How can stroke care be improved for younger service users? A qualitative study on the unmet needs of younger adults in inpatient and outpatient stroke care in Australia

Background: The incidence of young stroke is increasing worldwide. However, young adults are inadequately supported in their recovery by a system of stroke care in which the older patient is the majority consumer. Purpose: To examine the unmet needs of younger stroke survivors in inpatient and outpatient healthcare settings and identify opportunities for improved service delivery. Materials and Methods: In-depth semi-structured interviews were undertaken with 19 participants aged 18–55 at the time of their first-ever stroke and inductively analysed using a rigorous qualitative descriptive approach. Results: Many unmet care needs were identified within three emergent themes: inadequately addressed psycho-emotional and cognitive needs after young stroke; isolation from lack of information and structured support; and failure to deliver age-relevant patient-centred care. These themes were further divided into sub-themes and the sub-themes were named in a manner to signpost the way forward for young stroke care. Conclusions: This study provides new insights into the experience of inpatient and outpatient stroke care by younger stroke survivors and outlines possible improvements for clinical practice. Future research should evaluate the effect of targeted strategies to support younger adults after stroke.Implications for rehabilitationPost-stroke rehabilitation might be improved by providing more support for the non-physical effects of stroke (e.g., psycho-emotional support, cognitive rehabilitation).Younger stroke survivors may also benefit from a long-term community care plan and longer-term rehabilitation.Patient-centered rehabilitation and education about self-management interventions appear to be important areas for further development.Future research is required to evaluate the effect of targeted strategies to support younger stroke survivors, as well as identify the needs of younger adults with post-stroke communication impairment. Post-stroke rehabilitation might be improved by providing more support for the non-physical effects of stroke (e.g., psycho-emotional support, cognitive rehabilitation). Younger stroke survivors may also benefit from a long-term community care plan and longer-term rehabilitation. Patient-centered rehabilitation and education about self-management interventions appear to be important areas for further development. Future research is required to evaluate the effect of targeted strategies to support younger stroke survivors, as well as identify the needs of younger adults with post-stroke communication impairment.</p

table_1_Prediction of Outcome in Patients With Acute Ischemic Stroke Based on Initial Severity and Improvement in the First 24 h.docx

Introduction<p>Stroke severity measured by the baseline National Institutes of Health Stroke Scale (NIHSS) is a strong predictor of stroke outcome. Early change of baseline severity may be a better predictor of outcome. Here, we hypothesized that the change in NIHSS in the first 24 h after stroke improved stroke outcome prediction.</p>Materials and methods<p>Patients from the Leuven Stroke Genetics Study were included when the baseline NIHSS (B-NIHSS) was determined on admission in the hospital and NIHSS after 24 h could be obtained from patient files. The delta NIHSS, relative reduction NIHSS, and major neurological improvement (NIHSS of 0–1 or ≥8-point improvement at 24 h) were calculated. Good functional outcome (GFO) at 90 days was defined as a modified Rankin Scale of 0–2. Independent predictors of outcome were identified by multivariate logistic regression. We performed a secondary analysis after excluding patients presenting with a minor stroke (NIHSS 0–5) since the assessment of change in NIHSS might be more reliable in patients presenting with a moderate to severe deficit.</p>Results<p>We analyzed the outcome in 369 patients. B-NIHSS was associated with GFO (odds ratio: 0.82; 95% CI 0.77–0.86). In a multivariate model with B-NIHSS and age as predictors, the accuracy [area under the curve (AUC): 0.82] improved by including the delta NIHSS (AUC: 0.86; p < 0.01). In 131 patients with moderate to severe stroke, the predictive multivariate model was more accurate when including the RR NIHSS (AUC: 0.83) to the model which included B-NIHSS, age and ischemic heart disease (AUC: 0.77; p = 0.03).</p>Conclusion<p>B-NIHSS is a predictor of stroke outcome. In this cohort, the prediction of GFO was improved by adding change in stroke severity after 24 h to the model.</p

Additional file 1: of Hospital financing of ischaemic stroke: determinants of funding and usefulness of DRG subcategories based on severity of illness

Table S1. “Overview of laboratory tests and cost calculation”: this file contains a data table detailing typical lab tests carried out among stroke patients and the calclation of total cost. (DOCX 49 kb

Additional file 2: of Hospital financing of ischaemic stroke: determinants of funding and usefulness of DRG subcategories based on severity of illness

Table S2. “Overview of medical imaging procedures and cost calculation per SOI”: this file contains a data table with the rate of use of 49 different imaging tests, per SOI, and calculations of total imaging costs. (DOCX 54 kb

sj-docx-1-caj-10.1177_08465371241234545 – Supplemental material for Radiomics Studies on Ischemic Stroke and Carotid Atherosclerotic Disease: A Reporting Quality Assessment

Supplemental material, sj-docx-1-caj-10.1177_08465371241234545 for Radiomics Studies on Ischemic Stroke and Carotid Atherosclerotic Disease: A Reporting Quality Assessment by Ann-Marie Beaudoin, Jan Kee Ho, Adrienne Lam and Vincent Thijs in Canadian Association of Radiologists Journal</p

Self-evaluation of personal needs by community-living young stroke survivors using an online English language questionnaire

Identifying personal needs of young stroke survivors is crucial for their recovery. Identify factors, burden, and significance of unmet needs of young community-living stroke survivors. We used online advertising and word-of-mouth snowballing to recruit participants for an English language online questionnaire constructed for this purpose. Eligible participants aged 18–55 at time of stroke. Needs were classified into seven domains: Healthcare Experience, Impairments from Stroke, Everyday Activities, Work/Study, Finances, Relationships, and Social Participation. Random-effects logistic regression was used to determine the probability of unmet needs and X2 test to determine significance of distribution across domains. Out of 137 responses recorded: 32 did not meet inclusion criteria, 29 duplicates identified were discarded, and 76 eligible participants were analysed. Respondents were median 37 (IQR 32–47) years at time of stroke, and median 3 (1–5) years since stroke. Fifty-eight (76%) females. Modified Rankin Scale median score of 1 (1–3). Of 48 identified potential needs, 25 (IQR 19–30) were rated unmet. Twenty (IQR 15–25) considered of high significance. Unmet needs most frequently occurred in the domains: Impairments from Stroke, Finances, and Social Participation. There is high burden of unmet needs in community-living young stroke survivors which are spread disproportionately across the identified domains.IMPLICATIONS FOR REHABILITATIONIdentifying personal needs of young stroke survivors is crucial for their recovery.Impairments after Stroke, Finances, and Social Participation were often selected as being high burden unmet needs for community-living young people after stroke.Employing a post-stroke checklist to guide exploration of needs in young stroke may better capture which needs are unmet. Identifying personal needs of young stroke survivors is crucial for their recovery. Impairments after Stroke, Finances, and Social Participation were often selected as being high burden unmet needs for community-living young people after stroke. Employing a post-stroke checklist to guide exploration of needs in young stroke may better capture which needs are unmet.</p

sj-docx-1-cre-10.1177_02692155231172295 - Supplemental material for Dose, Content, and Context of Usual Care in Stroke Upper Limb Motor Interventions: A Systematic Review

Supplemental material, sj-docx-1-cre-10.1177_02692155231172295 for Dose, Content, and Context of Usual Care in Stroke Upper Limb Motor Interventions: A Systematic Review by Sarah P Newton, Emily J Dalton, Jia Y Ang, Marlena Klaic, Vincent Thijs and Kathryn S Hayward in Clinical Rehabilitation</p

sj-docx-1-nnr-10.1177_15459683241229676 – Supplemental material for Prevalence of Arm Weakness, Pre-Stroke Outcomes and Other Post-Stroke Impairments Using Routinely Collected Clinical Data on an Acute Stroke Unit

Supplemental material, sj-docx-1-nnr-10.1177_15459683241229676 for Prevalence of Arm Weakness, Pre-Stroke Outcomes and Other Post-Stroke Impairments Using Routinely Collected Clinical Data on an Acute Stroke Unit by Emily J. Dalton, Rebecca Jamwal, Lia Augoustakis, Emma Hill, Hannah Johns, Vincent Thijs and Kathryn S. Hayward in Neurorehabilitation and Neural Repair</p

Information Transfer Rate for all patients and for both systems plotted against the patients' ALSFRS-R scores.

<p>Note that the two most impaired patients have the lowest performance for both BCIs; however, no correlation was found between those two measures.</p

Image_1_Optimizing Resources for Endovascular Clot Retrieval for Acute Ischemic Stroke, a Discrete Event Simulation.TIFF

Objective: Endovascular clot retrieval (ECR) is the standard of care for acute ischemic stroke due to large vessel occlusion. Performing ECR is a time critical and complex process involving many specialized care providers and resources. Maximizing patient benefit while minimizing service cost requires optimization of human and physical assets. The aim of this study is to develop a general computational model of an ECR service, which can be used to optimize resource allocation.Methods: Using a discrete event simulation approach, we examined ECR performance under a range of possible scenarios and resource use configurations.Results: The model demonstrated the impact of competing emergency interventional cases upon ECR treatment times and time impact of allocating more physical (more angiographic suites) or staff resources (extending work hours).Conclusion: Our DES model can be used to optimize resources for interventional treatment of acute ischemic stroke and large vessel occlusion. This proof-of-concept study of computational simulation of resource allocation for ECR can be easily extended. For example, center-specific cost data may be incorporated to optimize resource allocation and overall health care value.</p