Sex differences in causes of death after stroke: evidence from a national, prospective registry

Background: We examined sex differences in cause of death and cause-specific excess mortality after stroke.Materials and Methods: First-ever strokes (2010-2013; 35 hospitals) participating in the Australian Stroke Clinical Registry were linked to national death registrations and other administrative datasets. One-year cause-specific mortality was categorized as stroke, ischemic heart disease, other cardiovascular disease (CVD; e.g., hypertension), cancer, and other. Specific hazard ratios (sHRs) of death for women compared to men were estimated using competing risk models, with adjustment for factors differing by sex (e.g., age and stroke severity). Age- and sex-specific mortality rates expected in the general population were derived from national data. Standardized mortality ratios (SMRs; observed/expected deaths) were estimated for cause-specific mortality by sex after age standardization.Results: Among 9,441 cases (46% women), women were 7 years older than men, had more severe strokes, and received similar patterns of suboptimal secondary prevention medications at discharge. Women had greater mortality associated with stroke (sHRunadjusted 1.65) and other CVD (sHRunadjusted 1.65), which was related to age and stroke severity rather than other factors. Compared to population norms, those surviving to 30 days had eight-fold increased mortality from stroke (primary/recurrent) events irrespective of sex (SMRage-standardised women 8.8; men 8.3). Excess mortality from other CVD was greater in women (SMRage-standardised 3.6 vs. men 2.8; p = 0.026).Conclusions: Cause-specific mortality after first-ever stroke differs by sex. The greater death rate attributed to stroke/other CVD in women was mostly explained by age and stroke severity. Greater implementation of secondary stroke prevention is relevant to both sexes

Age, sex, and setting in the etiology of stroke study (ASSESS): Study design and protocol

RATIONALE: Stroke etiology and risk factors vary by age, sex, setting (hospital or community-based) and by region. Identifying these differences would improve our understanding of stroke etiology, diagnosis, and treatment. AIM: The Age, Sex and Setting in the Etiology of Stroke Study (ASSESS) is a multicenter cohort study to assess differences in stroke etiology. METHODS AND DESIGN: Data from all centers will be categorized according to age, sex, setting, stroke subtypes. Centers with extensive hospital- or community-based data regarding stroke from Argentina, Australia, Canada, India, Iran, Italy, Ghana, Nigeria, Thailand, the United Kingdom and the United States have agreed to participate so far. STUDY OUTCOMES: The primary outcome includes differences in stroke etiology in study centers. The secondary outcomes include stroke incidence, risk factors, preventive strategies, and short- and long-term outcomes. CONCLUSION: ASSESS will enable comparisons of data from different regions to determine the age and sex distribution of the most common causes of stroke in each setting. This will help clinicians to tailor the assessment and treatment of stroke patients on the basis of their specific local characteristics. It will also empower stroke epidemiologists to design preventive measures by targeting the specific characteristics of each population

Process evaluation in the field: global learnings from seven implementation research hypertension projects in low-and middle-income countries.

BACKGROUND:Process evaluation is increasingly recognized as an important component of effective implementation research and yet, there has been surprisingly little work to understand what constitutes best practice. Researchers use different methodologies describing causal pathways and understanding barriers and facilitators to implementation of interventions in diverse contexts and settings. We report on challenges and lessons learned from undertaking process evaluation of seven hypertension intervention trials funded through the Global Alliance of Chronic Diseases (GACD). METHODS:Preliminary data collected from the GACD hypertension teams in 2015 were used to inform a template for data collection. Case study themes included: (1) description of the intervention, (2) objectives of the process evaluation, (3) methods including theoretical basis, (4) main findings of the study and the process evaluation, (5) implications for the project, policy and research practice and (6) lessons for future process evaluations. The information was summarized and reported descriptively and narratively and key lessons were identified. RESULTS:The case studies were from low- and middle-income countries and Indigenous communities in Canada. They were implementation research projects with intervention arm. Six theoretical approaches were used but most comprised of mixed-methods approaches. Each of the process evaluations generated findings on whether interventions were implemented with fidelity, the extent of capacity building, contextual factors and the extent to which relationships between researchers and community impacted on intervention implementation. The most important learning was that although process evaluation is time consuming, it enhances understanding of factors affecting implementation of complex interventions. The research highlighted the need to initiate process evaluations early on in the project, to help guide design of the intervention; and the importance of effective communication between researchers responsible for trial implementation, process evaluation and outcome evaluation. CONCLUSION:This research demonstrates the important role of process evaluation in understanding implementation process of complex interventions. This can help to highlight a broad range of system requirements such as new policies and capacity building to support implementation. Process evaluation is crucial in understanding contextual factors that may impact intervention implementation which is important in considering whether or not the intervention can be translated to other contexts

Sex differences in severity of stroke in the INSTRUCT Study: a meta-analysis of individual participant data

Background: Women have worse outcomes after stroke than men, and this may be partly explained by stroke severity. We examined factors contributing to sex differences in severity of acute stroke assessed by the National Institutes of Health Stroke Scale. Methods and Results: We pooled individual participant data with National Institutes of Health Stroke Scale assessment (N=6343) from 8 population-based stroke incidence studies (1996-2014), forming part of INSTRUCT (International Stroke Outcomes Study). Information on sociodemographics, stroke-related clinical factors, comorbidities, and pre-stroke function were obtained. Within each study, relative risk regression using log-binominal modeling was used to estimate the female:male relative risk ( RR ) of more severe stroke (National Institutes of Health Stroke Scale>7) stratified by stroke type (ischemic stroke and intracerebral hemorrhage). Study-specific unadjusted and adjusted RR s, controlling for confounding variables, were pooled using random-effects meta-analysis. National Institutes of Health Stroke Scale data were recorded in 5326 (96%) of 5570 cases with ischemic stroke and 773 (90%) of 855 participants with intracerebral hemorrhage. The pooled unadjusted female:male RR for severe ischemic stroke was 1.35 (95% CI 1.24-1.46). The sex difference in severity was attenuated after adjustment for age, pre-stroke dependency, and atrial fibrillation but remained statistically significant (pooled RRadjusted 1.20, 95% CI 1.10-1.30). There was no sex difference in severity for intracerebral hemorrhage ( RRcrude 1.08, 95% CI 0.97-1.21; RRadjusted 1.08, 95% CI 0.96-1.20). Conclusions: Although women presented with more severe ischemic stroke than men, much although not all of the difference was explained by pre-stroke factors. Sex differences could potentially be ameliorated by strategies to improve pre-stroke health in the elderly, the majority of whom are women. Further research on the potential biological origin of sex differences in stroke severity may also be warranted

Impact of socio-economic factors on stroke prevalence among urban and rural residents in Mainland China

<p>Abstract</p> <p>Background</p> <p>An inverse relationship between better socioeconomic status (total household income, education or occupation) and stroke has been established in developed communities, but family size has generally not been considered in the use of socioeconomic status indices. We explored the utility of Family Average Income (FAI) as a single index of socioeconomic status to examine the association with stroke prevalence in a region of China, and we also compared its performance as a single index of socioeconomic status with that of education and occupation.</p> <p>Methods</p> <p>A population-based cross-sectional study was conducted in Nanjing municipality of China during the period between October 2000 and March 2001. A total of 45 administrative villages were randomly selected using a multi-stage sampling approach and all regular local residents aged 35 years or above were included. Descriptive statistics and logistic regression models were used in analysis.</p> <p>Results</p> <p>The overall prevalence of diagnosed stroke was 1.54% in all 29,340 eligible participants. An elevated prevalence of stroke was associated with increasing levels of FAI. After adjustment for basic demographic variables (age, urban/rural area and gender) and a group of defined conventional risk factors, this gradient still remained significant, with participants in the highest (OR = 1.94, 95% CI = 1.40, 2.70) and middle (OR = 1.43, 95% CI = 1.01, 2.02) categories of FAI having higher risks compared with the lowest category. A significantly elevated OR of stroke prevalence was found in white collar workers compared to blue collar workers, while no significant relationship was observed with education.</p> <p>Conclusion</p> <p>Our study consistently revealed that the prevalence of stroke was associated with increasing levels of all SES indices, including FAI, education, and occupation. However, a significant gradient was only observed with FAI after controlling for important confounding factors. The findings suggested that, compared with occupation and education, FAI could be used as a more sensitive index of socio-economic status for public health studies in China.</p