (22.9 [IQR, 11.6-45.6]) vs. (5.8 [IQR, 2.6-14]); p < 0.001), smaller ischemic volume (59.0 [IQR, 29.7-89.2]) vs. (97.5 [IQR, 68.7-142.2]; p < 0.001), and smaller final infarct volume (12.6 [IQR, 7.5-18.4]) vs. (78.9 [IQR, 44.5-165.0]; p < 0.001) than those with unfavorable functional outcome. The HIR was significantly positively correlated with the functional outcome [r = 0.852; 95% confidence interval (CI): 0.813-0.884; p < 0.0001]. The receiver operating characteristic (ROC) analysis showed that the optimal threshold for predicting a favorable functional outcome was HIR ≤ 0.3 [area under the curve (AUC) 0.968; sensitivity 88.89%; specificity 99.21%], which was higher than the mCTA collateral score [AUC 0.741; sensitivity 82.4%; specificity 48.8%]. Conclusions: HIR was associated with the functional outcome of LVO AIS patients, and the correlation coefficient was higher than mCTA collateral score. HIR outperformed mCTA collateral score in predicting functional outcome.

Project description:BackgroundMixed data exist regarding the association between hyperglycemia and functional outcome after acute ischemic stroke when accounting for the impact of leptomeningeal collateral flow. We sought to determine whether collateral status modifies the association between treatment group and functional outcome in a subset of patients with large vessel occlusion enrolled in the Stroke Hyperglycemia Insulin Network Effort (SHINE) trial.MethodsIn this post-hoc analysis, we analyzed patients enrolled into the SHINE trial with anterior circulation large vessel occlusion who underwent imaging with CT angiography prior to glucose control treatment group assignment. The primary analysis assessed the degree to which collateral status modified the effect between treatment group and functional outcome as defined by the 90-day modified Rankin Scale score. Logistic regression was used to model the data, with adjustments made for thrombectomy status, age, post-perfusion thrombolysis in cerebral infarction (TICI) score, tissue plasminogen activator (tPA) use, and baseline National Institutes of Health Stroke Scale (NIHSS) score. Five SHINE trial centers contributed data for this analysis. Statistical significance was defined as a p-value < 0.05.ResultsAmong the 1151 patients in the SHINE trial, 57 with angiographic data were included in this sub-analysis, of whom 19 had poor collaterals and 38 had good collaterals. While collateral status had no effect (p = 0.855) on the association between glucose control treatment group and functional outcome, patients with good collaterals were more likely to have a favorable functional outcome (p = 0.001, OR 5.02; 95% CI 1.37-16.0).ConclusionsIn a post-hoc analysis using a subset of patients with angiographic data enrolled in the SHINE trial, collateral status did not modify the association between glucose control treatment group and functional outcome. However, consistent with prior studies, there was a significant association between good collateral status and favorable outcome in patients with large vessel occlusion stroke.Trial registrationClinicalTrials.gov Identifier is NCT01369069. Registration date is June 8, 2011.

Project description:Currently, few studies are reported on the composition of microbiota in stroke patients and the association with stroke prognosis. This study investigated the differing microbiota composition in stroke patients and confirmed the association of microbiota composition with poor functional outcome. Between January of 2018 and December of 2019, 198 patients with acute cerebral infarction were included in this study. For the case-control study, age and sex-matched normal healthy subjects (n = 200) were included when receiving their health screening examinations. We isolated bacterial extracellular membrane vesicles and extracted DNA from blood samples. Taxonomic assignments were performed by using the sequence reads of 16S rRNA genes following blood microbiota analysis. Statistical analysis was conducted appropriately by using Statistical Analysis System software. The mean age of the stroke patients were 63.7 ± 12.5 years, and the male sex was 58.5%. Of the total enrolled patients, poor functional outcome (modified Rankin Score ≥ 3) was noted in 19.7%. The principal component analysis of microbiota composition revealed significant differences between healthy control subjects and stroke patients. At the genus level, Aerococcaceae(f), ZB2(c), TM7-1(c), and Flavobacterium were significantly increased in stroke patients compared to the healthy controls, whereas Mucispirillum, rc4-4, Akkermansia, Clostridiales(o), Lactobacillus, and Stenotrophomonas were decreased considerably. For the functional outcome after ischemic stroke, Anaerococcus, Blautia, Dialister, Aerococcaceae(f), Propionibacterium, Microbacteriaceae(f), and Rothia were enriched in the group with good outcomes, whereas Ruminococcaceae(f) and Prevotella were enriched in the group with poor outcome. There was apparent dysbiosis of blood microbiota in patients with acute ischemic stroke compared to healthy people. Ruminococcaceae(f) and Prevotella were elevated in stroke patients with poor functional outcome.

Project description:ImportanceLong-term disability after stroke is associated with socioeconomic status (SES). However, the reasons for such disparities in outcomes remain unclear.ObjectiveTo assess whether lower SES is associated with larger admission infarct volume and whether initial infarct volume accounts for the association between SES and long-term disability.Design, setting, and participantsThis cohort study was conducted in a prospective, consecutive population (n = 1256) presenting with acute ischemic stroke who underwent magnetic resonance imaging (MRI) within 24 hours of admission. Patients were recruited in Massachusetts General Hospital, Boston, from May 31, 2009, to December 31, 2011. Data were analyzed from May 1, 2019, until June 30, 2020.Main outcomes and measuresInitial stroke severity (within 24 hours of presentation) was determined using clinical (National Institutes of Health Stroke Scale [NIHSS]) and imaging (infarct volume by diffusion-weighted MRI) measures. Stroke etiologic subtypes were determined using the Causative Classification of Ischemic Stroke algorithm. Long-term stroke disability was measured using the modified Rankin Scale. Socioeconomic status was estimated using zip code-derived median household income and census block group-derived area deprivation index (ADI). Regression and mediation analyses were performed.ResultsA total of 1098 patients had imaging and SES data available (mean [SD] age, 68.1 [15.7] years; 607 men [55.3%]). Income was inversely associated with initial infarct volume (standardized β, -0.074 [95% CI, -0.127 to -0.020]; P = .007), initial NIHSS (standardized β, -0.113 [95% CI, -0.171 to -0.054]; P < .001), and long-term disability (standardized β, -0.092 [95% CI, -0.149 to -0.035]; P = .001), which remained significant after multivariable adjustments. Initial stroke severity accounted for 64% of the association between SES and long-term disability (standardized β, -0.063 [95% CI, -0.095 to -0.029]; P < .05). Findings were similar when SES was alternatively assessed using ADI.Conclusions and relevanceThe findings of this cohort study suggest that lower SES is associated with larger infarct volumes on presentation. These SES-associated differences in initial stroke severity accounted for most of the subsequent disparities in long-term disability in this study. These findings shift the culpability for SES-associated disparities in poststroke disability from poststroke factors to those that precede presentation.

Project description:Background and Purpose- The ability to model long-term functional outcomes after acute ischemic stroke represents a major clinical challenge. One approach to potentially improve prediction modeling involves the analysis of connectomics. The field of connectomics represents the brain's connectivity as a graph, whose topological properties have helped uncover underlying mechanisms of brain function in health and disease. Specifically, we assessed the impact of stroke lesions on rich club organization, a high capacity backbone system of brain function. Methods- In a hospital-based cohort of 41 acute ischemic stroke patients, we investigated the effect of acute infarcts on the brain's prestroke rich club backbone and poststroke functional connectomes with respect to poststroke outcome. Functional connectomes were created using 3 anatomic atlases, and characteristic path-length (L) was calculated for each connectome. The number of rich club regions affected were manually determined using each patient's diffusion weighted image. We investigated differences in L with respect to outcome (modified Rankin Scale score; 90 days) and the National Institutes of Health Stroke Scale (NIHSS; early: 2-5 days; late: 90-day follow-up). Furthermore, we assessed the effect of including number of rich club regions and L in outcome models, using linear regression and assessing the explained variance (R2). Results- Of 41 patients (mean age [range]: 70 [45-89] years), 61% were male. Lower L was generally associated with better outcome. Including number of rich club regions in the backward selection models of outcome, R2 increased between 1.3- and 2.6-fold beyond that of traditional markers (age and acute lesion volume) for NIHSS and modified Rankin Scale score. Conclusions- In this proof-of-concept study, we showed that information on network topology can be leveraged to improve modeling of poststroke functional outcome. Future studies are warranted to validate this approach in larger prospective studies of outcome prediction in stroke.

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Is there a correlation between socioeconomic disparity and functional outcome after acute ischemic stroke?

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Is there a correlation between socioeconomic disparity and functional outcome after acute ischemic stroke?

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