Effectiveness of endovascular treatment for in-hospital stroke vs. community-onset stroke: a propensity score-matched analysis.

BACKGROUND: The effectiveness of endovascular treatment for in-hospital stroke remains debatable. We aimed to compare the outcomes between patients with in-hospital stroke and community-onset stroke who received endovascular treatment. METHODS: This prospective registry-based cohort study included consecutive patients who underwent endovascular treatment from January 2013 to December 2022 and were registered in the Selection Criteria in Endovascular Thrombectomy and Thrombolytic Therapy study and Yonsei Stroke Cohort. Functional outcomes at day 90, radiological outcomes, and safety outcomes were compared between the in-hospital and community-onset groups using logistic regression and propensity score-matched analysis. RESULTS: Of 1,219 patients who underwent endovascular treatment, 117 (9.6%) had in-hospital stroke. Patients with in-hospital onset were more likely to have a pre-stroke disability and active cancer than those with community-onset. The interval from the last known well to puncture was shorter in the in-hospital group than in the community-onset group (155 vs. 355 min, p<0.001). No significant differences in successful recanalization or safety outcomes were observed between the groups; however, the in-hospital group exhibited worse functional outcomes and higher mortality at day 90 than the community-onset group (all p<0.05). After propensity score matching including baseline characteristics, functional outcomes after endovascular treatment did not differ between the groups (OR: 1.19, 95% CI 0.78-1.83, p=0.4). Safety outcomes did not significantly differ between the groups. CONCLUSION: Endovascular treatment is a safe and effective treatment for eligible patients with in-hospital stroke. Our results will help physicians in making decisions when planning treatment and counseling caregivers or patients.

Validation of the prehospital stroke scales as a tool for in-hospital large vessel occlusion stroke: whether we satisfied?

BACKGROUND: Prehospital stroke severity scales have been widely used to identify whether community stroke patients presented with large vessel occlusion (LVO) or not. However, whether these scales are also applicable to in-hospital stroke patients remains unknown. PURPOSE: We aim to validate and compare the predictive capability of these scales for these patients. MATERIAL AND METHODS: From January 2016 to October 2020, a total of 243 patients who activated in-hospital stroke alerts, were included in this study. The area under the curve (AUC) was used to assess the predictive ability of five scales (Field Assessment Stroke Triage for Emergency Destination [FAST-ED], Rapid Arterial Occlusion Evaluation [RACE], Los Angeles Motor Scale [LAMS], Cincinnati Prehospital Stroke Severity Scale [CPSSS], and Prehospital Acute Stroke Severity scale [PASS]) for LVO. In addition, multivariable logistic analysis was adopted to determine the predictors of LVO in our patients cohort. RESULTS: Finally, 94 (38.7%) patients were confirmed presence of persistent LVO. The AUC for the FAST-ED, RACE, LAMS, CPSSS, and PASS scales to predict the presence of LVO in patients activating in-hospital stroke alerts were 0.82, 0.89, 0.86, 0.81, and 0.79, respectively. After multivariable analysis, baseline NIHSS (adjusted odds ratio [OR] = 1.160, 95% confidence interval [CI] = 1.110-1.212; P < 0.001) atrial fibrillation (adjusted OR = 2.940, 95% CI = 1.387-6.230; P = 0.005) and cardiac/pulmonary procedure (adjusted OR = 6.861, 95% CI = 2.437-19.315; P < 0.001) remained independent predictors of LVO. CONCLUSION: The prehospital stroke scales also showed good predictive capabilities in discriminating LVO among inpatients who activated stroke alerts. However, given that inpatients' history is more readily available, a specifically designed in-hospital stroke scale that combines stroke severity and history is warranted.

A single-site retrospective review of in-hospital stroke.

BACKGROUND: In-hospital stroke refers to a stroke arising in a patient during hospital admission for another condition. Between 2 and 17% of all inpatient strokes are in-hospital strokes. AIM: To compare the outcomes and performance on quality-of-care stroke measures of in-hospital stroke cases with community-onset strokes. METHODS: Data collected for the Irish Annual Audit of Stroke from an Irish university teaching hospital was analysed for a 2-year period from 1st January 2020 to 31st December 2021. A retrospective cohort study was conducted to compare baseline characteristics, outcomes, and performance on standardised quality-of-care measures between the cohorts. RESULTS: The rate of IHS was 15.6%. Median age was 73 years and 72 years for in-hospital and community-onset strokes respectively. Amongst in-hospital strokes, COVID-19 co-diagnosis (9.1% versus 1.3%; p = .0004), admission to intensive care (52.3% versus 5.3%; p < .0001), discharge to long term care (6.8% versus 2.3%; p = .04), mortality (12.5% versus 7.6%; p = .13), and modified Rankin score of two or more at discharge (58.0% versus 38.1%; p = .001), were more likely compared to community-onset strokes. Thrombolysis rates were lower (7.3% versus 12.0%; p = .22) and thrombectomy rates higher (9.8% versus 6.6;% p = .32), albeit non-significantly. Median time to thrombolysis was slower amongst in-hospital strokes (105 min versus 66 min; p = .03) and they were less likely to be admitted to the stroke unit (43.2% versus 78.5%; p < .0001). CONCLUSIONS: When compared with community-onset stroke, in-hospital stroke represents a distinct stroke subgroup with poorer outcomes and delays to thrombolysis emphasising the need for standardised approaches to evaluation and management.

Clinical validation of in-hospital stroke diagnosis.

OBJECTIVE: In-hospital stroke cases occur during hospitalization for another diagnosis and reflect a clinically distinct cohort from community-onset stroke. The objective was to validate the diagnostic accuracy of in-hospital stroke identification in stroke audit data at a large teaching hospital. METHODS: A retrospective clinical validation of in-hospital stroke diagnoses from two linked data sources was completed for a 2-year period from January 1st 2020 to December 31st 2021. The linked data sources include the Hospital Inpatient Enquiry system which assigns coded stroke diagnoses at discharge and/or the local stroke audit coordinators who work clinically in stroke teams and input additional specific clinical data. Diagnostic sensitivity, specificity and the level of agreement using an unweighted Cohen's Kappa were calculated. RESULTS: There were 597 strokes admitted during the 2-year period. The median age was 72 years and 55% occurred in males. In total, 88 cases of in-hospital stroke were clinically validated yielding an in-hospital stroke rate of 15%. The clinical audit coordinator identified in-hospital stroke with higher sensitivity (86%; 95% CI 77%-93%) whereas the coding process was more specific at 96% (95% CI 85% to 99%). Levels of agreement with the clinically validated gold standard sample were moderate for the audit coordinator and coding process with κ = 0.57 and K = 0.42 respectively. When both data sources were combined the level of agreement was substantial (κ = 0.65; p < .000). CONCLUSIONS: Clinical validation studies are required to reinforce data quality within stroke registers. Combining clinical and administrative data sources improves diagnostic accuracy for in-hospital stroke identification.

Prevalence and independent predictors of in-hospital stroke among patients who developed acute alteration of consciousness in the medical intensive care unit: A retrospective case-control study.

Background: In-hospital stroke is a serious event, associated with poor outcomes and high mortality. However, identifying signs of stroke may be more difficult in critically ill patients. Objectives: This study investigated the prevalence and independent predictors of in-hospital stroke among patients with acute alteration of consciousness in the medical intensive care unit (MICU) who underwent subsequent brain computed tomography (CT). Methods: This retrospective study enrolled eligible patients during the period 2007 - 2017. The alterations researched were radiologically confirmed acute ischaemic stroke (AIS) and intracerebral haemorrhage (ICH). Results: Of 4 360 patients, 113 underwent brain CT. Among these, 31% had AIS, while 15% had ICH. They had higher diastolic blood pressures and arterial pH than non-stroke patients. ICH patients had higher mean (standard deviation (SD) systolic blood pressures (152 (48) v. 129 (25) mmHg; p=0.01), lower mean (SD) Glasgow Coma Scale scores (4 (3) v. 7 (4); p=0.004), and more pupillary abnormalities (75% v. 9%; p<0.001) than AIS patients. AIS patients were older (65 (18) v. 57 (18) years; p=0.03), had more hypertension (60% v. 39%; p=0.04), and more commonly presented with the Babinski sign (26% v. 9%; p=0.04). Multivariate analysis found that pupillary abnormalities independently predicted ICH (adjusted odds ratio (aOR) 26.9; 95% CI 3.7 - 196.3; p=0.001). The Babinski sign (aOR 5.1; 95% CI 1.1 - 23.5; p=0.04) and alkalaemia (arterial pH >7.4; aOR 3.6; 95% CI 1.0 - 12.3; p=0.05) independently predicted AIS. Conclusion: Forty-six percent of the cohort had ICH or AIS. Both conditions had high mortality. The presence of pupillary abnormalities predicts ICH, whereas the Babinski sign and alkalaemia predict AIS. Contributions of the study: The present study reports that almost half (46%) of critically ill patients with alterations of consciousness had an acute stroke. Of these, two-thirds had an acute ischaemic stroke (AIS), and one-third had an intracranial haemorrhage (ICH). Multivariate analysis revealed that a pupillary abnormality was a predictor for ICH and the Babinski sign was identified as a predictor of AIS.

Characteristics of in-hospital stroke patients in Sweden: A nationwide register-based study.

INTRODUCTION: Few studies have reported the characteristics of patients with in-hospital stroke (IHS) including the reason for hospitalization and invasive procedures before the stroke. We aimed to extend current knowledge. PATIENTS AND METHODS: All adult patients with IHS in Sweden during 2010-2019 registered in the Swedish Stroke Register (Riksstroke) were included. The cohort was cross-linked to the National Patient Register and data extracted on background diagnoses, main discharge diagnoses, and procedure codes for the hospitalization when IHS occurred and any hospital-based healthcare contacts within 30 days before IHS. RESULTS: 231,402 stroke cases were identified of which 12,551 (5.4%) were in-hospital and had corresponding entries in the National Patient Register. Of the IHS patients, 11,420 (91.0%) had ischemic stroke and 1131 (9.0%) hemorrhagic stroke; 5860 (46.7%) of the IHS patients had at least one invasive procedure prior to ictus. 1696 (13.5%) had a cardiovascular procedure and 560 (4.5%) a neurosurgical procedure. 1319 (10.5%) patients only had minimally invasive procedures such as blood product transfusion, hemodialysis, or central line insertion. Common discharge diagnosis in patients with no invasive procedures were cardiovascular disorders, injuries, and respiratory disorders. DISCUSSION AND CONCLUSION: One in every 17 strokes in Sweden occur in a hospital. In this unselected large cohort the previously reported major causes for in-hospital stroke, cardiovascular and neurosurgical procedures, preceded IHS in only 18.0% of cases suggesting that other etiologies are more common than previously reported. Future studies should aim at determining absolute risks of stroke after surgical procedures and ways of risk reduction.

Utility of the RIPS Scale and 2CAN Score for In-Hospital Stroke Prediction.

Background: In-hospital strokes are a small but sizeable proportion of all strokes. Identification of in-hospital strokes is confounded by stroke mimics in as many as half of in-patient stroke codes. A quick scoring system based on risk factors and clinical signs during the initial evaluation of a suspected stroke might be helpful to distinguish true strokes from mimics. Two such scoring systems based on ischemic and hemorrhagic risk factors are the risk for in-patient stroke (RIPS) and the 2CAN score. Materials and Methods: This prospective clinical study was conducted at a quaternary care hospital in Bengaluru, India. All hospitalized patients aged 18 years and above for whom a "stroke code" alert was recorded during the study period of January 2019 to January 2020 were included in the study. Results: A total of 121 in-patient "stroke codes" were documented during the study. Ischemic stroke was the most common etiological diagnosis. A total of 53 patients were diagnosed to have ischemic stroke, 4 had intracerebral hemorrhage, and the rest were mimics. Receiver operative curve analysis was performed and at a cut-off of RIPS ≥3, it predicts stroke with a sensitivity of 77% and a specificity of 73%. At a cut-off of 2CAN ≥3, it predicts stroke with a sensitivity of 67% and a specificity of 80%. RIPS and 2CAN significantly predicted stroke. Conclusions: There was no difference in the use of either RIPS or 2CAN for differentiating stroke from mimics, and hence they may be used interchangeably. They were statistically significant with good sensitivity and specificity, as a screening tool to determine in-patient stroke.

Recognition of Strokes in the ICU: A Narrative Review.

Despite the remarkable progress in acute treatment for stroke, in-hospital stroke is still devastating. The mortality and neurological sequelae are worse in patients with in-hospital stroke than in those with community-onset stroke. The leading cause of this tragic situation is the delay in emergent treatment. To achieve better outcomes, early stroke recognition and immediate treatment are crucial. In general, in-hospital stroke is initially witnessed by non-neurologists, but it is sometimes challenging for non-neurologists to diagnose a patient's state as a stroke and respond quickly. Therefore, understanding the risk and characteristics of in-hospital stroke would be helpful for early recognition. First, we need to know "the epicenter of in-hospital stroke". Critically ill patients and patients who undergo surgery or procedures are admitted to the intensive care unit, and they are potentially at high risk for stroke. Moreover, since they are often sedated and intubated, evaluating their neurological status concisely is difficult. The limited evidence demonstrated that the intensive care unit is the most common place for in-hospital strokes. This paper presents a review of the literature and clarifies the causes and risks of stroke in the intensive care unit.

Mechanisms of in-hospital acute ischemic stroke and their relevance to prognosis: A retrospective analysis.

OBJECTIVES: In-hospital stroke (IHS) is common and has a poor prognosis. Limited data were about the mechanisms of IHS, posing a challenge in taking measures to prevent stroke during hospitalization. This study aims to investigate the mechanisms of IHS and their relevance to prognosis. MATERIALS AND METHODS: Patients with in-hospital acute ischemic stroke at Peking Union Medical College Hospital from June 2012 to April 2022 were consecutively enrolled. The Trial of Org 10172 in Acute Stroke Treatment (TOAST) classification of stroke and detailed mechanisms were evaluated by two experienced neurologists. Functional outcome at discharge was evaluated. RESULTS: A total of 204 IHS patients were included, with a median age of 64 (IQR 52-72) and 61.8% male. The most common mechanism was embolism (57.8%), followed by hypoperfusion (42.2%), hypercoagulation (36.3%), small vessel mechanism (19.1%), discontinuation of antithrombotic drugs (13.2%), and iatrogenic injury (9.8%). Iatrogenic injury (P = 0.001), hypoperfusion (P = 0.006), embolism (P = 0.03), and discontinuation of antithrombotic drugs (P = 0.004) were more common in perioperative stroke compared to non-perioperative stroke. Median NIHSS improvement (2 vs 1, P = 0.002) and median mRS improvement (1 vs 0.5, P = 0.02) at discharge were higher in perioperative patients. Advanced age and higher NIHSS at onset were significantly associated with a poorer prognosis, whereas embolism mechanism was associated with a better prognosis. CONCLUSIONS: The etiologies and mechanisms of IHS are complex. Perioperative and non-perioperative IHS have different mechanisms and prognostic features. Determining the causes and mechanisms of IHS will help to identify the population at risk and prevent stroke appropriately during hospitalization.

Derivation and Validation of an Algorithm to Detect Stroke Using Arm Accelerometry Data.

Background Early diagnosis is essential for effective stroke therapy. Strokes in hospitalized patients are associated with worse outcomes compared with strokes in the community. We derived and validated an algorithm to identify strokes by monitoring upper limb movements in hospitalized patients. Methods and Results A prospective case-control study in hospitalized patients evaluated bilateral arm accelerometry from patients with acute stroke with lateralized weakness and controls without stroke. We derived a stroke classifier algorithm from 123 controls and 77 acute stroke cases and then validated the performance in a separate cohort of 167 controls and 33 acute strokes, measuring false alarm rates in nonstroke controls and time to detection in stroke cases. Faster detection time was associated with more false alarms. With a median false alarm rate among nonstroke controls of 3.6 (interquartile range [IQR], 2.1-5.0) alarms per patient per day, the median time to detection was 15.0 (IQR, 8.0-73.5) minutes. A median false alarm rate of 1.1 (IQR. 0-2.2) per patient per day was associated with a median time to stroke detection of 29.0 (IQR, 11.0-58.0) minutes. There were no differences in algorithm performance for subgroups dichotomized by age, sex, race, handedness, nondominant hemisphere involvement, intensive care unit versus ward, or daytime versus nighttime. Conclusions Arm movement data can be used to detect asymmetry indicative of stroke in hospitalized patients with a low false alarm rate. Additional studies are needed to demonstrate clinical usefulness.

Delays in initial workflow cause delayed initiation of mechanical thrombectomy in patients with in-hospital ischemic stroke.

Objectives: The benefit of mechanical thrombectomy for acute ischemic stroke is highly time dependent. However, time to treatment is longer for in-hospital stroke patients than community-onset stroke patients. This study aimed to clarify the cause of this difference. Methods: A retrospective single-center study was performed to analyze patients with large vessel occlusion who underwent mechanical thrombectomy between January 2017 and December 2019. Patients were divided into in-hospital stroke and community-onset stroke groups. Clinical characteristics and treatment time intervals were compared between groups. Results: One hundred four patients were analyzed: 17 with in-hospital stroke and 87 with community-onset stroke. Patient characteristics did not significantly differ between groups. Median door (stroke recognition)-to-computed tomography time (36 min vs. 14 min, P<0.01) and door-to-puncture time (135 min vs. 117 min, P=0.02) were significantly longer in the in-hospital stroke group than the community-onset stroke group. However, median computed tomography-to-puncture time (104 min vs. 104 min, P=0.47) and puncture-to-reperfusion time (53 min vs. 38 min, P=0.17) did not significantly differ. Conclusions: Longer door-to-puncture time in in-hospital stroke patients was mostly caused by longer door-to-computed tomography time, which is the initial part of the workflow. An in-hospital stroke protocol that places importance on early stroke specialist consultation and prompt transportation to the computed tomography scanner might hasten treatment and improve outcomes in patients with in-hospital stroke.

Comparing characteristics and outcomes of in-hospital stroke and community-onset stroke.

BACKGROUND: In-hospital strokes account for 4-17% of all strokes and usually lead to urgent and severe conditions. However, features of in-hospital strokes have been scarcely reported in China, and the management systems of in-hospital strokes are unestablished. The study aims to analyze the characteristics of in-hospital strokes in comparison to community-onset strokes and provides evidence for the development of national in-patient stroke care systems. METHODS: We retrospectively analyzed consecutive patients with in-hospital strokes (IHS group) and community-onset strokes (COS group) hospitalized in our hospital between June 2012, and January 2022. Clinical characteristics, care measures, and outcomes were compared between the two groups. RESULTS: A total of 1162 patients (age 61 ± 16 and 65% male) were included, of whom 193 (16.6%) had an in-hospital stroke and 969 (83.4%) had community-onset stroke. Compared with COS group, patients in IHS group had higher NIHSS at onset (7.25 vs 5.96, P = 0.054), higher use of endovascular therapy (10.4% vs 2.0%, P < 0.001), and lower use of intravascular thrombolysis (1.6% vs 7.2%, P = 0.003). Also, in-hospital strokes were associated with lower rate of mRS0-2 at discharge (OR[95%CI] = 0.674[0.49, 0.926], P = 0.015) and increased in-hospital mobility (OR[95%CI] = 3.621[1.640, 7.996], P = 0.001), after adjusting for age, sex, and cardiovascular risk factors. CONCLUSION: Compared with community-onset strokes, the patients with in-hospital stroke had insufficient urgent treatment and poorer outcomes, reflecting the need for increased awareness of in-patient stroke, and strategies to streamline in-hospital acute stroke care.

Stroke in the stroke unit: Recognition, treatment and outcomes in a single-centre cohort.

BACKGROUND AND PURPOSE: In-hospital strokes (IHS) are associated with longer diagnosis times, treatment delays and poorer outcomes. Strokes occurring in the stroke unit have seldom been studied. Our aim was to assess the management of in-stroke-unit ischaemic stroke (ISUS) by analysing ISUS characteristics, delays in diagnosis, treatments and outcomes. METHODS: Consecutive patients from the Acute Stroke Registry and Analysis of Lausanne (ASTRAL), from January 2003 to June 2019, were classified as ISUS, other-IHS or community-onset stroke (COS). Baseline and stroke characteristics, time to imaging and time to treatment, missed treatment opportunities, treatment rates and outcomes were compared using multivariate analysis with adjustment for relevant clinical, imaging and laboratory data available in ASTRAL. RESULTS: Amongst the 3456 patients analysed, 138 (4.0%) were ISUS, 214 (6.2%) other-IHS and 3104 (89.8%) COS. In multivariate analysis, patients with ISUS more frequently had known stroke onset time than other-IHS (adjusted odds ratio [aOR] 2.44; 95% confidence interval [CI] 1.39-4.35) or COS (aOR 2.56; 95% CI 1.59-4.17), had fewer missed treatment opportunities than other-IHS (aOR 0.22; 95% CI 0.06-0.86) and higher endovascular treatment (EVT) rates than COS (aOR 3.03; 95% CI 1.54-5.88). ISUS was associated with a favourable shift in the modified Rankin Scale at 3 months in comparison with other-IHS (aOR 1.73; 95% CI 1.11-2.69) or COS (aOR 1.46; 95% CI 1.00-2.12). CONCLUSION: In-stroke-unit ischaemic stroke more frequently had known stroke onset time than other-IHS or COS, fewer missed treatment opportunities than other-IHS and a higher EVT rate than COS. This readiness to identify and treat patients in the stroke unit may explain the better long-term outcome of ISUS.

Ischaemic stroke as a complication of cardiac catheterisation. Clinical and radiological characteristics, progression, and therapeutic implications.

INTRODUCTION: Ischaemic stroke is the most common neurological complication of cardiac catheterisation. This study aims to analyse the clinical and prognostic differences between post-catheterisation stroke code (SC) and all other in-hospital and prehospital SC. METHODS: We prospectively recorded SC activation at our centre between March 2011 and April 2016. Patients were grouped according to whether SC was activated post-catheterisation, in-hospital but not post-catheterisation, or before arrival at hospital; groups were compared in terms of clinical and radiological characteristics, therapeutic approach, functional status, and three-month mortality. RESULTS: The sample included 2224 patients, of whom 31 presented stroke post-catheterisation. Baseline National Institutes of Health Stroke Scale score was lower for post-catheterisation SC than for other in-hospital SC and pre-hospital SC (5, 10, and 7, respectively; P=.02), and SC was activated sooner (50, 100, and 125minutes, respectively; P<.001). Furthermore, post-catheterisation SC were more frequently due to transient ischaemic attack (38%, 8%, and 9%, respectively; P<.001) and less frequently to proximal artery occlusion (17.9%, 31.4%, and 39.2%, respectively; P=.023). The majority of patients with post-catheterisation strokes (89.7%) did not receive reperfusion therapy; 60% of the patients with proximal artery occlusion received endovascular treatment. The mortality rate was 12.95% for post-catheterisation strokes and 25% for all other in-hospital strokes. Although patients with post-catheterisation stroke had a better functional prognosis, the adjusted analysis showed that this effect was determined by their lower initial severity. CONCLUSIONS: Post-catheterisation stroke is initially less severe, and presents more often as transient ischaemic attack and less frequently as proximal artery occlusion. Most post-catheterisation strokes are not treated with reperfusion; in case of artery occlusion, mechanical thrombectomy is the preferred treatment.

Delays in the Identification and Assessment of in-Hospital Stroke Patients.

OBJECTIVES: In-hospital stroke is associated with poor outcomes. Reasons for delays, use of interventions, and presence of large vessel occlusion are not well characterized. MATERIALS AND METHODS: A retrospective single center cohort of 97 patients with in-hospital stroke was analyzed to identify factors associated with delays from last known normal to symptom identification and to stroke team alerting. Stroke interventions and presence of large vessel occlusion were also assessed. RESULTS: Strokes were predominantly on surgery services (70%), ischemic (82%), and severe (median NIHSS 16; interquartile range [IQR] 6-24). There were long delays from last known normal to symptom identification (median 5.1 hours, IQR 1.0-19.7 hours), symptom identification to stroke team alerting (median 2.1 hours, IQR 0.5-9.9 hours), and total time from last known normal to alerting (median 11.4 [IQR 2.7-34.2] hours). In univariable analysis, being on a surgical service, in an ICU, intubated, and higher NIHSS were associated with delays. In multivariable analysis only intubation was independently associated with time from last known normal to symptom identification (coefficient 20 hours, IQR 0.2 - 39.8, p=0.047). Interventions were given to 17/80 (21%) ischemic stroke patients; 3 (4%) received IV tPA and 14 (18%) underwent thrombectomy. Vascular imaging occurred in 57/80 (71%) ischemic stroke patients and 21/57 (37%) had large vessel occlusion. CONCLUSIONS: Hospitalized patients with stroke experience long delays from symptom identification to stroke team alerting. Intubation was strongly associated with delay to symptom identification. Although stroke severity was high and large vessel occlusion common, many patients did not receive acute interventions.

A nomogram for predicting the in-hospital risk of recurrence among patients with minor non-cardiac stroke.

BACKGROUND: Patients with minor stroke suffer a substantial risk of further recurrences, especially in the first two weeks. We aimed to develop and validate a prognostic nomogram to predict in-hospital stroke recurrence among patients with acute minor stroke. METHODS: A total of 1326 patients with minor non-cardiac stroke (NIHSS) ≤5) from three centers were divided into development cohort (1016 patients from two centers) and validation cohort (310 patients from another center). Recurrent stroke was defined as a new ischemic stroke. A logistic regression model was employed to develop the nomogram to predict in-hospital stroke recurrence in patients with minor stroke using demographic, medical and imaging information. We then validated the nomogram externally. The predictive discrimination and calibration of the nomogram were assessed in the development and validation cohorts by area under the curve (AUC) and calibration plots. RESULTS: During a median length of stay of 12 days, stroke recurrence occurred in 34 patients (3.3%). Predictors of in-hospital recurrence included prior history of transient ischemic attack, baseline NIHSS score, multiple infarctions, and carotid stenosis. The clinical and imaging-based nomogram B demonstrated adequate calibration and discrimination (AUC = 0.777), which was validated among 273 patients in a separate validation cohort (AUC = 0.753). Our clinical-imaging based nomogram was determined to be superior to the clinical-based nomogram and the RRE90 score in terms of discrimination. CONCLUSION: A prognostic nomogram that integrates clinical and imaging information to predict the in-hospital risk of stroke recurrence among patients after acute minor stroke was constructed and validated externally. The nomogram demonstrated adequate calibration and discrimination in both the development and validation cohort.

Outcomes between in-hospital stroke and community-onset stroke after thrombectomy: Propensity-score matching analysis.

BACKGROUND: The benefit of endovascular thrombectomy for patients with in-hospital stroke remains unclear. Thus, the aim of this study was to compare the endovascular thrombectomy outcomes between in-hospital stroke and community-onset stroke among patients with acute ischemic stroke. METHODS: From January 2015 to July 2019, 362 consecutive patients with acute ischemic stroke with large vessel occlusion in the anterior circulation received endovascular thrombectomy in our centre. After propensity score matching with a ratio of 1:2 (in-hospital stroke:community-onset stroke), clinical characteristics and functional outcomes were compared between in-hospital stroke and community-onset stroke groups. RESULTS: Thirty-six patients with in-hospital stroke and 72 patients with community-onset stroke were enrolled. The number of patients with New York Heart Association classification III/IV (41.7% vs. 6.9%, p < 0.001) and with underlying cancer (25.0% vs. 2.8%, p < 0.001) was higher in the in-hospital stroke than in the community-onset stroke group. The intravenous thrombolysis rate was lower in the in-hospital stroke group (13.9% vs. 43.1%, p = 0.002). No significant difference in symptom onset to puncture (p = 0.618), symptom onset to recanalisation (p = 0.618) or good reperfusion (modified thrombolysis in cerebral infarction ≥2b) rates (p = 0.852) was found between the groups. The favourable clinical outcome trend (modified Rankin scale ≤2 at 90 days) was inferior, but acceptable, in the in-hospital stroke, group compared to the community-onset stroke group (30.6% vs. 41.7%, p = 0.262). CONCLUSION: Patients with in-hospital stroke had more disadvantageous comorbidities than those with community-onset stroke. Cardiac dysfunction seems to be associated with poor outcomes after thrombectomy. Nevertheless, endovascular thrombectomy still appears to be safe and effective for patients with in-hospital stroke.

In-Hospital Stroke Care: A Six-Year Community-Based Primary Stroke Center Experience.

BACKGROUND AND PURPOSE: In-hospital stroke-onset assessment and management present numerous challenges, especially in community hospitals. Comprehensive analysis of key stroke care metrics in community-based primary stroke centers is under-studied. METHODS: Medical records were reviewed for patients admitted to a community hospital for non-cerebrovascular indications and for whom a stroke alert was activated between 2013 and 2019. Demographic, clinical, radiologic and laboratory information were collected for each incident stroke. Descriptive statistical analysis was employed. When applicable, Kruskal-Wallis and Chi-Square tests were used to compare median values and categorical data between pre-specified groups. Statistical significance was set at alpha = 0.05. RESULTS: There were 192 patients with in-hospital stroke-alert activation; mean age (SD) was 71.0 years (15.0), 49.5% female. 51.6% (99/192) had in-hospital ischemic and hemorrhagic stroke. The most frequent mechanism of stroke was cardioembolism. Upon stroke activation, 45.8% had ischemic stroke while 40.1% had stroke mimics. Stroke team response time from activation was 26 minutes for all in-hospital activations. Intravenous thrombolysis was utilized in 8% of those with ischemic stroke; 3.4% were transferred for consideration of endovascular thrombectomy. In-hospital mortality was 17.7%, and the proportion of patients discharged to home was 34.4% for all activations. CONCLUSION: The in-hospital stroke mortality was high, and the proportions of patients who either received or were considered for acute intervention were low. Quality improvement targeting increased use of acute stroke intervention in eligible patients and reducing hospital mortality in this patient cohort is needed.

Incidence of Acute Ischemic Stroke in Hospitalized Patients With Atrial Fibrillation Who Had Anticoagulation Interruption: A Retrospective Study.

BACKGROUND: Atrial fibrillation (AF) is one of the leading causes of acute ischemic stroke requiring anticoagulation. Many patients experience treatment interruption in the hospital setting. The aim of this study was to evaluate the effect of anticoagulation interruption on short-term risk of ischemic stroke in hospitalized patients with AF. METHODS: We performed a retrospective medical record review using the Hospital Corporation of America (HCA) database. We included patients admitted to our institution between December 2015 and December 2018 who had a prior history of AF. Patients were excluded if they had ischemic stroke, hemorrhagic stroke, history venous thromboembolism or mechanical valve on admission. We compared the incidence of ischemic stroke in patients in whom anticoagulation was interrupted for more than 48 h to those who continued anticoagulation. RESULTS: A total of 2,277 patients with history of AF were included in the study. In this cohort, 79 patients (3.47%) had anticoagulation interruption of more than 48 h during their hospital stay. There was no difference in incidence of stroke between the interruption and no interruption groups (1.27% (n = 1) vs. 0.23% (n = 5), P = 0.19). Interruption of anticoagulation did not associate with a significant increase in the risk of in-hospital ischemic stroke. CHA2DS2VASc score was a strong predictor of in-hospital stroke risk regardless of anticoagulation interruption (odds ratio: 7.199, 95% confidence interval: 2.920 - 17.751). CONCLUSION: In this study, the in-hospital incidence of ischemic stroke in patients with AF did not significantly increase by short-term anticoagulation interruption.

A Case of Endovascular Treatment for In-Hospital Stroke with COVID-19 under Protected Code Stroke.

Objective: Coronavirus disease 2019 (COVID-19) is characterized by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) and presents with respiratory symptoms. Overall, 5.7% of COVID-19 patients with severe respiratory status have been reported to develop acute cerebrovascular diseases (CVDs), and 41.3% of COVID-19 cases were considered nosocomial infections. Therefore, Protected Code Stroke, which is a guideline for acute stroke management that takes into account the safety of healthcare workers, has been developed. We created an operational manual for COVID-19 in the endovascular treatment center of our hospital and report our experience treating acute stroke in a COVID-19 patient. Case Presentation: A 67-year-old man presented with a 5-day history of fever. Chest CT showed ground glass opacity (GGO) on admission, and the polymerase chain reaction (PCR) test for COVID-19 was positive. Dysarthria, right-sided hemiparesis, and aphasia were discovered on the morning of the third day after hospitalization. MRI showed an acute ischemic stroke at the left corona radiata and occlusion of the left middle cerebral artery (MCA). Progression of right-sided hemiparesis and exacerbation of respiratory status developed after the MRI. Tracheal intubation was performed, and the patient was treated with intravenous alteplase and mechanical thrombectomy (MT). Recanalization of blood flow was not obtained, and the neurological deficits remained. Conclusion: MT was performed for large-vessel occlusion (LVO) in a COVID-19 patient during the COVID-19 pandemic. Safety for healthcare workers and appropriate rapid treatment for acute stroke patients are both vital in the current environment.