In-hospital Stroke Patients Research Articles

Abstract WP290: Endovascular Treatment Of In-hospital Strokes: An Open Book

INTRODUCTION: In-hospital stroke (IHS) presents a different treatment challenge than out of hospital stroke. IHS often has contraindication to IV tPA, such as such as recent surgery, MI, and use of anticoagulation. Intra-arterial therapy (IAT) with tPA and/or mechanical thrombectomy is an option for large vessel acute IHS with contraindications to or fail to recanalize with IV tPA, to restore cerebral perfusion. Objective: To assess the characteristics and outcomes of patients with in-hospital strokes large vessel occlusion who receive IAT. Methods: From our database of patients from 1/1/2008 to 12/31/2011 who had IAT for an acute stroke due to large vessel occlusion, in hospital strokes and out of hospital strokes were identified. Patient characteristics, imaging, and outcomes were retrospectively collected. Statistical analysis was performed on JMP 9.0. Result: 151 patients were included, 23 (15%) were in-hospital strokes (IHS) and 128 (85%) were out of hospital strokes (OHS). Initial median NIHSS of 17 and 16 respectively (p=0.3). IHS were frequently in the cardiology/CTS service (14, 60%) for CHF and cardiac valve repair (12, 52%). Other comorbidities present were atrial fibrillation (68%), hypertension (68%), and hyperlipidemia (56%). Seven (30%) were on warfarin prior to admission, but all had subtherapeutic INR. Three (13%) IHS received IV tPA. The time from last known well (LKW) to non-contrast CT brain was 80 min, and to CTA was 113 min in IHS, and 147 min and 229 min respectively in OHS (p = 0.0003). 20 (87%) had lesion in the anterior circulation. LKW to IAT recanalization was 248 min in IHS, compared to 375 min in OHS. Recanalization rate was 68% for IHS and 81% for OHS (p=0.2). Nine (39%) IHS had favorable mRS of 1 to 3 at 90 days, compared to 44 (34%) OHS, (p = 0.6). Despite faster recanalization time, there was no difference in the 90 day mortality of IHS v OHS (48% vs 30%, p = 0.1), and IHS had greater 1 year mortality (65% vs 30%, p = 0.005). Discussion: In-hospital strokes have higher mortality than out of hospital strokes. There is a role for IAT In carefully selected IHS with large vessel occlusion. A multicenter study is needed to reveal the characteristics of IHS patients who may benefit from IAT.

Abstract 3097: Acute In-hospital Stroke: How Do We Do Compared To Strokes In The Emergency Department?

Introduction: Intravenous tissue plasminogen activator (IV tPA) has been approved for treating strokes up to 3 hours after onset of symptoms and may be beneficial up to 4.5 hours in patients who qualify. Additionally, neuro-intervention, i.e., intra-arterial thrombolysis or thrombectomy, is also an approved treatment option. Population studies show that 6% receive IV tPA within 3 hours of stroke onset. However, in-hospital strokes present challenges to treating within an adequate time. We present here our experience with in-hospital strokes, treatments, and identifiable delays in treatments. Methods: Single, tertiary center retrospective study of 55 in-hospital strokes over a one-year period from January 2009 to January 2010, and strokes in the Emergency Department over 6 month period from January 2010 to June 2010. Results: Twenty-nine in-hospital strokes were evaluated within 3 hours of symptoms onset. Two (6.9%) received IV tPA, and four (13.8%) received neuro-intervention (either intra-arterial thrombolysis or thrombectomy). None of the patients who presented greater than 3 hours after symptom onset was treated with any treatment (n=28). When compared to patients who present to the ED within 3 hours, in-hospital strokes were less likely to get IV tPA (6.9% vs. 20.8%), and they were more likely to receive neuro-intervention (13.8% vs. 10.3%). Neuro-intervention was performed on 9.09% of all in-hospital strokes (1 of 5 presented beyond the 3 hour time window). For in-hospital strokes that receive any treatment within 3 hours, the average time to neurology evaluation, to CT, and to treatment are 35 min, 68 min, and 237 min, respectively. For strokes in the Ed, the average time to evaluation, to CT, and to treatment are 90 min, 28 min, and 66 min respectively. The delay for in-hospital strokes is in obtaining the CT and initiating the treatment. Discussion: In-hospital stroke patients wait longer than their ED counterparts to be taken to CT and to receive stroke treatment. They are also less likely to receive IV tPA, and more likely to receive neuro-intervention. The longer time to neuro-imaging and thrombolytic treatment may reflect the fact that patients suffering in-hospital strokes have more complex medical co-morbidities that must be taken account during the evaluation and administration of thrombolytic therapy.

“Code Stroke”: Hospitalized versus Emergency Department Patients

Stroke rapid-response ("code stroke") teams facilitate the evaluation and treatment of patients presenting to emergency departments (EDs). Little is known about the usefulness of code stroke systems for patients hospitalized primarily for other conditions. We hypothesized that the yield of code stroke evaluations would be lower in hospitalized than in ED patients, and sought to identify potential targets for quality improvement efforts. Diagnoses and management of in-hospital and ED code stroke patients were assessed retrospectively in a Joint Commission-certified primary stroke center over a 1-year period. A total of 93 in-hospital and 204 ED code strokes were identified during this period. Compared with the ED patients, the hospitalized patients were less likely to have had a stroke/transient ischemic attack (26.8% vs 51.4%; P < .0001) and less likely to have been treated with a thrombolytic agent (odds ratio, 0.27; 95% confidence interval, 0.07-0.97: P = .03). Conditions not necessitating immediate neurologic care accounted for 63.4% of in-hospital strokes, compared with 31.3% of ED code strokes (P < .0001). "Altered mental status" was the sole presenting symptom in 48% of the hospitalized patients, compared with only 10% of ED patients (P < .0001), and was the only clinical feature independently associated with a stroke mimic in the hospitalized patients (odds ratio, 63.52; 95% confidence interval, 7.37-547.69; P = .0002). There was no association between a final diagnosis of a stroke mimic and patient age, sex or race-ethnicity or nursing shift. The proportions of patients with acute ischemic stroke and patients treated with thrombolytics after activation of in-hospital code stroke were small, and were lower than those of patients with ED code stroke in the same hospital over the same time period. Developing a standardized assessment protocol for hospitalized patients with altered mental status may improve the efficacy of care.

Improving stroke alert response time: Applying quality improvement methodology to the inpatient neurologic emergency

Stroke often leaves its victims with devastating disabilities if not treated promptly. Guidelines recommend that brain imaging be obtained within 25 minutes, yet this benchmark is rarely achieved for the in-hospital stroke. To reduce time to evaluation for strokes occurring in patients already hospitalized, through systematic analysis of current processes and application of standardized quality improvement methodology. Improving the quality of care for in-hospital stroke patients involved 4 key steps: (1) creation of a detailed process map to identify inefficiencies in the current process for identifying and treating hospitalized stroke patients, (2) development of an optimized care pathway, (3) implementation of a checklist of optimal practices for the acute stroke response team and nursing staff, and (4) real-time feedback. Time from stroke alert to initiation of computed tomography (CT) scan was prospectively tracked for the 6-month period prior to intervention. After a 3-month interval for intervention roll-out, the response times for the pre-intervention period were compared to a 6-month post-intervention evaluation period. Pre-intervention median inpatient stroke alert-to-CT time was 69.0 minutes, with 19% meeting the goal of 25 minutes from alert to CT time. Post-intervention median inpatient stroke alert-to-CT time was reduced to 29.5 minutes, with 32% at goal (P < 0.0001). This inpatient stroke alert quality improvement initiative decreased median inpatient alert-to-CT time by 57%, and demonstrated that speed of in-hospital stroke evaluation can be improved through systematic application of quality improvement principles.

Author Response to Social Marketing and the FAST Campaign.

Dear Editor, We thank Dr Bolam and colleagues from the National Stroke Foundation of Australia for their letter regarding our paper evaluating the FAST campaign in a sample of stroke patients and bystanders. These authors make significant points regarding the potential reach of stroke awareness campaigns that have limited funding and exposure. We agree that these should be considered when reading our paper. We also acknowledge that the evaluation of the awareness of such campaigns needs to be performed on a larger scale. However, the benefits of undertaking such an evaluation on a patient population similar to the one in this publication should not be discounted. In our paper we have acknowledged the study limitations outlined by Bolam et al. We do however feel that the sample interviewed was a valid representation of stroke patients who attend a public hospital, and their responses were indicative of the retention of a health message such as the FAST campaign, as it was undertaken at that time. Our results would suggest that the FAST information may not be reaching those who potentially can benefit the most – stroke patients and their families. Indeed such information, if replicated on a larger scale, could be used to convince public health authorities to invest in the FAST campaign. We would also like to take this opportunity to clarify a misinterpretation of the data regarding the population sample. In their letter Bolam et al. note ‘‘the unusually high proportion of inhospital stroke patients excluded, 23% of all stroke admissions’’. The 23% of patients they refer to as ‘‘in-hospital strokes’’ included in-hospital strokes as well as those strokes occurring in patients in institutional care (nursing homes and rehabilitation). The exclusion of these patients was intentional because the focus of this study was to obtain a community, lay-persons perspective. Yours sincerely,

Risk factors and treatment of stroke in Chinese young adults

Objective: To evaluate the risk factors and treatment status of Chinese stroke patients aged 35–45 years old.Methods: We collected data from 1988 in-hospital stroke patients aged 35–45 years old from 36 hospitals in mainland China and compared it to 12,260 health controls with the same age. Information about stroke risk factors was obtained through a questionnaire. Multiple logistic regression and chi-square test were performed to explore the association between risk factors and stroke in young patients.Results: Of the stroke patients, 94·3% had an ischemic stroke and 73·0% were male. Frequencies of stroke risk factors were significantly higher in patients than those in controls, including history of hypertension (41·0% versus 9·0%, p<0·05), diabetes (5·2% versus 1·7%, p<0·05), hypercholesterolemia (4·2% versus 2·9%, p<0·05), heart diseases (7·2% versus 1·6%, p<0·05), stroke (14·9% versus 1·3%, p<0·05), smoking (38·8% versus 33·3%, p<0·05) and drinking (38·0% versus 24·9%, p<0·05). Furthermore, only 12·8% of patients with hypertension took antihypertensive drugs regularly, and 27·9% of diabetic patients took hypoglycemic drugs regularly. Risk factors when compared between male and female patients were as follows: history of heart diseases (5·9 versus 10·8, p<0·05), smoking (50·9 versus 6·5, p<0·05) and drinking (50·4 versus 5·8, p<0·05).Conclusion: Majority of the Chinese stroke patients aged 35–45 years were male and had suffered an ischemic stroke. The history of stroke, heart disease and hypercholesterolemia could increase the risk of stroke in young adults, and the risk factors in the order of importance were hypertension, smoking, alcohol drinking, previous stroke, heart disease, diabetes mellitus and hyperlipidemia. Hypertension, smoking and alcohol drinking were found to be the main risk factors; treatment state and lifestyle should be improved for young stroke patients.

Subtypes and case-fatality rates of stroke:: A hospital-based stroke registry in Taiwan (SCAN-IV)

Stroke data bank can afford important information regarding risk factors, pathogenesis, prognosis, etc. By means of hospital-based stroke registry, we investigated the risk factors and case-fatality rates in different types of stroke and transient ischemic attack (TIA) patients at the National Taiwan University Hospital in 1995. After excluding ineligible patients, 995 patients aged 1–98 years (575 men and 420 women) were recruited. Men predominated in all age groups for stroke and TIA in general except for cerebral hemorrhage (CH) in patients aged <35 years and subarachnoid hemorrhage (SAH) in patients aged ≥45 years. Of these, 676 (67.9%), 41 (4.1%), 228 (22.9%) and 50 (5%) patients were classified in the categories of cerebral infarction (CI), TIA, CH and SAH, respectively. The CI/CH ratio was 2.96. Hypertension remained one of the most important risk factors for CI, CH and TIA patients. Severe extracranial carotid artery stenosis (≥50%) was found in 12% of the CI patients and 27% of the TIA patients, but not found in the CH and SAH patients. Of these patients, the 30-day case-fatality rate was 10.9%, highest in SAH (30%), followed by CH (24.1%) and CI (5.6%). There were 41 in-hospital stroke patients who had significantly higher case-fatality rates than the other stroke patients ( P<0.001 for all stroke, CI and CH patients by χ 2 test). As compared to the previous stroke registries in Taiwan, there is a secular trend of increasing CI/CH ratios. These findings in Taiwan were compared with those in other populations, including other Asian, Caucasian and black populations. The CI/CH ratios in Asian populations, including Chinese, Japanese and Korean, were much lower than those in Caucasian and black populations. Dietary, environmental and genetic factors probably play important roles in these differences.

Evaluation times for patients with in-hospital strokes.

Each year at least 35,000 people suffer a stroke while hospitalized, but little is known about the clinical characteristics of such patients or how rapidly they are identified and evaluated. With a recent emphasis on the very early treatment of stroke, in-hospital stroke patients may be candidates for some early interventions. This was a retrospective study using the stroke registries at two academic medical centers. Data were collected about the clinical characteristics of patients with an in-hospital stroke and who recognized the stroke. Detailed time data were analyzed to determine the time of stroke recognition, medical evaluation, and neurological evaluation. These specific time epochs were analyzed to determine which were responsible for any delays in stroke identification and assessment. Data were analyzed using nonparametric methods, including the Wilcoxon rank sum and Kruskal-Wallis procedure. Sixty-three patients were identified with in-hospital strokes and adequate time data. In-hospital stroke patients were recognized most frequently by nurses (63%) and by the patient (16%). Patients on a cardiology service and general surgery service accounted for 48% of all in-hospital strokes. The mean and median times from stroke recognition to a neurology evaluation were 14.5 and 2.5 hours, respectively. Total delays differed significantly with service and locale (P = .004). Patients on the Duke neurology service were evaluated significantly sooner (median delay, 0.5 hour) than patients on the Duke medical (median delay, 5.8 hours) or Duke surgical (median delay, 20.5 hours; P < .01 by Wilcoxon rank sum) services. Patients on the Yale surgical service were evaluated significantly sooner than patients on the Duke medical (P = .0006) or surgical (P = .0001) services. The time between physician notification and calling for a neurology evaluation accounted for > 60% of the total time delay for patients not on a neurology service. A substantial number of in-hospital stroke patients experience a long delay between symptom recognition and a neurological evaluation. While medical personnel are usually notified very soon after an in-hospital stroke is recognized, such patients often do not receive a rapid neurological evaluation. Additional education of hospital staff may reduce these time delays.

Interobserver variability in the assessment of neurologic history and examination in the Stroke Data Bank.

Interobserver reliability in obtaining neurologic histories and examinations was investigated among neurologists collaborating in the Stroke Data Bank (SDB). Seventeen in-hospital stroke patients were examined by six neurologists experienced in stroke over the course of three days. Patients were examined twice a day for two successive days, with each patient seen by four different neurologists. Data were recorded on SDB forms, according to definitions and procedures established for the SDB. Percent agreement and kappa coefficients were calculated to assess the levels of agreement for each item. Important differences in levels of agreement were found among items on both neurologic history and examination. Agreement among neurologists was higher for neurologic examination than for history. Patterns of agreement for items with low prevalence or with numerous unknown ratings are discussed. Improvement in interobserver agreement due to data editing for intra-observer consistency was shown.