The impact of stroke unit care on outcome in a Scottish stroke population, taking into account case mix and selection bias

Sex Differences in Severity and Risk Factors for Ischemic Stroke in Patients With Hyperlipidemia

Objective

This study aims to determine sex differences in poststroke hypertriglyceridemia (serum triglyceride levels ⩾ 200 mg/dl) and high stroke severity in ischemic stroke patients.

Method

Our study analyzed data from 392 males and 373 females with hypertriglyceridemia. Stroke severity on admission was measured using the National Institute of Health Stroke Scale (NIHSS) with a value ⩽7 indicating a more favorable post-stroke prognosis while a score of >7 indicates poorer post-stroke outcomes. Logistic regression models adjusted for demographic and risk factors. The adjusted odds ratios (ORs) and 95% confidence intervals (CIs) for each clinical risk factor were used to predict the increasing odds of an association of a specific clinical baseline risk factor with the male or female AIS with hypertriglyceridemia.

Results

In the adjusted analysis, male patients with hypertriglyceridemia, diastolic blood pressure (OR = 1.100, 95% CI, 1.034-1.171, P = .002), and Ischemic stroke mortality (OR = 6.474, 95% CI, 3.262-12.847, P < .001) were significantly associated with increased stroke severity. In female patients with hypertriglyceridemia, age (OR = 0.920, 95% CI, 0.866-0.978, P = .008) was associated with reduced stroke severity, while ischemic stroke mortality score (OR = 37.477, 95% CI, 9.636-145.756, P < .001) was associated with increased stroke severity.

Conclusion

Increased ischemic stroke mortality risk score was associated with increased severity in both male and female AIS patients with hypertriglyceridemia. Our findings provide information about sex differences in specific risk factors that can be managed to improve the care of male and female ischemic stroke patients with hypertriglyceridemia.

Predicting 90-day prognosis for patients with stroke: a machine learning approach

Background

Stroke is a significant global health burden and ranks as the second leading cause of death worldwide.

Objective

This study aims to develop and evaluate a machine learning-based predictive tool for forecasting the 90-day prognosis of stroke patients after discharge as measured by the modified Rankin Score.

Methods

The study utilized data from a large national multiethnic stroke registry comprising 15,859 adult patients diagnosed with ischemic or hemorrhagic stroke. Of these, 7,452 patients satisfied the study's inclusion criteria. Feature selection was performed using the correlation and permutation importance methods. Six classifiers, including Random Forest (RF), Classification and Regression Tree, Linear Discriminant Analysis, Support Vector Machine, and k-Nearest Neighbors, were employed for prediction.

Results

The RF model demonstrated superior performance, achieving the highest accuracy (0.823) and excellent discrimination power (AUC 0.893). Notably, stroke type, hospital acquired infections, admission location, and hospital length of stay emerged as the top-ranked predictors.

Conclusion

The RF model shows promise in predicting stroke prognosis, enabling personalized care plans and enhanced preventive measures for stroke patients. Prospective validation is essential to assess its real-world clinical performance and ensure successful implementation across diverse healthcare settings.

Effect of admission in the stroke care unit versus intensive care unit on in-hospital mortality in patients with acute ischemic stroke

BACKGROUND/OBJECTIVE

Few reports have directly compared the outcomes of patients with acute ischemic stroke (AIS) who are managed in a stroke care unit (SCU) with those who are managed in an intensive care units (ICU). This large database study in Japan aimed to compare in-hospital mortality between patients with AIS admitted into SCU and those admitted into ICU.

METHODS

Patients with AIS who were admitted between April 1, 2014, and March 31, 2019, were selected from the administrative database and divided into the SCU and ICU groups. We calculated the propensity score to match groups for which the admission unit assignment was independent of confounding factors, including the modified Rankin scale (mRS) score. The primary outcome was in-hospital mortality, and secondary outcomes were the mRS score at discharge, length of stay (LOS), and total hospitalization cost.

RESULTS

Overall, 8,683 patients were included, and 960 pairs were matched. After matching, the in-hospital mortality rates of the SCU and ICU groups were not significantly different (5.9% vs. 7.9%, P = 0.106). LOS was significantly shorter (SCU = 20.9 vs. ICU = 26.2 days, P < 0.001) and expenses were significantly lower in the SCU group than in the ICU group (SCU = 1,686,588 vs. ICU = 1,998,260 yen, P < 0.001). mRS scores (score of 1-3 or 4-6) at discharge were not significantly different after matching. Stratified analysis showed that the in-hospital mortality rate was lower in the ICU group than in the SCU group among patients who underwent thrombectomy.

CONCLUSIONS

In-hospital mortality was not significantly different between the ICU and SCU groups, with significantly lower costs and shorter LOS in the SCU group than in the ICU group.

Effects of delay to stroke unit admission in patients with ischemic and hemorrhagic stroke

OBJECTIVE

To determine the association between delay in transfer to a central stroke unit from peripheral institutions and outcomes.

METHODS

We conducted a retrospective cohort study of all patients with acute stroke, admitted to a comprehensive stroke center (CSC) from three emergency departments (EDs), between 2016 and 2018. The primary outcomes were length of stay, functional status at 3 months, discharge destination, and time to stroke investigations.

RESULTS

One thousand four hundred thirty-five patients were included, with a mean age of 72.9 years, and 92.4% ischemic stroke; 663 (46.2%) patients were female. Each additional day of delay was associated with 2.0 days of increase in length of stay (95% confidence interval [CI] 0.8-3.2, p = 0.001), 11.5 h of delay to vascular imaging (95% CI 9.6-13.4, p < 0.0001), 24.2 h of delay to Holter monitoring (95% CI 7.9-40.6, p = 0.004), and reduced odds of nondisabled functional status at 3 months (odds ratio 0.98, 95% CI 0.96-1.00, p = 0.01). Factors affecting delay included stroke onset within 6 h of ED arrival (605.9 min decrease in delay, 95% CI 407.9-803.9, p < 0.0001), delay to brain imaging (59.4 min increase in delay for each additional hour, 95% CI 48.0-71.4, p < 0.0001), admission from an alternative service (3918.7 min increase in delay, 95% CI 3621.2-4079.9, p < 0.0001), and transfer from a primary stroke center (PSC; 740.2 min increase in delay, 95% CI 456.2-1019.9, p < 0.0001).

CONCLUSION

Delay to stroke unit admission in a system involving transfer from PSCs to a CSC was associated with longer hospital stay and poorer functional outcomes.

Cost Utility Analysis of Multidisciplinary Postacute Care for Stroke: A Prospective Six-Hospital Cohort Study

Background

Few studies have compared the optimal duration and intensity of organized multidisciplinary neurological/rehabilitative care delivered in a regional/district hospital with the standard rehabilitative care delivered in the general neurology/rehabilitation ward of a medical center. This study measured functional outcomes and conducted cost-utility analysis of an organized multidisciplinary postacute care (PAC) project in secondary care compared with standard rehabilitative care delivered in tertiary care.

Methods

This prospective cohort study enrolled 1,476 patients who had a stroke between March 2014 and March 2018 and had a modified Rankin scale score of 2–4. After exact matching for age ± 1 year, sex, year of stroke diagnosis, nasogastric tube, and Foley catheter and propensity score matching for the other covariates, we obtained 120 patients receiving PAC (the PAC group) from four regional/district hospitals and 120 patients not receiving PAC (the non-PAC group) from two medical centers.

Results

At baseline, the non-PAC group showed significantly better functional outcomes than the PAC group, including EuroQol-5 dimensions (EQ-5D), Mini-Mental State Examination (MMSE) and Barthel index (BI). During weeks 7–12 of rehabilitation, improvements in all functional outcomes were significantly larger in the PAC group (P < 0.001) except for Functional Oral Intake Scale (FOIS). Cost-utility analysis revealed that the PAC group had a significantly lower mean (± standard deviation) of direct medical costs (US$3,480 ± $1,758 vs. US$3,785 ± $3,840, P < 0.001) and a significantly higher average gain of quality-adjusted life years (0.1993 vs. 0.1233, P < 0.001). The PAC project was an economically “dominant” strategy.

Conclusions

The PAC project saved costs and significantly improved the functional outcomes of patients with stroke with slight to moderately severe disabilities. Randomized control trials are required to corroborate these results.

Multidisciplinary Care after Acute Care for Stroke: A Prospective Comparison between a Multidisciplinary Post-Acute Care Group and a Standard Group Matched by Propensity Score

In this large-scale prospective cohort study, a propensity score matching method was applied in a natural experimental design to investigate how post-acute care (PAC) after stroke affects functional status and to identify predictors of functional status. The main objective of this study was to examine longitudinal changes in various measures of functional status in stroke patients and predictors of scores for these measures before and after PAC. A group of patients who had received PAC for stroke at one of two medical centers (PAC group, n = 273) was compared with a group who had received standard care for stroke at one of four hospitals (three regional hospital and one district hospital; non-PAC group, n = 273) in Taiwan from March, 2014, to October, 2018. The patients completed the functional status measures before rehabilitation, the 12th week and the 1st year after rehabilitation. Generalized estimating equations were used to estimate differences-in-differences models for examining the effects of PAC. The average age was 68.0 (SD = 8.1) years, and males accounted for 57.9%. During the follow-up period, significant risk factors for poor functional outcomes were advanced age, hemorrhagic stroke, and poor function scores before rehabilitation (p < 0.05). Between-group comparisons at subsequent time points revealed significantly higher functional status scores in the PAC group versus the non-PAC group (p < 0.001). Notably, for all functional status measures, between-group differences in total scores significantly increased over time from baseline to 1 year post-rehabilitation (p < 0.001). The contribution of this study is its further elucidation of the clinical implications and health policy implications of rehabilitative care after stroke. Specifically, it improves understanding of the effects of PAC in stroke patients at different follow-up times. Therefore, a policy implication of this study is that standard care for stroke should include intensive rehabilitative PAC to maximize recovery of overall function.

Predictive Value of the Alberta Stroke Program Early CT Score (ASPECTS) in the Outcome of the Acute Ischemic Stroke and Its Correlation with Stroke Subtypes, NIHSS, and Cognitive Impairment

OBJECTIVES

This study is aimed at correlating ASPECTS with mortality and morbidity in patients with acute middle cerebral artery territory infarction and at determining the cutoff value of ASPECTS that may predict the outcome.

METHODS

150 patients diagnosed with acute middle cerebral artery territory infarction were involved in this study. Risk factors, initial NIHSS, and GCS were determined. An initial or follow-up noncontrast CT brain was done and assessed by ASPECTS. Outcomes were determined by mRS during the follow-up of cases after 3 months. Correlations of ASPECTS and outcome variables were done by Spearman correlation. Logistic regression analysis and ROC curve were done to detect the cutoff value of ASPECTS that predicts unfavorable outcomes.

RESULTS

The most common subtypes of ischemic strokes were lacunar stroke in 66 patients (44%), cardioembolic stroke in 39 patients (26%), and LAA stroke in 30 cases (20%). The cardioembolic stroke had a statistically significant lower ASPECT score than other types of ischemic strokes (P < 0.05). Spearman correlation showed that lower ASPECTS values (worse outcome) were more in older patients and associated with lower initial GCS. ASPECTS values were inversely correlated with initial NIHSS, inpatient stay, inpatient complications, mortality, and mRS. The ASPECTS cutoff value determined for the prediction of unfavorable outcomes was equal to ≤7. The binary logistic regression analysis detected that patients with ASPECTS ≤ 7 were significantly associated with about fourfold increased risk of poor outcomes (OR 3.95, 95% CI 2.09-11.38, and P < 0.01).

CONCLUSIONS

ASPECTS is a valuable and appropriate technique for the evaluation of the prognosis in acute ischemic stroke. Patients with high ASPECTS values are more likely to attain favorable outcomes, and the cutoff value of ASPECTS is a strong predictor for unfavorable outcomes. This trial is registered with ClinicalTrials.gov NCT04235920.

The Unmet Needs of Stroke Survivors and Stroke Caregivers: A Systematic Narrative Review

INTRODUCTION

Facilitating stroke survivors and their caregivers to lead a fulfilling life after stroke requires service providers to think about their different needs. Poor post stroke care may lead to unmet needs in stroke survivors and stroke caregivers. This may compromise them in leading their lives optimally after stroke.

OBJECTIVES & METHODOLOGY

This systematic narrative review examines articles published from 1990 to 2017, generated from Ovid, MEDLINE, CINAHL, and PubMed. The search was also supplemented by an examination of reference lists for related articles via Scopus. We included 105 articles.

FINDINGS

We found that the type of unmet needs in stroke survivors and the contributing factors were substantially different from their caregivers. The unmet needs in stroke survivors ranged from health-related needs to re-integration into the community; while the unmet needs in stroke caregivers ranged from information needs to support in caring for the stroke survivors and caring for themselves. Additionally, the unmet needs in both groups were associated with different factors.

CONCLUSION

More research is required to understand the unmet needs of stroke survivors and stroke caregivers to improve the overall post-stroke care services.

Predicting Early Mortality of Acute Ischemic Stroke

Background and Purpose—

Several risk factors are known to increase mid- and long-term mortality of ischemic stroke patients. Information on predictors of early stroke mortality is scarce but often requested in clinical practice. We therefore aimed to develop a rapidly applicable tool for predicting early mortality at the stroke unit.

Methods—

We used data from the nationwide Austrian Stroke Unit Registry and multivariate regularized logistic regression analysis to identify demographic and clinical variables associated with early (≤7 days poststroke) mortality of patients admitted with ischemic stroke. These variables were then used to develop the Predicting Early Mortality of Ischemic Stroke score that was validated both by bootstrapping and temporal validation.

Results—

In total, 77 653 ischemic stroke patients were included in the analysis (median age: 74 years, 47% women). The mortality rate at the stroke unit was 2% and median stay of deceased patients was 3 days. Age, stroke severity measured by the National Institutes of Health Stroke Scale, prestroke functional disability (modified Rankin Scale >0), preexisting heart disease, diabetes mellitus, posterior circulation stroke syndrome, and nonlacunar stroke cause were associated with mortality and served to build the Predicting Early Mortality of Ischemic Stroke score ranging from 0 to 12 points. The area under the curve of the score was 0.879 (95% CI, 0.871–0.886) in the derivation cohort and 0.884 (95% CI, 0.863–0.905) in the validation sample. Patients with a score ≥10 had a 35% (95% CI, 28%–43%) risk to die within the first days at the stroke unit.

Conclusions—

We developed a simple score to estimate early mortality of ischemic stroke patients treated at a stroke unit. This score could help clinicians in short-term prognostication for management decisions and counseling.

Evaluation of reconfigurations of acute stroke services in different regions of England and lessons for implementation: a mixed-methods study

Background

Centralising acute stroke services is an example of major system change (MSC). ‘Hub and spoke’ systems, consisting of a reduced number of services providing acute stroke care over the first 72 hours following a stroke (hubs), with a larger number of services providing care beyond this phase (spokes), have been proposed to improve care and outcomes.

Objective

To use formative evaluation methods to analyse reconfigurations of acute stroke services in different regions of England and to identify lessons that will help to guide future reconfigurations, by studying the following contrasting cases: (1) London (implemented 2010) – all patients eligible for Hyperacute Stroke Units (HASUs); patients admitted 24 hours a day, 7 days a week; (2) Greater Manchester A (GMA) (2010) – only patients presenting within 4 hours are eligible for HASU treatment; one HASU operated 24/7, two operated from 07.00 to 19.00, Monday to Friday; (3) Greater Manchester B (GMB) (2015) – all patients eligible for HASU treatment (as in London); one HASU operated 24/7, two operated with admission extended to the hours of 07.00–23.00, Monday to Sunday; and (4) Midlands and East of England – planned 2012/13, but not implemented.

Design

Impact was studied through a controlled before-and-after design, analysing clinical outcomes, clinical interventions and cost-effectiveness. The development, implementation and sustainability of changes were studied through qualitative case studies, documentation analysis (n = 1091), stakeholder interviews (n = 325) and non-participant observations (n = 92; ≈210 hours). Theory-based framework was used to link qualitative findings on process of change with quantitative outcomes.

Results

Impact – the London centralisation performed significantly better than the rest of England (RoE) in terms of mortality [–1.1%, 95% confidence interval (CI) –2.1% to –0.1%], resulting in an estimated additional 96 lives saved per year beyond reductions observed in the RoE, length of stay (LOS) (–1.4 days, 95% –2.3 to –0.5 days) and delivering effective clinical interventions [e.g. arrival at a Stroke Unit (SU) within 4 hours of ‘clock start’ (when clock start refers to arrival at hospital for strokes occurring outside hospital or the appearance of symptoms for patients who are already in-patients at the time of stroke): London = 66.3% (95% CI 65.6% to 67.1%); comparator = 54.4% (95% CI 53.6% to 55.1%)]. Performance was sustained over 6 years. GMA performed significantly better than the RoE on LOS (–2.0 days, 95% CI –2.8 to –1.2 days) only. GMB (where 86% of patients were treated in HASU) performed significantly better than the RoE on LOS (–1.5 days, 95% CI –2.5 to –0.4 days) and clinical interventions [e.g. SU within 4 hours: GMB = 79.1% (95% CI 77.9% to 80.4%); comparator = 53.4% (95% CI 53.0% to 53.7%)] but not on mortality (–1.3%, 95% CI –2.7% to 0.01%; p = 0.05, accounting for reductions observed in RoE); however, there was a significant effect when examining GMB HASUs only (–1.8%, 95% CI –3.4% to –0.2%), resulting in an estimated additional 68 lives saved per year. All centralisations except GMB were cost-effective at 10 years, with a higher net monetary benefit than the RoE at a willingness to pay for a quality-adjusted life-year (QALY) of £20,000–30,000. Per 1000 patients at 10 years, London resulted in an additional 58 QALYs, GMA resulted in an additional 18 QALYs and GMB resulted in an additional 6 QALYs at costs of £1,014,363, –£470,848 and £719,948, respectively. GMB was cost-effective at 90 days. Despite concerns about the potential impact of increased travel times, patients and carers reported good experiences of centralised services; this relied on clear information at every stage. Planning change – combining top-down authority and bottom-up clinical leadership was important in co-ordinating multiple stakeholders to agree service models and overcome resistance. Implementation – minimising phases of change, use of data, service standards linked to financial incentives and active facilitation of changes by stroke networks was important. The 2013 reforms of the English NHS removed sources of top-down authority and facilitative capacity, preventing centralisation (Midlands and East of England) and delaying implementation (GMB). Greater Manchester’s Operational Delivery Network, developed to provide alternative network facilitation, and London’s continued use of standards suggested important facilitators of centralisation in a post-reform context.

Limitations

The main limitation of our quantitative analysis was that we were unable to control for stroke severity. In addition, findings may not apply to non-urban settings. Data on patients’ quality of life were unavailable nationally, clinical interventions measured changed over time and national participation in audits varied. Some qualitative analyses were retrospective, potentially influencing participant views.

Conclusions

Centralising acute stroke services can improve clinical outcomes and care provision. Factors related to the service model implemented, how change is implemented and the context in which it is implemented are influential in improvement. We recommend further analysis of how different types of leadership contribute to MSC, patient and carer experience during the implementation of change, the impact of change on further clinical outcomes (disability and QoL) and influence of severity of stroke on clinical outcomes. Finally, our findings should be assessed in relation to MSC implemented in other health-care specialties.

Funding

The National Institute for Health Research Health Services and Delivery Research programme.

Inequality in Care and Differences in Outcome Following Stroke in People With ESRD

Introduction

Stroke rate and mortality are greater in individuals with end-stage renal disease (ESRD) than in those without ESRD. We examined discrepancies in stroke care in ESRD patients and their influence on mortality.

Methods

This is a national record linkage cohort study of hospitalized stroke individuals from 2005 to 2013. Presentation, measures of care quality (admission to stroke unit, swallow assessment, antithrombotics, or thrombolysis use), and outcomes were compared in those with and without ESRD after propensity score matching (PSM). We examined the effect of being admitted to a stroke unit on survival using Kaplan-Meier and Cox survival analyses.

Results

A total of 8757 individuals with ESRD and 61,367 individuals with stroke were identified. ESRD patients (n =486) experienced stroke over 34,551.9 patient-years of follow-up; incidence rates were 25.3 (dialysis) and 4.5 (kidney transplant)/1000 patient-years. After PSM, dialysis patients were less likely to be functionally independent (61.4% vs. 77.7%; P < 0.0001) before stroke, less frequently admitted to stroke units (64.6% vs. 79.6%; P < 0.001), or to receive aspirin (75.3% vs. 83.2%; P = 0.01) than non-ESRD stroke patients. There were no significant differences in management of kidney transplantation patients. Stroke with ESRD was associated with a higher death rate during admission (dialysis 22.9% vs.14.4%, P = 0.002; transplantation: 19.6% vs. 9.3%; P = 0.034). Managing ESRD patients in a stroke unit was associated with a lower risk of death at follow-up (hazard ratio: 0.68; 95% confidence interval: 0.55-0.84).

Conclusion

Stroke incidence is high in ESRD. Individuals on dialysis are functionally more dependent before stroke and less frequently receive optimal stroke care. After a stroke, death is more likely in ESRD patients. Acute stroke unit care may be associated with lower mortality.

Evaluation of anticoagulation status for atrial fibrillation on early ischaemic stroke outcomes: a registry-based, prospective cohort study of acute stroke care in Surrey, UK

OBJECTIVE

The relationship of anticoagulation therapies with stroke severity and outcomes have been well documented in the literature. However, none of the previous research has reported the relationship of atrial fibrillation (AF)/anticoagulation therapies with urinary tract infection (UTI), pneumonia and length of stay in hyperacute stroke units (HASUs). The present study aimed to evaluate AF and anticoagulation status in relation to early outcomes in 1387 men (median age=75 years, IQR=65-83) and 1371 women (median age=83 years, IQR=74-89) admitted with acute ischaemic stroke to HASUs in Surrey between 2014 and 2016.

METHODS

We conducted this registry-based, prospective cohort study using data from the Sentinel Stroke National Audit Programme. Association between AF anticoagulation status with severe stroke on arrival (National Institutes of Health Stroke Scale score ≥16), prolonged HASU stay (>3 weeks), UTI and pneumonia within 7 days of admission, severe disability on discharge (modified Rankin Scale score=4 and 5) and inpatient mortality was assessed by logistic regression, adjusted for age, sex, hypertension, congestive heart failure, diabetes and previous stroke.

RESULTS

Compared with patients with stroke who are free from AF, those with AF without anticoagulation had an increased adjusted risk of having more severe stroke: 5.8% versus 14.0%, OR=2.4 (95% CI 1.6 to 3.6, P<0.001), prolonged HASU stay: 21.5% versus 32.0%, OR=1.4 (1.0-2.0, P=0.027), pneumonia: 8.2% versus 19.1%, OR=2.1 (1.4-2.9, P<0.001), more severe disability: 24.2% versus 40.4%, OR=1.6 (1.2-2.1, P=0.004) and mortality: 9.3% versus 21.7%, OR=1.9 (1.4-2.8, P<0.001), and AF patients with anticoagulation also had greater risk for having UTI: 8.6% versus 12.3%, OR=1.9 (1.2-3.0, P=0.004), pneumonia: 8.2% versus 11.5%, OR=1.6 (1.1-2.4, P=0.025) and mortality: 9.7% versus 21.7%, OR=1.9 (1.4-2.8, P<0.001). The median HASU stay for stroke patients with AF without anticoagulation was 10.6 days (IQR=2.8-26.4) compared with 5.8 days (IQR=2.3-17.5) for those free from AF (P<0.001).

CONCLUSIONS

Patients with AF, particularly those without anticoagulation, are at increased risk of severe stroke, associated with prolonged HASU stay and increased risk of early infection, disability and mortality.

Predicting Discharge to Institutional Long-Term Care After Stroke: A Systematic Review and Metaanalysis

BACKGROUND/OBJECTIVES

Stroke is a leading cause of disability worldwide, and a significant proportion of stroke survivors require long-term institutional care. Understanding who cannot be discharged home is important for health and social care planning. Our aim was to establish predictive factors for discharge to institutional care after hospitalization for stroke.

DESIGN

We registered and conducted a systematic review and meta-analysis (PROSPERO: CRD42015023497) of observational studies. We searched MEDLINE, EMBASE, and CINAHL Plus to February 2017. Quantitative synthesis was performed where data allowed.

SETTING

Acute and rehabilitation hospitals.

PARTICIPANTS

Adults hospitalized for stroke who were newly admitted directly to long-term institutional care at the time of hospital discharge.

MEASUREMENTS

Factors associated with new institutionalization.

RESULTS

From 10,420 records, we included 18 studies (n = 32,139 participants). The studies were heterogeneous and conducted in Europe, North America, and East Asia. Eight studies were at high risk of selection bias. The proportion of those surviving to discharge who were newly discharged to long-term care varied from 7% to 39% (median 17%, interquartile range 12%), and the model of care received in the long-term care setting was not defined. Older age and greater stroke severity had a consistently positive association with the need for long-term care admission. Individuals who had a severe stroke were 26 times as likely to be admitted to long-term care than those who had a minor stroke. Individuals aged 65 and older had a risk of stroke that was three times as great as that of younger individuals. Potentially modifiable factors were rarely examined.

CONCLUSION

Age and stroke severity are important predictors of institutional long-term care admission directly from the hospital after an acute stroke. Potentially modifiable factors should be the target of future research. Stroke outcome studies should report discharge destination, defining the model of care provided in the long-term care setting.

Association between patient outcomes and key performance indicators of stroke care quality: A systematic review and meta-analysis

Purpose

Translating research evidence into clinical practice often uses key performance indicators to monitor quality of care. We conducted a systematic review to identify the stroke key performance indicators used in large registries, and to estimate their association with patient outcomes.

Method

We sought publications of recent (January 2000-May 2017) national or regional stroke registers reporting the association of key performance indicators with patient outcome (adjusting for age and stroke severity). We searched Ovid Medline, EMBASE and PubMed and screened references from bibliographies. We used an inverse variance random effects meta-analysis to estimate associations (odds ratio; 95% confidence interval) with death or poor outcome (death or disability) at the end of follow-up.

Findings

We identified 30 eligible studies (324,409 patients). The commonest key performance indicators were swallowing/nutritional assessment, stroke unit admission, antiplatelet use for ischaemic stroke, brain imaging and anticoagulant use for ischaemic stroke with atrial fibrillation, lipid management, deep vein thrombosis prophylaxis and early physiotherapy/mobilisation. Lower case fatality was associated with stroke unit admission (odds ratio 0.79; 0.72-0.87), swallow/nutritional assessment (odds ratio 0.78; 0.66-0.92) and antiplatelet use for ischaemic stroke (odds ratio 0.61; 0.50-0.74) or anticoagulant use for ischaemic stroke with atrial fibrillation (odds ratio 0.51; 0.43-0.64), lipid management (odds ratio 0.52; 0.38-0.71) and early physiotherapy or mobilisation (odds ratio 0.78; 0.67-0.91). Reduced poor outcome was associated with adherence to swallowing/nutritional assessment (odds ratio 0.58; 0.43-0.78) and stroke unit admission (odds ratio 0.83; 0.77-0.89). Adherence with several key performance indicators appeared to have an additive benefit.

Discussion

Adherence with common key performance indicators was consistently associated with a lower risk of death or disability after stroke.

Conclusion

Policy makers and health care professionals should implement and monitor those key performance indicators supported by good evidence.

Stroke unit care in germany: the german stroke registers study group (ADSR)

BACKGROUND

Factors influencing access to stroke unit (SU) care and data on quality of SU care in Germany are scarce. We investigated characteristics of patients directly admitted to a SU as well as patient-related and structural factors influencing adherence to predefined indicators of quality of acute stroke care across hospitals providing SU care.

METHODS

Data were derived from the German Stroke Registers Study Group (ADSR), a voluntary network of 9 regional registers for monitoring quality of acute stroke care in Germany. Multivariable logistic regression analyses were performed to investigate characteristics influencing direct admission to SU. Generalized Linear Mixed Models (GLMM) were used to estimate the influence of structural hospital characteristics (percentage of patients admitted to SU, year of SU-certification, and number of stroke and TIA patients treated per year) on adherence to predefined quality indicators.

RESULTS

In 2012 180,887 patients were treated in 255 hospitals providing certified SU care participating within the ADSR were included in the analysis; of those 82.4% were directly admitted to a SU. Ischemic stroke patients without disturbances of consciousness (p < .0001), an interval onset to admission time ≤3 h (p < .0001), and weekend admission (p < .0001) were more likely to be directly admitted to a SU. A higher proportion of quality indicators within predefined target ranges were achieved in hospitals with a higher proportion of SU admission (p = 0.0002). Quality of stroke care could be maintained even if certification was several years ago.

CONCLUSIONS

Differences in demographical and clinical characteristics regarding the probability of SU admission were observed. The influence of structural characteristics on adherence to evidence-based quality indicators was low.

Care pathways and healthcare use of stroke survivors six months after admission to an acute-care hospital in France in 2012

INTRODUCTION

Care pathways and healthcare management are not well described for patients hospitalized for stroke.

METHODS

Among the 51 million beneficiaries of the French national health insurance general scheme (77% of the French population), patients hospitalized for a first stroke in 2012 and still alive six months after discharge were included using data from the national health insurance information system (Sniiram). Patient characteristics were described by discharge destination-home or rehabilitation center (for < 3 months)-and were followed during their first three months back home.

RESULTS

A total of 61,055 patients had a first admission to a public or private hospital for stroke (mean age; 72 years, 52% female), 13% died during their stay and 37% were admitted to a stroke management unit. Overall, 40,981 patients were still alive at six months: 33% of them were admitted to a rehabilitation center (mean age: 73 years) and 54% were discharged directly to their home (mean age 67 years). For each group, 45 and 62% had been previously admitted to a stroke unit. Patients discharged to rehabilitation centers had more often comorbidities, 39% were highly physically dependent and 44% were managed in specialized neurology centers. For patients with a cerebral infarction who were directly discharged to their home 76% received at least one antihypertensive drug, 96% an antithrombotic drug and 76% a lipid-lowering drug during the following month. For those with a cerebral hemorrhage, these frequencies were respectively 46, 33 and 28%. For those admitted to a rehabilitation center, more than half had at least one visit with a physiotherapist or a nurse, 15% a speech therapist, 10% a neurologist or a cardiologist and 15% a psychiatrist during the following three months back home (average numbers of visits for those with at least one visit: 23 for physiotherapists and 100 for nurses). Patients who returned directly back home had fewer physiotherapist (30%) or nurse (47%) visits but more medical consultations. The 3-month re-hospitalization rate for patients who were discharged directly to their home was 23% for those who had been admitted to a stroke unit and 25% for the others. In rehabilitation centers, this rate was 10% for patients who stayed < 3 months.

CONCLUSIONS

These results illustrate the value of administrative databases to study stroke management, care pathways and ambulatory care. These data should be used to improve care pathways, organization, discharge planning and treatments.

Agreement between routine electronic hospital discharge and Scottish Stroke Care Audit (SSCA) data in identifying stroke in the Scottish population

Background

In Scotland all non-obstetric, non-psychiatric acute inpatient and day case stays are recorded by an administrative hospital discharge database, the Scottish Morbidity Record (SMR01). The Scottish Stroke Care Audit (SSCA) collects data from all hospitals managing acute stroke in Scotland to support and improve quality of stroke care. The aim was to assess whether there were discrepancies between these data sources for admissions from 2010 to 2011.

Methods

Records were matched when admission dates from the two data sources were within two days of each other and if an International Classification of Diseases (ICD) code of I61, I63, I64, or G45 was in the primary or secondary diagnosis field on SMR01. We also carried out a linkage analysis followed by a case-note review within one hospital in Scotland.

Results

There were a total of 22 416 entries on SSCA and 22 200 entries on SMR01. The concordance between SSCA and SMR01 was 16 823. SSCA contained 5593 strokes that were not present in SMR01, whereas SMR01 contained 185 strokes that were not present in SSCA. In the case-note review the concordance was 531, with SSCA containing 157 strokes that were not present in SMR01 and SMR01 containing 32 strokes that were not present in SSCA.

Conclusions

When identifying strokes, hospital administrative discharge databases should be used with caution. Our results demonstrate that SSCA most accurately represents the number of strokes occurring in Scotland. This resource is useful for determining the provision of adequate patient care, stroke services and resources, and as a tool for research.