scholarly journals Stroke in neurological services in Italy

2009 ◽  
Vol 1 (1) ◽  
pp. 8 ◽  
Author(s):  
Fabrizio Antonio De Falco ◽  
Maurizio A. Leone ◽  
Ettore Beghi
Keyword(s):  
Multivariate Analysis ◽  
Ct Scan ◽  
Stroke Unit ◽  
Emergency Setting ◽  
Discharge Diagnosis ◽  
Stroke Patients ◽  
Stroke Units ◽  
Very High ◽  
Italian Neurological ◽  
Structured Questionnaire

o assess the stroke workload of Italian neurological services and to correlate it with indicators of each hospital’s emergency setting. A semi-structured questionnaire was sent to the 220 neurology units (NU) located in hospitals with an emergency room (ER) (155 responders, 71%). Stroke was the most common discharge diagnosis (29%) (273 patients/year/NU on average) and condition requiring consultation in ER (28%). A stroke unit was available in 28% of NU, bedside monitors in 45%, a 24 hour/day and 7 day/week (24/7) CT scan in 90%, a 24/7-MRI in 32%, a 24/7 on-duty neurologist in 36%. The stroke workload was correlated only with the number of ER consultations per year, and marginally to the presence of stroke units and the number of monitored beds in the univariate, but not in the multivariate analysis. The stroke workload in Italian NU is very high, but is largely unrelated to their structural and functional characteristics, in contrast with the international indications requiring several essential criteria for the best hospital management of all stroke patients.

Stroke Rehabilitation 2007: What Should it Be?

2007 ◽  
Vol 2 (3) ◽  
pp. 191-200 ◽  
Author(s):  
Helen M. Dewey ◽  
Lisa J. Sherry ◽  
Janice M. Collier
Keyword(s):  
Stroke Unit ◽  
Stroke Rehabilitation ◽  
Number Needed To Treat ◽  
Stroke Patients ◽  
High Quality ◽  
High Quality Research ◽  
Stroke Units ◽  
Proven Efficacy ◽  
Stroke Unit Care ◽  
Medical Wards

Background There are an estimated 62 million stroke survivors worldwide. The majority will have long-term disability. Despite this reality, there have been few large, high-quality randomized controlled trials of stroke rehabilitation interventions. Summary of review There is excellent evidence for the effectiveness of a number of stroke rehabilitation interventions, notably care of stroke patients in inpatient stroke units and stroke rehabilitation units providing organized, goal-focused care via a multidisciplinary team. Stroke units (in comparison with care on general medical wards) effectively reduce death and disability with the number needed to treat to prevent one person from failing to regain independence being 20. Unfortunately, only a minority of stroke patients have access to stroke unit care. The key principles of effective stroke rehabilitation have been identified. These include ( 1 ) a functional approach targeted at specific activities e.g. walking, activities of daily living, ( 2 ) frequent and intense practice, and ( 3 ) commencement in the first days or weeks after stroke. Conclusion The most effective approaches to restoration of brain function after stroke remain unknown and there is an urgent need for more high-quality research. In the meantime, simple, broadly applicable stroke rehabilitation interventions with proven efficacy, particularly stroke unit care, must be applied more widely.

scholarly journals The Stroke Unit Story: Where Have We Been and Where Are We Going?

2021 ◽  
pp. 1-8
Author(s):  
Peter Langhorne
Keyword(s):  
Collaborative Research ◽  
Stroke Unit ◽  
Final Section ◽  
Evidence Base ◽  
Stroke Severity ◽  
Stroke Patients ◽  
Stroke Units ◽  
History Of ◽  
Stroke Unit Care ◽  
Stroke Type

<b><i>Background:</i></b> The concept of stroke unit care has been discussed for over 50 years, but it is only in the last 25 years that clear evidence of its effectiveness has emerged to inform these discussions. <b><i>Summary:</i></b> This review outlines the history of the concept of stroke units to improve recovery after stroke and their evaluation in clinical trials. It describes the first systematic review of stroke unit trials published in 1993, the establishment of a collaborative research group (the Stroke Unit Trialists’ Collaboration), the subsequent analyses and updates of the evidence base, and the efforts to implement stroke unit care in routine settings. The final section considers some of the remaining challenges in this area of research and clinical practice. <b><i>Key Messages:</i></b> Good quality evidence confirms that stroke patients who are looked after in a stroke unit are more likely to survive and be independent and living at home 1 year after their stroke. The apparent benefits are independent of patient age, sex, stroke type, or initial stroke severity. The benefits are most obvious in units based in a discrete ward (stroke ward). The current challenges include integrating effective stroke units with more recent systems to deliver hyper-acute stroke interventions and implementing stroke units in lower resource regions.

scholarly journals Hemorrhagic transformation predictors in ischemic stroke patients from a Stroke Unit

2021 ◽  
Author(s):  
Fernanda Ferreira de Abreu ◽  
Vinícius Bessa Mendez ◽  
Ivã Taiuan Fialho Silva ◽  
Alice Monteiro Soares Cajaíba ◽  
Pedro Antonio Pereira de Jesus
Keyword(s):  
Atrial Fibrillation ◽  
Ischemic Stroke ◽  
Ct Scan ◽  
Computer Tomography ◽  
Prospective Cohort ◽  
Stroke Unit ◽  
Hemorrhagic Transformation ◽  
Stroke Patients ◽  
Nihss Score ◽  
Toast Classification

Background: Hemorrhagic transformation (HT) is an aggravating factor to patients with ischemic stroke. For patients’ best care, it’s essential to know its predictors. Objective: To describe HT in patients with ischemic stroke. Design and setting: Prospective cohort with ischemic stroke patients from a Stroke Unit, admitted between 2017 to 2019. Methods: All patients performed a brain computer tomography (CT) scan on arrival and 24-hours later. Patients with or without HT were compared for predictors. Results: 363 patients were included, with a mean age of 63,14 (±13,92), 53,1% were male and 9,9% (n= 38) had HT. Thrombolysis didn’t increase the risk of HT [(55,3% vs 42,5%); p= 0,132]. Patients with atrial fibrillation [(31,6% vs 12,6%); p= 0,002], and cardioembolic etiology according with TOAST classification [(57,6% vs 21,7%); p< 0,001] had higher risk of HT. Patients with HT had lower ASPECTS scores on their initial CT [8 (6-9) vs 9 (8-10); p< 0,001] and higher NIHSS scores [12 (9-15) vs 8 (5-12); p< 0,001]. Cardioembolic strokes [OR= 4,67; (IC95% 2,01-10,84)] and higher NIHSS [OR= 1,11; (IC95% 1,01-1,22)] were independently associated with HT after multivariate adjustments, considering ASPECTS and thrombolysis. Conclusion: Cardioembolic etiology and higher NIHSS score were independently associated with HT. It’s essential to know HT predictors due to worse outcomes associated with its occurrence.

scholarly journals Stroke unities: the role of the occupational therapist and the perception of the multidisciplinary team

2021 ◽  
Vol 4 (6) ◽  
pp. 102-105
Author(s):  
António Arsénio Duarte ◽  
Ana Paula Martin ◽  
Diana Santos ◽  
Rafael Santos ◽  
Rita Viegas
Keyword(s):  
Acute Stroke ◽  
Multidisciplinary Team ◽  
Stroke Unit ◽  
Occupational Therapist ◽  
Medical Emergency ◽  
Structured Interviews ◽  
Stroke Patients ◽  
Stroke Units ◽  
The World

Every second a person in the world suffers from a stroke, not surprising, therefore, that stroke is the leading cause of death and morbidity in Portugal. Increasingly, acute stroke is considered a medical emergency. The evidence proves that the treatment of these patients in specialized units (stroke units) is effective in acute stroke. A stroke unit is a hospital area where professionals with specific, well-defined training work, who provide care to stroke patients who are already stabilized, but are still in an acute phase(DGS, 2001). The aim of this study is to understand the role of the occupational therapist in stroke units and to identify the perspective of the multidisciplinary team on their work, clarifying what are the advantages of this professional in the team. The study falls within the qualitative paradigm, exploratory and descriptive. Semi-structured interviews were performed to 39 health professionals. The technique used was the content analysis of interviews. Based on previously established categories, other categories emerged.

Stroke units: research in practice

2015 ◽  
Author(s):  
Lalit Kalra
Keyword(s):  
Stroke Unit ◽  
Stroke Care ◽  
Evidence Base ◽  
Multidisciplinary Teams ◽  
Stroke Patients ◽  
Stroke Units ◽  
Key Points ◽  
Stroke Unit Care ◽  
Rehabilitation Needs ◽  
Therapy Sessions

Key points• Stroke units are the cornerstone of quality stroke care.• The benefits of stroke unit care are supported by a very strong evidence base• In 2007 the National Stroke Strategy mandated that all stroke patients should have prompt access to stroke unit care.• Despite policy and guidelines, only 62% stroke patients were treated on specialist stroke units in 2010.• Patients spend long periods of inactivity on stroke units; multidisciplinary teams need to encourage rehabilitation activities outside therapy sessions.• Rehabilitation needs to be family- and carer-oriented to prepare patients for life after discharge.

scholarly journals 55 A Review of Stroke Demographics and Outcomes at a Regional Hospital without a Stroke Unit

2019 ◽  
Vol 48 (Supplement_3) ◽  
pp. iii17-iii65
Author(s):  
Lushen Pillay ◽  
Kushan Galav ◽  
Deeptish Tulsi ◽  
Joanna McGlynn ◽  
John Doherty ◽  
...  
Keyword(s):  
Mortality Rate ◽  
Length Of Stay ◽  
Stroke Unit ◽  
Average Length ◽  
Length Of Hospital Stay ◽  
Local Analysis ◽  
Stroke Patients ◽  
Stroke Units ◽  
Average Length Of Stay ◽  
Stroke Register

Abstract Background According to the 2017 National Stroke Register Report; 75% of strokes occur in patients aged 65 years and older. Within the audit 19 stroke units reported that 70.6% of stroke patients were admitted to a stroke unit and their median length of stay of 9 days. Numerous studies have shown better outcomes in patients admitted to a stroke unit versus a medical unit leading to national stroke networks and bypass protocols for patients. However, stroke patients can still be found in non-stroke unit hospitals such as our own. Methods Demographics from HIPE data was collected on all stroke patients admitted to our hospital between January 1st and December 31st 2017. Basic statistical methods were used to analyse the data. Results We analyzed 103 patient records. The average age at presentation was 73 years (range: 35-97) and 60.1% were males. The average length of hospital stay was 16.1 days (range 1- 130 days). Ischemic (77%) events were more common than haemorrhagic events (23%). The three most common co-morbidities were hypertension (45%), hyperlipidemia (30%) and atrial fibrillation (19%). Discharge destination was home (66%), nursing home (14%), national rehabilitation (2%) and an 18% mortality rate within 3 months. The mortality rate was higher in the hemorrhagic (42%) compared to ischemic (11%). Conclusion The average length of stay was 16.1 days, considerably higher than the national stroke unit average of 9. The overall mortality rate was 5% higher than the national of 13%. Limited rehabilitation services and time awaiting national rehabilitation beds contributed to the long LOS. There is a definite need for a dedicated stroke service at our hospital, local analysis suggests that 6 beds would meet the needs of our catchment area; and this would lead to better outcomes for stroke patients. A further locally dedicated stroke audit is needed.

scholarly journals Five Years of Acute Stroke Unit Care: Comparing ASU and Non-ASU Admissions and Allied Health Involvement

2014 ◽  
Vol 2014 ◽  
pp. 1-5
Author(s):  
Isobel J. Hubbard ◽  
Malcolm Evans ◽  
Sarah McMullen-Roach ◽  
Jodie Marquez ◽  
Mark W. Parsons
Keyword(s):  
Length Of Stay ◽  
Acute Stroke ◽  
Stroke Unit ◽  
Allied Health ◽  
Stroke Patients ◽  
Stroke Units ◽  
John Hunter ◽  
Acute Stroke Unit ◽  
Allied Healthcare ◽  
Over Time

Background.Evidence indicates that Stroke Units decrease mortality and morbidity. An Acute Stroke Unit (ASU) provides specialised, hyperacute care and thrombolysis. John Hunter Hospital, Australia, admits 500 stroke patients each year and has a 4-bed ASU.Aims.This study investigated hospital admissions over a 5-year period of all strokes patients and of all patients admitted to the 4-bed ASU and the involvement of allied health professionals.Methods.The study retrospectively audited 5-year data from all stroke patients admitted to John Hunter Hospital(n=2525)and from nonstroke patients admitted to the ASU(n=826). The study’s primary outcomes were admission rates, length of stay (days), and allied health involvement.Results.Over 5 years, 47% of stroke patients were admitted to the ASU. More male stroke patients were admitted to the ASU (chi2=5.81;P=0.016). There was a trend over time towards parity between the number of stroke and nonstroke patients admitted to the ASU. When compared to those admitted elsewhere, ASU stroke patients had a longer length of stay (z=−8.233;P=0.0000) and were more likely to receive allied healthcare.Conclusion.This is the first study to report 5 years of ASU admissions. Acute Stroke Units may benefit from a review of the healthcare provided to all stroke patients. The trends over time with respect to the utilisation of the John Hunter Hospitall’s ASU have resulted in a review of the hospitall’s Stroke Unit and allied healthcare.

Abstract W P232: Lower Rates of Delirium in Stroke Units May Reflect Selection Bias

Stroke ◽  
2014 ◽  
Vol 45 (suppl_1) ◽  
Author(s):  
Eric M Liotta ◽  
Carlos Corado ◽  
Deborah L Bergman ◽  
Richard A Bernstein ◽  
Fan Z Caprio ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Ischemic Stroke ◽  
Acute Ischemic Stroke ◽  
Selection Bias ◽  
Stroke Unit ◽  
Cardioembolic Stroke ◽  
Stroke Patients ◽  
Stroke Units ◽  
Entire Cohort ◽  
Stroke Mechanism

Introduction: Studies of delirium after acute stroke focus on stroke units (SUs). A protective effect of SUs against delirium has been suggested. We hypothesized that selection bias against medically complex patients accounts for this apparent effect. Methods: An observational cohort of acute ischemic stroke patients was screened for post-stroke delirium. Delirium was diagnosed using the Confusion Assessment Method (CAM). Key patient variables were prospectively recorded including initial NIHSS score and medical complications. Univariate associations with delirium were identified and a logistic regression model was developed for the entire cohort. Separate logistic regression models were also developed for non-stroke unit (NSU) and SU patients. The SU consisted of a specialized stroke ward, step-down stroke unit, and a neuroscience ICU. Results: Over 10 months 246 patients (56% male, mean 65 years, 29% in NSUs) met inclusion criteria. Delirium occurred in 30 (12%) patients and was less frequent in the SU (8.0% vs 22.5%, p=0.002). Frequency of CAM checks differed between NSU and SU (median 4.1 vs 3.7 per day; p=0.03). NSU patients had similar NIHSS scores as SU patients (median [interquartile range], 3 [1-8] vs 3 [1-5]; p=0.18) but more ICU admissions (48% vs 27%, p=0.001) and more infections (18% vs 9.7%, p=0.06). In the entire cohort, initial NIHSS (OR 1.07, 95% CI 1.02-1.13; p=0.006), cardioembolic stroke mechanism (OR 3.0, 95% CI 1.3-6.9; p=0.009) and SU care (OR 0.39, 95% CI 0.17-0.88; p=0.02) predicted delirium after correcting for covariates, including frequency of CAM checks. In the NSU model, age (OR 1.06, 95% CI 1.01-1.11; p=0.02) and infections (OR 6.8, 95% CI 1.5-30.2; p=0.01) were associated with delirium. Only cardioembolic stroke mechanism (OR 5.4, 95% CI 1.7-16.7; p=0.003) was associated with delirium in the SU model. Conclusion: Associations with delirium after acute ischemic stroke differ between NSU and SU patients. Stroke patients treated in NSUs are fundamentally different than SU patients. Given the potential for residual confounding, the lower incidence of delirium after stroke in SUs than NSUs may reflect selection bias rather than a specific effect of SU care.

Abstract WP76: Artificial Intelligence CTA Vessel Density Mapping to Enhance Identification of Large Vessel Occlusions in Mobile Stroke Unit

Stroke ◽  
2020 ◽  
Vol 51 (Suppl_1) ◽  
Author(s):  
Kevin Brown ◽  
Bryan Villareal ◽  
Kenneth Harrell ◽  
Mersedeh Bahr Hosseini ◽  
Lucas Restrepo-Jimenez ◽  
...  
Keyword(s):  
Stroke Unit ◽  
Clinical Decision Making ◽  
Vessel Density ◽  
Large Vessel ◽  
Stroke Patients ◽  
Anterior Circulation ◽  
Vessel Occlusion ◽  
Stroke Units ◽  
Density Mapping ◽  
Mobile Stroke Unit

Background: Equipped with CT scanners capable of imaging the brain parenchyma and vasculature, Mobile Stroke Units (MSU) have the ability to image, diagnose and treat stroke patients in the prehospital setting. Automated CTA vessel density mapping could enhance frontline neurologist scan review in identifying large vessel occlusion (LVO), ensuring appropriate patient diagnosis and routing. Methods: We analyzed consecutive acute ischemic stroke patients undergoing CTA imaging in a regional Mobile Stroke Unit. Automated CTA vessel density mapping was performed in the field immediately after scan completion. CTA source images were wirelessly transferred to an off-site processing server (RAPID.Ai, IschemiaView) for artery reconstruction and color-coded density mapping, with blue, green, yellow, and red color shading indicating vessel density decreases of 70%-85%, 60%-75%, 45%-60%, and <45%. Results: Among all 16 patients, median processing time was 186 secs, and all images were available in time to aid clinical decision-making. Overall, automated processing yielded evaluable images in 94% (suboptimal contrast opacification precluded analysis of 1). Of the 15 diagnostically adequate exams, 100% (15/15) showed concordance for identification of anterior circulation occluded/abnormal vessel territories between automated CTA vessel density mapping and expert physician final CTA interpretation. Cases included true positives in 7, and true negatives in 8. Among true positives, CTA vessel density mapping identified the symptomatic occlusion in 6/6 and also correctly identified a severe cervical ICA stenosis unrelated to the clinical presentation in 1/1. Correctly detected intracranial occlusions included: ICA-17%. M1-17%, M1-M2 junction-17%, and M2-50%. Degree of vessel density diminution correlated with proximal-distal occlusion location. Conclusion: CTA vessel density mapping can feasibly and efficiently be conducted in Mobile Stroke Units and shows high accuracy in detection of large and medium intracranial vessel occlusions. Extension of mapping to the intracranial posterior circulation and algorithmic adjustment for proximal cervical stenoses/occlusions would further improve utility in aiding prehospital routing.

Abstract 267: Improving Inpatient Stroke Care by Implementing Stroke Units Across Health Systems Using an Improvement Collaborative Approach

2014 ◽  
Vol 7 (suppl_1) ◽  
Author(s):  
Noreen Kamal ◽  
Pamela Aikman ◽  
Philip Teal ◽  
Michael Suddes ◽  
Todd Collier ◽  
...  
Keyword(s):  
Quality Improvement ◽  
Stroke Unit ◽  
Best Practice ◽  
Interdisciplinary Team ◽  
Stroke Care ◽  
Quality Improvement Initiative ◽  
Stroke Patients ◽  
Acute Stroke Care ◽  
Learning Session ◽  
Stroke Units

Background: Stroke units, defined as a geographic location where stroke patients are cared for by an interdisciplinary team, hold the strongest evidence in reduced mortality and disability for stroke patients. However, according to the 2011 Canadian Stroke Network’s National Stroke Audit, only 23% of stroke patients in Canada were admitted to a Stroke Unit with the Canadian province of British Columbia (BC) lagging at only 4%. The objective of this quality improvement initiative was to increase the number of stroke units and to improve existing stroke units; additionally, we aimed to improve adherence to best practice acute stroke care. Methods: Using the Institute for Healthcare Improvement’s Breakthrough Series Collaborative methodology, a stroke unit Improvement Collaborative was run from January 2013 to December 2013 by Stroke Services BC, a program of the Provincial Health Services Authority in BC. Faculty members were recruited from BC and the Calgary Stroke Program in the province of Alberta. The collaborative had 4 Learning Sessions, a closing workshop, and bi-weekly webinars. Teams followed a structured 7-step framework: understanding current volumes; securing space; establishing the team; ensuring clinical best practice; creating processes for team communication; ensuring patient engagement; and establishing quality improvement mechanisms. Pre and post self-reports of care were collected through electronic polling at Learning Session 2 in February 2013 (pre, n=78) and at the Closing Celebration in December 2013 (post, n=66) using a 4-point Likert scale. There were 20 questions based on best practice. Results: Eleven teams enrolled representing 17 hospitals in BC and a hospital in Saskatoon in the province of Saskatchewan. Teams were either working at the hospital or health region level. There were a total of 75 new stroke beds created in BC, and 12 beds recommended for Saskatoon. Furthermore, the results from the e-voting on best practice showed statistically significant improvement in the following areas: admission to a stroke unit (p=0.005); assessment by an interdisciplinary team within 48 hours of admission (p=0.002); use of standardized valid tools (p=0.002); swallowing screen within 24 hours (p<0.001); core interprofessional team on the stroke unit (p<0.001); care to prevent secondary complication (p<0.001); management of serum lipid levels (p=0.017); patient education (p<0.001); and team education (p=0.02). Conclusions: This inter-provincial Quality Improvement Collaborative was successful in implementing and improving stroke units, and in improving best practice care of inpatient stroke patients. Critical success factors include the engagement of faculty from high-performing centers even if they exist outside the jurisdiction where improvement is sought, and the use of the 7-step framework for implementing stroke units.

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