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Author(s): Amanda Clery 1,*, Ajay Bhalla 1,2, Anthony G. Rudd 1,2, Charles D. A. Wolfe 1,3,4, Yanzhong Wang 1,3,4 Introduction Stroke incidence has declined by 30% in the United Kingdom [...], Background Acute stroke impairments often result in poor long-term outcome for stroke survivors. The aim of this study was to estimate the trends over time in the prevalence of these acute stroke impairments. Methods and findings All first-ever stroke patients recorded in the South London Stroke Register (SLSR) between 2001 and 2018 were included in this cohort study. Multivariable Poisson regression models with robust error variance were used to estimate the adjusted prevalence of 8 acute impairments, across six 3-year time cohorts. Prevalence ratios comparing impairments over time were also calculated, stratified by age, sex, ethnicity, and aetiological classification (Trial of Org 10172 in Acute Stroke Treatment [TOAST]). A total of 4,683 patients had a stroke between 2001 and 2018. Mean age was 68.9 years, 48% were female, and 64% were White. After adjustment for demographic factors, pre-stroke risk factors, and stroke subtype, the prevalence of 3 out of the 8 acute impairments declined during the 18-year period, including limb motor deficit (from 77% [95% CI 74%-81%] to 62% [56%-68%], p < 0.001), dysphagia (37% [33%-41%] to 15% [12%-20%], p < 0.001), and urinary incontinence (43% [39%-47%) to 29% [24%-35%], p < 0.001). Declines in limb impairment over time were 2 times greater in men than women (prevalence ratio 0.73 [95% CI 0.64-0.84] and 0.87 [95% CI 0.77-0.98], respectively). Declines also tended to be greater in younger patients. Stratified by TOAST classification, the prevalence of all impairments was high for large artery atherosclerosis (LAA), cardioembolism (CE), and stroke of undetermined aetiology. Conversely, small vessel occlusions (SVOs) had low levels of all impairments except for limb motor impairment and dysarthria. While we have assessed 8 key acute stroke impairments, this study is limited by a focus on physical impairments, although cognitive impairments are equally important to understand. In addition, this is an inner-city cohort, which has unique characteristics compared to other populations. Conclusions In this study, we found that stroke patients in the SLSR had a complexity of acute impairments, of which limb motor deficit, dysphagia, and incontinence have declined between 2001 and 2018. These reductions have not been uniform across all patient groups, with women and the older population, in particular, seeing fewer reductions.

Introduction Providing healthcare on weekends and overnight that is of equal quality to the care provided in regular working hours is a major challenge to healthcare systems. In the United [...], BACKGROUND: Observational studies have reported higher mortality for patients admitted on weekends. It is not known whether this 'weekend effect' is modified by clinical staffing levels on weekends. We aimed to test the hypotheses that rounds by stroke specialist physicians 7 d per week and the ratio of registered nurses to beds on weekends are associated with mortality after stroke. METHODS AND FINDINGS: We conducted a prospective cohort study of 103 stroke units (SUs) in England. Data of 56,666 patients with stroke admitted between 1 June 2011 and 1 December 2012 were extracted from a national register of stroke care in England. SU characteristics and staffing levels were derived from cross-sectional survey. Cox proportional hazards models were used to estimate hazard ratios (HRs) of 30-d post-admission mortality, adjusting for case mix, organisational, staffing, and care quality variables. After adjusting for confounders, there was no significant difference in mortality risk for patients admitted to a stroke service with stroke specialist physician rounds fewer than 7 d per week (adjusted HR [aHR] 1.04, 95% CI 0.91-1.18) compared to patients admitted to a service with rounds 7 d per week. There was a dose-response relationship between weekend nurse/bed ratios and mortality risk, with the highest risk of death observed in stroke services with the lowest nurse/bed ratios. In multivariable analysis, patients admitted on a weekend to a SU with 1.5 nurses/ten beds had an estimated adjusted 30-d mortality risk of 15.2% (aHR 1.18, 95% CI 1.07-1.29) compared to 11.2% for patients admitted to a unit with 3.0 nurses/ten beds (aHR 0.85, 95% CI 0.77-0.93), equivalent to one excess death per 25 admissions. The main limitation is the risk of confounding from unmeasured characteristics of stroke services. CONCLUSIONS: Mortality outcomes after stroke are associated with the intensity of weekend staffing by registered nurses but not 7-d/wk ward rounds by stroke specialist physicians. The findings have implications for quality improvement and resource allocation in stroke care. Please see later in the article for the Editors' Summary.

Background and purpose: Machine learning (ML) has attracted much attention with the hope that it could make use of large, routinely collected datasets and deliver accurate personalised prognosis. The aim of this systematic review is to identify and critically appraise the reporting and developing of ML models for predicting outcomes after stroke. Methods: We searched PubMed and Web of Science from 1990 to March 2019, using previously published search filters for stroke, ML, and prediction models. We focused on structured clinical data, excluding image and text analysis. This review was registered with PROSPERO (CRD42019127154). Results: Eighteen studies were eligible for inclusion. Most studies reported less than half of the terms in the reporting quality checklist. The most frequently predicted stroke outcomes were mortality (7 studies) and functional outcome (5 studies). The most commonly used ML methods were random forests (9 studies), support vector machines (8 studies), decision trees (6 studies), and neural networks (6 studies). The median sample size was 475 (range 70–3184), with a median of 22 predictors (range 4–152) considered. All studies evaluated discrimination with thirteen using area under the ROC curve whilst calibration was assessed in three. Two studies performed external validation. None described the final model sufficiently well to reproduce it. Conclusions: The use of ML for predicting stroke outcomes is increasing. However, few met basic reporting standards for clinical prediction tools and none made their models available in a way which could be used or evaluated. Major improvements in ML study conduct and reporting are needed before it can meaningfully be considered for practice. [ABSTRACT FROM AUTHOR]

Introduction The World Health Organization's Global Burden of Disease analyses rely on routine mortality and limited disability data throughout most countries worldwide. These data have persistently highlighted stroke as the [...], Background: Although stroke is acknowledged as a long-term condition, population estimates of outcomes longer term are lacking. Such estimates would be useful for planning health services and developing research that might ultimately improve outcomes. This burden of disease study provides population-based estimates of outcomes with a focus on disability, cognition, and psychological outcomes up to 10 y after initial stroke event in a multi-ethnic European population. Methods and Findings: Data were collected from the population-based South London Stroke Register, a prospective population-based register documenting all first in a lifetime strokes since 1 January 1995 in a multi-ethnic inner city population. The outcomes assessed are reported as estimates of need and included disability (Barthel Index 10), and mental and physical domain scores of the Medical Outcomes Study 12-item short form (SF-12) health survey. Estimates were stratified by age, gender, and ethnicity, and ageadjusted using the standard European population. Plots of outcome estimates over time were constructed to examine temporal trends and sociodemographic differences. Between 1995 and 2006, 3,373 first-ever strokes were registered: 20%30% of survivors had a poor outcome over 10 y of follow-up. The highest rate of disability was observed 7 d after stroke and remained at around 110 per 1,000 stroke survivors from 3 mo to 10 y. Rates of inactivity and cognitive impairment both declined up to 1 y (280/1,000 and 180/1,000 survivors, respectively);thereafter rates of inactivity remained stable till year eight, then increased, whereas rates of cognitive impairment fluctuated till year eight, then increased. Anxiety and depression showed some fluctuation over time, with a rate of 350 and 310 per 1,000 stroke survivors, respectively. SF- 12 scores showed little variation from 3 mo to 10 y after stroke. Inactivity was higher in males at all time points, and in white compared to black stroke survivors, although black survivors reported better outcomes in the SF-12 physical domain. No other major differences were observed by gender or ethnicity. Increased age was associated with higher rates of disability, inactivity, and cognitive impairment. Conclusions: Between 20% and 30% of stroke survivors have a poor range of outcomes up to 10 y after stroke. Such epidemiological data demonstrate the sociodemographic groups that are most affected longer term and should be used to develop longer term management strategies that reduce the significant poor outcomes of this group, for whom effective interventions are currently elusive. Please see later in the article for the Editors' Summary.

Background: Stroke care and outcomes have improved significantly over the past decades. It is unclear if patients who had a stroke in hospital (in-hospital stroke, IHS) experienced similar improvements to those who were admitted with stroke (community-onset stroke, COS). Methods: Data from the South London Stroke Register were analysed to estimate trends in processes of care and outcomes across three cohorts (1995–2001, 2002–2008, 2009–2015). Kaplan-Meier survival curves were calculated for each cohort. Associations between patient location at stroke onset, processes of care, and outcomes were investigated using multiple logistic regression and Cox proportional hazards models. Results: Of 5,119 patients admitted to hospital and registered between 1995 and 2015, 552(10.8%) had IHS. Brain imaging rates increased from 92.4%(COS) and 78.3%(IHS) in 1995–2001 to 100% for COS and IHS in 2009–2015. Rates of stroke unit admission rose but remained lower for IHS (1995–2001: 32.2%(COS) vs. 12.4%(IHS), 2002–2008: 77.1%(COS) vs. 50.0%(IHS), 2009–2015: 86.3%(COS) vs. 65.4%(IHS)). After adjusting for patient characteristics and case-mix, IHS was independently associated with lower rates of stroke unit admission in each cohort (1995–2001: OR 0.49, 95%CI 0.29–0.82, 2002–2008: 0.29, 0.18–0.45, 2009–2015: 0.22, 0.11–0.43). In 2009–2015, thrombolysis rates were lower for ischaemic IHS (17.8%(COS) vs. 13.8%(IHS)). Despite a decline, in-hospital mortality remained significantly higher after IHS in 2009–2015 (13.7%(COS) vs. 26.7%(IHS)). Five-year mortality rates declined for COS from 58.9%(1995–2001) to 35.2%(2009–2015) and for IHS from 80.8%(1995–2001) to 51.1%(2009–2015). In multivariable analysis, IHS was associated with higher mortality over five years post-stroke in each cohort (1995–2001: HR 1.27, 95%CI 1.03–1.57, 2002–2008: 1.24, 0.99–1.55, 2009–2016: 1.39, 0.95–2.04). Conclusions: Despite significant improvements for IHS patients similar to those for COS patients, rates of stroke unit admission and thrombolysis remain lower, and short- and long-term outcomes poorer after IHS. Factors preventing IHS patients from entering evidence-based stroke-specific hospital pathways in a timely fashion need further investigation. [ABSTRACT FROM AUTHOR]

Background: As the average life expectancy increases, more people are predicted to have strokes. Recent studies have shown an increasing incidence in certain types of cerebral infarction. We aimed to estimate time trends in incidence, prior risk factors, and use of preventive treatments for ischaemic stroke (IS) aetiological subtypes and to ascertain any demographic disparities.Methods and Findings: Population-based data from the South London Stroke Register (SLSR) between 2000 and 2015 were studied. IS was classified, based on the underlying mechanism, into large-artery atherosclerosis (LAA), cardio-embolism (CE), small-vessel occlusion (SVO), other determined aetiologies (OTH), and undetermined aetiologies (UND). After calculation of age-, sex-, and ethnicity-specific incidence rates by subtype for the 16-year period, we analysed trends using Cochran-Armitage tests, Poisson regression models, and locally estimated scatterplot smoothers (loess). A total of 3,088 patients with first IS were registered. Between 2000-2003 and 2012-2015, the age-adjusted incidence of IS decreased by 43% from 137.3 to 78.4/100,000/year (incidence rate ratio [IRR] 0.57, 95% CI 0.5-0.64). Significant declines were observed in all subtypes, particularly in SVO (37.4-18; p < 0.0001) and less in CE (39.3-25; p < 0.0001). Reductions were recorded in males and females, younger (<55 years old) and older (≥55 years old) individuals, and white and black ethnic groups, though not significantly in the latter (144.6-116.2; p = 0.31 for IS). A 4-fold increase in prior-to-stroke use of statins was found (adjusted odds ratio [OR] 4.39, 95% CI 3.29-5.86), and despite the increasing prevalence of hypertension (OR 1.54, 95% CI 1.21-1.96) and atrial fibrillation (OR 1.7, 95% CI 1.22-2.36), preventive use of antihypertensive and antiplatelet drugs was declining. A smaller number of participants in certain subgroup-specific analyses (e.g., black ethnicity and LAA subtype) could have limited the power to identify significant trends.Conclusions: The incidence of ISs has been declining since 2000 in all age groups but to a lesser extent in the black population. The reported changes in medication use are unlikely to fully explain the reduction in stroke incidence; however, innovative prevention strategies and better management of risk factors may contribute further reduction. [ABSTRACT FROM AUTHOR]

Background: Previous studies have found low use of anticoagulation prior to stroke, in people with atrial fibrillation (AF). This study examined data on patients with AF-related stroke from a population-based stroke register, and sought to examine changes in management of AF prior to stroke, and reasons for suboptimal treatment, in those who were known to be at a high risk of stroke. Methods: The South London Stroke Register (SLSR) is an ongoing population-based register recording first-in-a-lifetime stroke. Trends in the prevalence of AF, and antithrombotic medication prescribed before the stroke, were investigated from 1995 to 2014. Multivariable logistic regression analyses were conducted to assess the factors associated with appropriate management. Results: Of the 5041 patients on the register, 816 (16.2%) were diagnosed with AF before their stroke. AF related stroke increased substantially among Black Carribean and Black African patients, comprising 5% of the overall cohort in 1995–1998, increasing to 25% by 2011–2014 (p<0.001). Anticoagulant prescription in AF patients at high-risk of stroke (CHADS2 score [> = 2]) increased from 9% (1995–1998) to 30% (2011–2014) (p<0.001). Antiplatelet prescription was more commonly prescribed throughout all time periods (43% to 64% of high-risk patients.) Elderly patients (>65) were significantly less likely to be prescribed an anticoagulant, with ethnicity, gender and deprivation showing no association with anticoagulation. Conclusions: Most AF-related strokes occurred in people who could have been predicted to be at high risk before their stroke, yet were not prescribed optimal preventative treatment. The elderly,despite being at highest stroke risk, were rarely prescribed anticoagulants. [ABSTRACT FROM AUTHOR]

Background: There is inconsistent evidence that patients with stroke admitted to hospital out of regular working hours (such as weekends) experience worse outcomes. We aimed to identify if inequalities in the quality of care and mortality exist in contemporary stroke care in England. Methods: SINAP is a prospective database of acute stroke patients, documenting details of processes of care over the first 72 hours. We compared quality of care indicators and mortality at 72 hours, 7 days and 30 days, for patients who arrived within normal hours (Monday–Friday 8am to 6pm) and for those who arrived out of hours, using multivariable logistic and Cox proportional hazard models. Quality of care was defined according to time from arrival at hospital to interventions (e.g., brain scan), and whether the patient received therapeutic interventions (such as thrombolysis). Results: 45,726 stroke patients were admitted to 130 hospitals in England between 1 April 2010 and 31 January 2012. Patients admitted out of hours (n = 23779) had more features indicative of worse prognosis (haemorrhagic stroke, reduced consciousness, pre stroke dependency). Out of hours admission was significantly associated with longer delays in receiving a CT scan or being admitted to a stroke unit, and reduced odds of receiving thrombolysis. After adjusting for casemix, there was no consistent evidence of higher mortality for patients admitted out of hours, but patients admitted at the weekends had a higher risk of 30 day mortality (OR 1.14, 95% CI 1.06–1.21) Conclusion: Inequalities in the provision of stroke care for people admitted out of regular hours persist in contemporary stroke in England. The association with mortality is small and largely attributable to higher illness severity in patients admitted out of hours. [ABSTRACT FROM AUTHOR]

Background: In July 2010 a new multiple hub-and-spoke model for acute stroke care was implemented across the whole of London, UK, with continuous specialist care during the first 72 hours provided at 8 hyper-acute stroke units (HASUs) compared to the previous model of 30 local hospitals receiving acute stroke patients. We investigated differences in clinical outcomes and costs between the new and old models. Methods: We compared outcomes and costs ‘before’ (July 2007–July 2008) vs. ‘after’ (July 2010–June 2011) the introduction of the new model, adjusted for patient characteristics and national time trends in mortality and length of stay. We constructed 90-day and 10-year decision analytic models using data from population based stroke registers, audits and published sources. Mortality and length of stay were modelled using survival analysis. Findings: In a pooled sample of 307 patients ‘before’ and 3156 patients ‘after’, survival improved in the ‘after’ period (age adjusted hazard ratio 0.54; 95% CI 0.41–0.72). The predicted survival rates at 90 days in the deterministic model adjusted for national trends were 87.2% ‘before’ % (95% CI 86.7%–87.7%) and 88.7% ‘after’ (95% CI 88.6%–88.8%); a relative reduction in deaths of 12% (95% CI 8%–16%). Based on a cohort of 6,438 stroke patients, the model produces a total cost saving of £5.2 million per year at 90 days (95% CI £4.9-£5.5 million; £811 per patient). Conclusion: A centralized model for acute stroke care across an entire metropolitan city appears to have reduced mortality for a reduced cost per patient, predominately as a result of reduced hospital length of stay. [ABSTRACT FROM AUTHOR]

Background: Studies examining the impact of organised acute stroke care interventions on survival in subgroups of stroke patients remain limited. Aims: This study examined the effects of a range of evidence-based interventions of acute stroke care on one year survival post-stroke and determined the size of the effect across different socio-demographic and clinical subgroups of patients. Methods: Data on 4026 patients with a first-ever stroke recruited to the population-based South London Stroke Register between 1995 and 2010 were used. In uni-variable analyses, one year cumulative survival rates in socio-demographic groups and by care received was determined. Survival functions were compared using Log-rank tests. Multivariable Cox models were used to test for interactions between components of care and age group, sex, ethnic group, social class, stroke subtype and level of consciousness. Results: 1949 (56.4%) patients were admitted to a stroke unit. Patients managed on a stroke unit, those with deficits receiving specific rehabilitation therapies and those with ischaemic stroke subtype receiving aspirin in the acute phase had better one year survival compared to those who did not receive these interventions. The greatest reduction in the hazards of death among patients treated on a stroke unit were in the youngest patients aged <65 years, (HR 0.39; 95% CI: 0.25–0.62), and those with reduced levels of consciousness, GCS <9, (HR: 0.44; CI: 0.33–0.58). Conclusions: There was evidence of better one year survival in patients receiving specific acute interventions after stroke with a significantly greater effect in stroke subgroups, suggesting the possibility of re-organising stroke services to ensure that the most appropriate care is made accessible to patients likely to derive the most benefits from such interventions. [ABSTRACT FROM AUTHOR]

Background: Electronic patient records from primary care databases are increasingly used in public health and health services research but methods used to identify cases with disease are not well described. This study aimed to evaluate the relevance of different codes for the identification of acute stroke in a primary care database, and to evaluate trends in the use of different codes over time. Methods: Data were obtained from the General Practice Research Database from 1997 to 2006. All subjects had a minimum of 24 months of up-to-standard record before the first recorded stroke diagnosis. Initially, we identified stroke cases using a supplemented version of the set of codes for prevalent stroke used by the Office for National Statistics in Key health statistics from general practice 1998 (ONS codes). The ONS codes were then independently reviewed by four raters and a restricted set of 121 codes for 'acute stroke' was identified but the kappa statistic was low at 0.23. Results: Initial extraction of data using the ONS codes gave 48,239 cases of stroke from 1997 to 2006. Application of the restricted set of codes reduced this to 39,424 cases. There were 2,288 cases whose index medical codes were for 'stroke annual review' and 3,112 for 'stroke monitoring'. The frequency of stroke review and monitoring codes as index codes increased from 9 per year in 1997 to 1,612 in 2004, 1,530 in 2005 and 1,424 in 2006. The one year mortality of cases with the restricted set of codes was 29.1% but for 'stroke annual review,' 4.6% and for 'stroke monitoring codes', 5.7%. Conclusion: In the analysis of electronic patient records, different medical codes for a single condition may have varying clinical and prognostic significance; utilisation of different medical codes may change over time; researchers with differing clinical or epidemiological experience may have differing interpretations of the relevance of particular codes. There is a need for greater transparency in the selection of sets of codes for different conditions, for the reporting of sensitivity analyses using different sets of codes, as well as sharing of code sets among researchers. [ABSTRACT FROM AUTHOR]