73 research outputs found
Survival differences post-stroke in a multi-ethnic population : The South London Stroke Register
No full textObjectives: To identify ethnic differences in survival after stroke and examine the factors that influence survival. Design: Population based stroke register with follow-up. Settings: South London Stroke Register. Participants: 2321 patients with first stroke registered between January 1995 and December 2002. Main outcome measures: Sociodemographic factors, risk factors for stroke and their management, severity of stroke, and acute service provision factors. Survival analysis with Kaplan-Meier curves, log rank test, and Cox's proportional hazard model with stratification. Results: In univariable analyses of survival, outcome was better for black people than white people (median 33.7 v 20.0 months). After stratification by socioeconomic status, type of stroke, and Glasgow coma score, and adjustment for other potential confounders, being black was generally associated with better survival, taking into account the interaction between ethnicity and age, and ethnicity and prior Barthel score. Of the risk factors for stroke considered, current smoking (hazard ratio 1.21, 95% confidence interval 1.01 to 1.45, P = 0.044), untreated atrial fibrillation (1.36, 1.08 to 1.72, P = 0.009), untreated diabetes (1.53, 1.05 to 2.22, P = 0.027), and treated diabetes (1.61, 1.27 to 2.03, P < 0.001) were associated with reduced survival. Conclusion: In general, black patients in a south London population with first ever stroke are more likely to survive than white patients, the exceptions being in those aged < 65 and those with a prior Barthel score < 15. Some pre-stroke risk factors that have the potential to be modified, including the appropriate treatment of existing health problems, have a strong impact on survival
Variations in the screening history and appropriateness of management of cervical cancer in South East England
No full textBehavioral risk factor prevalence and lifestyle change after stroke : a prospective study
No full textBackground and Purpose — Stroke patients have a 15-fold increased risk of recurrent stroke, and those with ≥1 risk factor have a further increased risk of recurrence. Previous work found management of physiological risk factors after stroke to be unsatisfactory, but there is little information on behavioral risks within the stroke population. This study estimates behavioral risk factor prevalence after stroke and explores lifestyle change.
Methods — The study used data from the population-based South London Stroke Register, collected prospectively between 1995 and 1998. Main measures included smoking status, alcohol use, and obesity. Logistic regression was used to determine sociodemographic differences in these measures.
Results — At 1 year after stroke, 22% of patients still smoked, 36% of patients were obese, and 4% drank excessively. Younger patients, whites, and men were more likely to smoke, and younger whites were more likely to drink excessively. Women and nonwhites were more likely to be obese. Those living in hospital, nursing home, or residential care and nonwhites were more likely to give up smoking, but there were no other associations between lifestyle change and the sociodemographic characteristics of patients.
Conclusions — Different behavioral risk factors were associated with specific sociodemographic groups within the stroke population. After stroke, high-risk groups should continue to be targeted to prevent stroke recurrence. However, the relationship between sociodemographic characteristics and lifestyle change remains unclear; more research is needed into the process of change to find out how best to intervene to improve secondary prevention.</p
Stop Stroke:Development of an innovative intervention to improve risk factor management after stroke
No full textObjective: Stroke survivors are at high risk of stroke recurrence yet current strategies to reduce recurrence risk are sub-optimal. The UK Medical Research Council (MRC) have proposed a framework for developing and evaluating complex interventions, such as community management of stroke secondary prevention. The Framework outlines a five-phased approach from theory through to implementation of effective interventions. This paper reports Phases I-III of the development of a novel intervention to improve risk factor management after stroke. Methods: The pre-clinical/theoretical phase entailed reviewing the literature and undertaking quantitative and qualitative studies to identify current practices and barriers to secondary prevention. In Phase I (modelling), findings were used to design an intervention with the potential to overcome barriers to effective stroke secondary prevention management. The feasibility of delivering the intervention and its acceptability were tested in the Phase II exploratory trial involving 25 stroke survivors and their general practitioners. Results: This led to the development of the definitive risk factor management intervention. This comprises multiple components and involves using an on-going population stroke register to target patients, carers and health care professionals with tailored secondary prevention advice. Clinical, socio-demographic and service use data collected by the stroke register are transformed to provide an individualised secondary prevention package for patients, carers and health care professionals at three time points: within 10 weeks, 3 and 6 months post-stroke. Conclusion: The intervention is currently being evaluated in a randomised controlled trial. Further research is needed to test generalisability to other aspects of stroke management and for other chronic diseases. Practice implications: The MRC Framework for complex interventions provides a structured approach to guide the development of novel interventions in public health. Implications for practice in stroke secondary prevention will emerge when the results of our randomised controlled trial are published
Behavioral risk factor prevalence and lifestyle change after stroke : a prospective study
No full text<p>Background and Purpose — Stroke patients have a 15-fold increased risk of recurrent stroke, and those with ≥1 risk factor have a further increased risk of recurrence. Previous work found management of physiological risk factors after stroke to be unsatisfactory, but there is little information on behavioral risks within the stroke population. This study estimates behavioral risk factor prevalence after stroke and explores lifestyle change.</p>
<p>Methods — The study used data from the population-based South London Stroke Register, collected prospectively between 1995 and 1998. Main measures included smoking status, alcohol use, and obesity. Logistic regression was used to determine sociodemographic differences in these measures.</p>
<p>Results — At 1 year after stroke, 22% of patients still smoked, 36% of patients were obese, and 4% drank excessively. Younger patients, whites, and men were more likely to smoke, and younger whites were more likely to drink excessively. Women and nonwhites were more likely to be obese. Those living in hospital, nursing home, or residential care and nonwhites were more likely to give up smoking, but there were no other associations between lifestyle change and the sociodemographic characteristics of patients.</p>
<p>Conclusions — Different behavioral risk factors were associated with specific sociodemographic groups within the stroke population. After stroke, high-risk groups should continue to be targeted to prevent stroke recurrence. However, the relationship between sociodemographic characteristics and lifestyle change remains unclear; more research is needed into the process of change to find out how best to intervene to improve secondary prevention.</p>
Supported Accommodation Evaluation Framework (SAEF): drop-in support
No full textThe NSW Department of Family and Community Services, Ageing, Disability and Home Care (ADHC) commissioned the Social Policy Research Centre (SPRC) at University of New South Wales (UNSW) Australia to design an evaluation framework and collect data for the accommodation support and funding models under Stronger Together 2 (ST2). The evaluation used longitudinal, mixed methods and a participatory research approach.
The project built evidence about accommodation support through the collection of data and development of an evaluation framework. This evidence base informs the design and development of disability policy. The evaluation includes nine SAEF options grouped in four categories: individual packages, Drop-in Support, group accommodation and Other.
This report is about implementation and use of the Drop-in Support options: Independent Living Drop-in Support (ILDIS) and Independent Living Skills Initiative (ILSI).
Drop-in Support is about helping people with disability to live as independently as they can, in a place they want and with the type of help that best suited them. There are two types of Drop-in Support:
Independent Living Drop-in Support
Independent Living Drop-in Support helps people with disability to move to a more independent way of living over time.
It includes case management, planning and learning new skills.
Independent Living Skills Initiative
The Independent Living Skills Initiative is about living independently in the community with both formal and informal help.
People can live in their current home or move house.
Evidence from the evaluation showed that Dropin Support achieved positive outcomes for many participants, particularly in selfdetermination, personal development, social inclusion, and emotional wellbeing. Less change was evident in people’s interpersonal relationships, and there was little change in material wellbeing and employment. Living in independent accommodation had been realised mainly where families had some capacity to assist or the support worker could help with the social housing process. The findings have policy implications for design, implementation and collaboration
Point-of-care cluster randomized trial in stroke secondary prevention using electronic health records.
No full textBACKGROUND AND PURPOSE: The aim of this study was to evaluate whether the remote introduction of electronic decision support tools into family practices improves risk factor control after first stroke. This study also aimed to develop methods to implement cluster randomized trials in stroke using electronic health records. METHODS: Family practices were recruited from the UK Clinical Practice Research Datalink and allocated to intervention and control trial arms by minimization. Remotely installed, electronic decision support tools promoted intensified secondary prevention for 12 months with last measure of systolic blood pressure as the primary outcome. Outcome data from electronic health records were analyzed using marginal models. RESULTS: There were 106 Clinical Practice Research Datalink family practices allocated (intervention, 53; control, 53), with 11 391 (control, 5516; intervention, 5875) participants with acute stroke ever diagnosed. Participants at trial practices had similar characteristics as 47,887 patients with stroke at nontrial practices. During the intervention period, blood pressure values were recorded in the electronic health records for 90% and cholesterol values for 84% of participants. After intervention, the latest mean systolic blood pressure was 131.7 (SD, 16.8) mm Hg in the control trial arm and 131.4 (16.7) mm Hg in the intervention trial arm, and adjusted mean difference was -0.56 mm Hg (95% confidence interval, -1.38 to 0.26; P=0.183). The financial cost of the trial was approximately US 2400 per family practice allocated. CONCLUSIONS: Large pragmatic intervention studies may be implemented at low cost by using electronic health records. The intervention used in this trial was not found to be effective, and further research is needed to develop more effective intervention strategies. CLINICAL TRIAL REGISTRATION URL: http://www.controlled-trials.com. Current Controlled Trials identifier: ISRCTN35701810
Does admission to hospital improve the outcome for stroke patients?
No full textObjectives: to identify the factors associated with hospital admission and the differences in management and outcome of stroke patients between hospital and home.
Design: a prospective community stroke register (1995–8) with multiple notification sources.
Setting: an inner city multi‐ethnic population of 234 533 in South London, UK.
Participants: 975 subjects with first in a lifetime strokes, whether or not they were admitted to hospital. Patients dying suddenly and those already hospitalized at the time of stroke were excluded.
Main outcome measures: factors associated with hospital admission; differences in management in the acute phase of stroke; mortality and dependency assessed by the Barthel index 3 months post‐stroke.
Results: 812 patients were admitted to hospital for stroke; 163 were managed in the community. Factors independently associated with hospital admission included stroke severity, pre‐stroke independence, atrial fibrillation, having an intracranial haemorrhage and having a non‐lacunar infarction. Computed tomography scan rates were higher in admitted (78%) than non‐admitted patients (63%; P=0.001). By 3 months, 285 (35%) of the admitted patients had died compared with 13 (8%) of non‐admitted patients (P<0.001). Of the admitted patients, 241 (47%) had a Barthel index ≥18 compared with 106 (72%) of those who were not admitted (P<0.001). After adjusting for case‐mix variables, the odds ratios for death and dependency (Barthel index<18) in admitted and non‐admitted patients were 2.21 (0.96–5.12) and 2.39 (1.35–4.22) respectively.
Conclusion: patients with clinical indicators for a more severe stroke were more likely to be admitted to hospital. Hospitalized stroke patients may have poorer survival and disability rates than those who remain at home, even after adjustment for case mix. There may be some aspects of acute hospital care that may be detrimental to outcome in certain groups of stroke patients. This requires further investigation
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