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Background: Resource allocation can be problematic in ischemic stroke receiving IV thrombolysis (tPA) during COVID-19 pandemic as only a subset requires critical care interventions. It is also unknown whether the usage of non-ICU stroke unit for post-tPA care has better patient outcome compared to ICU. Methods: A pilot study in a single tertiary medical center, in which one-bed tPA unit was created in a non-ICU Stroke Unit during the COVID-19 pandemic, with the provision of ICU level of nursing care. We included 123 consecutive ischemic stroke patients treated with tPA, included in an institutional registry between October 2020 and December 2021. The primary outcome of interest was inpatient length of stay (LOS). The secondary outcome of interest was the 90-day clinical outcomes. Results: Amongst a total of 123 patients, control group consisted of 98 (79.7%) patients who received standard post-tPA care in an ICU, and the study group consisted of 25 (20.3%) patients who received standard post-tPA care in Stroke Unit. There were no statistically significant differences between the 2 groups in terms of median LOS or median 90-day NIHSS. However, the median 90-day mRS was lower in the study group compared to the ICU group (0 IQR (0-1) vs. 2 (1-5); P=0.0011). The 90-day death outcome was also lower in the study group compared to the control (0% vs. 25.5%, P

ObjectivesTo examine the associations between catheter ablation treatment (CA) vs. medical management and cognitive impairment among older adults with atrial fibrillation (AF).MethodsAmbulatory patients who had AF, were ≥65-years-old, and were eligible to receive oral anticoagulation could be enrolled into the SAGE (Systematic Assessment of Geriatric Elements)-AF study from internal medicine and cardiology clinics in Massachusetts and Georgia between 2016 and 2018. Cognitive function was assessed using the Montreal Cognitive Assessment (MoCA) tool at baseline, 1-, and 2 years. Cognitive impairment was defined as a MoCA score ≤ 23. Multivariate-adjusted logistic regression of longitudinal repeated measures was used to examine associations between treatment with CA vs. medical management and cognitive impairment.Results887 participants were included in this analysis. On average, participants were 75.2 ± 6.7 years old, 48.6% women, and 87.4% white non-Hispanic. 193 (21.8%) participants received a CA before enrollment. Participants who had previously undergone CA were significantly less likely to be cognitively impaired during the 2-year study period (aOR 0.70, 95% CI 0.50–0.97) than those medically managed (i.e., rate and/or rhythm control), even after adjusting with propensity score for CA. At the 2-year follow-up a significantly greater number of individuals in the non-CA group were cognitively impaired (MoCA ≤ 23) compared to the CA-group (311 [44.8%] vs. 58 [30.1%], p = 0.0002).ConclusionIn this 2-year longitudinal prospective cohort study participants who underwent CA for AF before enrollment were less likely to have cognitive impairment than those who had not undergone CA.

BackgroundUnplanned 30-day hospital readmissions following a stroke is a serious quality and safety issue in the United States. The transition period between the hospital discharge and ambulatory follow-up is viewed as a vulnerable period in which medication errors and loss of follow-up plans can potentially occur. We sought to determine whether unplanned 30-day readmission in stroke patients treated with thrombolysis can be reduced with the utilization of a stroke nurse navigator team during the transition period.MethodsWe included 447 consecutive stroke patients treated with thrombolysis from an institutional stroke registry between January 2018 and December 2021. The control group consisted of 287 patients before the stroke nurse navigator team implementation between January 2018 and August 2020. The intervention group consisted of 160 patients after the implementation between September 2020 and December 2021. The stroke nurse navigator interventions included medication reviews, hospitalization course review, stroke education, and review of outpatient follow-ups within 3 days following the hospital discharge.ResultsOverall, baseline patient characteristics (age, gender, index admission NIHSS, and pre-admission mRS), stroke risk factors, medication usage, and length of hospital stay were similar in control vs. intervention groups (P > 0.05). Differences included higher mechanical thrombectomy utilization (35.6 vs. 24.7%, P = 0.016), lower pre-admission oral anticoagulant use (1.3 vs. 5.6%, P = 0.025), and less frequent history of stroke/TIA (14.4 vs. 27.5%, P = 0.001) in the implementation group. Based on an unadjusted Kaplan–Meier analysis, 30-day unplanned readmission rates were lower during the implementation period (log-rank P = 0.029). After adjustment for pertinent confounders including age, gender, pre-admission mRS, oral anticoagulant use, and COVID-19 diagnosis, the nurse navigator implementation remained independently associated with lower hazards of unplanned 30-day readmission (adjusted HR 0.48, 95% CI 0.23–0.99, P = 0.046).ConclusionThe utilization of a stroke nurse navigator team reduced unplanned 30-day readmissions in stroke patients treated with thrombolysis. Further studies are warranted to determine the extent of the results of stroke patients not treated with thrombolysis and to better understand the relationship between resource utilization during the transition period from discharge and quality outcomes in stroke.

BackgroundThe LACE+ index is used to predict unplanned 30-day hospital readmissions, but its utility to predict 30-day readmission in hospitalized patients with stroke is unknown.MethodsWe retrospectively analyzed 1,657 consecutive patients presenting with ischemic or hemorrhagic strokes, included in an institutional stroke registry between January 2018 and August 2020. The primary outcome of interest was unplanned 30-day readmission for any reason after index hospitalization for stroke. The 30-day readmission risk was categorized by LACE+ index to high risk (≥78), medium-to-high risk (59–77), medium risk (29–58), and low risk (≤ 28). Kaplan-Meier analysis, Log rank test, and multivariable Cox regression analysis (with backward elimination) were used to determine whether the LACE+ score was an independent predictor for 30-day unplanned readmission.ResultsThe overall 30-day unplanned readmission rate was 11.7% (194/1,657). The median LACE+ score was higher in the 30-day readmission group compared to subjects that had no unplanned 30-day readmission [74 (IQR 67–79) vs. 70 (IQR 62–75); p < 0.001]. On Kaplan-Meier analysis, the high-risk group had the shortest 30-day readmission free survival time as compared to medium and medium-to-high risk groups (p < 0.01, each; statistically significant). On fully adjusted multivariable Cox-regression, the highest LACE+ risk category was independently associated with the unplanned 30-day readmission risk (per point: HR 1.67 95%CI 1.23–2.26, p = 0.001).ConclusionSubjects in the high LACE+ index category had a significantly greater unplanned 30-day readmission risk after stroke as compared to lower LACE+ risk groups. This supports the validity of the LACE+ scoring system for predicting unplanned readmission in subjects with stroke. Future studies are warranted to determine whether LACE+ score-based risk stratification can be used to devise early interventions to mitigate the risk for unplanned readmission.

Background: Atrial fibrillation (AF) is a common heart rhythm disorder that elevates stroke risk. Stroke survivors undergo routine heart rhythm monitoring for AF. Smartwatches are capable of AF detection and potentially can replace traditional cardiac monitoring in stroke patients. Objective: The goal of Pulsewatch is to assess the accuracy, usability, and adherence of a smartwatch-based AF detection system in stroke patients. Methods: The study will consist of two parts. Part I will have 6 focus groups with stroke patients, caretakers, and physicians, and a Hack-a-thon, to inform development of the Pulsewatch system. Part II is a randomized clinical trial with 2 phases designed to assess the accuracy and usability in the first phase (14 days) and adherence in the second phase (30 days). Participants will be randomized in a 3:1 ratio (intervention to control) for the first phase, and both arms will receive gold-standard electrocardiographic (ECG) monitoring. The intervention group additionally will receive a smartphone/smartwatch dyad with the Pulsewatch applications. Upon completion of 14 days, participants will be re-randomized in a 1:1 ratio. The intervention group will receive the Pulsewatch system and a handheld ECG device, while the control group will be passively monitored. Participants will complete questionnaires at enrollment and at 14- and 44-day follow-up visits to assess various psychosocial measures and health behaviors. Results: Part I was completed in August 2019. Enrollment for Part II began September 2019, with expected completion by the end of 2021. Conclusion: Pulsewatch aims to demonstrate that a smartwatch can be accurate for real-time AF detection, and that older stroke patients will find the system usable and will adhere to monitoring.

Background. Several studies investigated the use of selective serotonin reuptake inhibitors (SSRI) after ischemic stroke to improve motor recovery. However, little is known about the effects of preexisting psychotropic medication use (PPMU), such as antidepressants, on a long-term ischemic stroke functional disability. Objective. We sought to determine the prevalence of PPMU and whether PPMU relates to the long-term clinical outcome in a cohort of patients presenting with acute ischemic strokes. Methods. We retrospectively analyzed 323 consecutive patients who presented with an acute ischemic stroke in a single institution between January 2015 and December 2017. Baseline characteristics, functional disability as measured by the modified Rankin Scale (mRS), and major adverse cardiovascular complications (MACE) within 365 days were recorded. The comparison groups included a control group of ischemic stroke patients who were not on psychotropic medications before and after the index ischemic stroke and a second group of poststroke psychotropic medication use (PoMU), which consisted of patients started on psychotropic medication during the index admission. Results. The prevalence of PPMU in the studied cohort was 21.4% (69/323). There was a greater proportion of females in the PPMU than in the comparison groups (P

Background: Depression often interferes with self-management and treatment of medical conditions. This may result in serious medical complications and escalated health-care cost. Objectives: Study distribution of heart failure (HF) cases estimates the prevalence of depression and its effects on HF-related hospital costs by ethnicity and gender. Methods: Secondary data files of California Hospital Discharge System for he year 2010 were examined. For patients with a HF diagnosis, details regarding depression, demographics, comorbid conditions, and hospital costs were studied. Age-adjusted HF rates and depression were examined for whites, blacks, Hispanics, and Asians/Pacific Islanders (AP) by comparing HF patients with depression (HF +D) versus HF without depression (HFND). Results: HF cases (n = 62,685; average age: 73) included nearly an equal number of males and females. HF rates were higher (P < 0.001) among blacks compared to Hispanics, AP, and whites and higher among males than females. One-fifth of HF patients had depression, higher among females and whites compared to males and other ethnic groups. Further, HF hospital costs for blacks and AP were higher (P < 0.001) compared to other groups. The cost for HF +D was 22% higher compared to HFND, across all gender and ethnic groups, largely due to higher comorbidities, more admissions, and longer hospitalization. Conclusion: Depression, ethnicity, and gender are all associated with increased hospital costs of HF patients. The higher HF and HF +D costs among blacks, AP, and males reflect additional burden of comorbidities (hypertension and diabetes). Prospective studies to assess if selective screening and treating depression among HF patients can reduce hospital costs are warranted.

Objective: To investigate the effect of smoking and depression on hospital costs for lung cancer (LC). Methods: We extracted data on depression, smoking history, demographics, and hospital charges for patients with respiratory cancers (ICD-9 codes 161–163, 165) from the 2008 Tennessee Hospital Discharge Data System. The sample (n=6665) was mostly white (86%) and male (57%). Age-adjusted rates were developed in accordance with Centers for Disease Control and Prevention methods, and hospital costs were compared for patients with LC with versus without depression and a smoking history. Results: Three findings (P

Multifractal denoising techniques capture interest in biomedicine, economy, and signal and image processing. Regarding stroke data there are subtle details not easily detectable by eye physicians. For the stroke subtypes diagnosis, details are important due to including hidden information concerning the possible existence of medical history, laboratory results, and treatment details. Recently, K-means and fuzzy C means (FCM) algorithms have been applied in literature with many datasets. We present efficient clustering algorithms to eliminate irregularities for a given set of stroke dataset using 2D multifractal denoising techniques (Bayesian (mBd), Nonlinear (mNold), and Pumping (mPumpD)). Contrary to previous methods, our method embraces the following assets: (a) not applying the reduction of the stroke datasets’ attributes, leading to an efficient clustering comparison of stroke subtypes with the resulting attributes; (b) detecting attributes that eliminate “insignificant” irregularities while keeping “meaningful” singularities; (c) yielding successful clustering accuracy performance for enhancing stroke data qualities. Therefore, our study is a comprehensive comparative study with stroke datasets obtained from 2D multifractal denoised techniques applied for K-means and FCM clustering algorithms. Having been done for the first time in literature, 2D mBd technique, as revealed by results, is the most successful feature descriptor in each stroke subtype dataset regarding the mentioned algorithms’ accuracy rates.

Aims: To examine the variation in risk factors and hospitalization costs among four elderly dementia cohorts by race and gender. Materials and Methods: The 2008 Tennessee Hospital Discharged database was examined. The prevalence, risk factors and cost of inpatient care of dementia were examined for individuals aged 65 years and above, across the four race gender cohorts - white males (WM), black males (BM), white females (WF), and black females (BF). Results: 3.6% of patients hospitalized in 2008 had dementia. Dementia was higher among females than males, and higher among blacks than whites. Further, BF had higher prevalence of dementia than WF; similarly, BM had a higher prevalence of dementia than WM. Overall, six risk factors were associated with dementia for the entire sample including HTN, DM, CKD, CHF, COPD, and stroke. These risk factors varied slightly in predicting dementia by race and gender. Hospital costs were 14% higher among dementia patients compared to non-dementia patients. Conclusions: There exist significant race and gender disparities in prevalence of dementia. A greater degree of co-morbidity, increased duration of hospital stay, and more frequent hospitalizations, may result in a higher cost of inpatient dementia care. Aggressive management of risk factors may subsequently reduce stroke and cost of dementia care, especially in the black population. Race and gender dependent milestones for management of these risk factors should be considered.

Background: Factors influencing outcome after cerebral artery occlusion are not completely understood. Although it is well accepted that the site of arterial occlusion critically influences outcome, the majority of studies investigating this issue has focused on proximal large artery occlusion. To gain a better understanding of factors influencing outcome after distal large artery occlusion, we sought to assess predictors of outcome following isolated M2 middle cerebral artery occlusion infarcts. Methods: We retrospectively analyzed patients with isolated acute M2 occlusion admitted to a single academic center from January 2010 to August 2012. Baseline clinical, laboratory imaging, and outcome data were assessed from a prospectively collected database. Factors associated with a modified Rankin Scale (mRS) score ≤2 in univariable analyses (p Results: 90 patients with isolated M2 occlusion were included in the final analyses. Of these, 69% had a good 90-day outcome which was associated with age 28 ml (OR 11.874, 95% CI 2.630-53.604, p = 0.001), age >80 years (OR 4.953, 95% CI 1.087-22.563, p = 0.039), need for intubation (OR 7.788, 95% CI 1.072-56.604), and history of congestive heart failure (OR 5.819, 95% CI 1.140-29.695) were independent predictors of 90-day mortality (20% of all included patients). Conclusion: While the majority of patients with isolated M2 occlusion stroke has a good 90-day outcome, a substantial proportion of subjects dies by 90 days, as identified by a unique subset of predictors. The knowledge gained from our study may lead to an improvement in the prognostic accuracy, clinical management, and resource utilization in this patient population.

Introduction: Although there is sufficient evidence that HMG CoA Reductase Inhibitors reduce stroke recurrence in patients with or ischemic heart disease, it remains unclear whether they also improve outcomes given before or after stroke onset and whether such an effect is more robust with pre-stroke or post-stroke use of statins. Materials and Methods: We carried out a retrospective analysis of a large University Health Consortium Database. Patients with statin use before or after stroke onset were included in the analysis. Twenty patients discontinued statins after stroke onset. The outcome measures were discharge home or long-term care facility and/or death within 45 days. Results: Patients with prior statin use were more likely to be discharged home (1.67, CI 1.12-2.49), as were post stroke statin patients who had a more robust effect OR 2.63, CI 1.61-4.53). Conclusions: Patients started on statins after stroke were more likely to be discharged home versus patients already on statins before stroke onset. However, both groups were also more likely to be discharged home than those patients not on statins.

Neha S Dangayach1, Kevin Kane2, Majaz Moonis31Saint Vincent Hospital, 2University of Massachusetts Medical School, 3University of Massachusetts Memorial Health Center, Worcester, MA, USAIntroduction: Paroxysmal atrial fibrillation (PAF) is perhaps the most underdiagnosed mechanism of apparent cryptogenic stroke (CS). Various studies have shown that increasing the duration of monitoring can increase the diagnosis of PAF in CS.Methods: We compared demographic and risk factors for ischemic stroke across different TOAST (Trial of ORG 10172 in Acute Stroke Treatment) stroke subtypes to look for clinical differences between other subtypes and CS and subsequently performed periodic Holter monitoring and imaging studies in apparent CS patients.Results: Of the 298 patients with ischemic stroke, 17% had CS. Periodic holter monitoring enabled diagnosis of PAF in 29% of patients. Five of 51 patients with CS had recurrent ischemic stroke and all 5 were demonstrated as PAF on repeated Holter monitoring.Conclusions: Long-term periodic rhythm monitoring in patients with apparent CS showed PAF in a significant percentage of CS patients, which altered subsequent treatment.Keywords: cryptogenic stroke, atrial fibrillation, stroke of undetermined etiology

Eugene Lin, Rajiv Padmanabhan, Majaz MoonisDepartment of Neurology, University of Massachusetts Medical School and UMass Memorial Medical Center, Worcester, Massachusetts, USAIntroduction: Antiplatelet therapy remains one of the cornerstones in the management of noncardioembolic ischemic stroke. However, a significant percentage of patients have concomitant gastroesophageal reflux or peptic ulcer disease that requires acid-reducing medications, the most powerful and effective being the proton pump inhibitors (PPIs). Antiplatelet efficacy, at least in vivo, and particularly for clopidogrel, has been shown to be reduced with concomitant proton pump inhibitor use. Whether this is clinically relevant is not clear from the limited studies available.Methods: We conducted an extensive review of studies available on Medline related to pharmacodynamic interactions between the antiplatelet medications and proton pump inhibitors as well as clinical studies that addressed this potential interaction.Results: Based on the present pharmacodynamic and clinical studies we did not find a significant interaction that would reduce the efficacy of antiplatelet agents with concomitant user of proton pump inhibitors.Conclusions: Patients on antiplatelet agents after a transient ischemic attack or ischemic stroke can safely use aspirin, and extended release dipyridamole/aspirin with proton pump inhibitors. Patients on clopidogrel may use other acid-reducing drugs besides proton pump inhibitors. In rare cases where proton pump inhibitors and clopidogrel have to be used concurrently, careful close monitoring for recurrent vascular events is required.Keywords: proton pump inhibitors, antiplatelet medications, clopidogrel, ischemic stroke, cardiovascular events

Amongst various mechanisms of presyncopal events, posterior circulation disease needs to be considered. This particular mechanism has been underrecognized. We describe a case of a 76-year-old patient with recurrent posterior circulation TIAs, presenting as recurrent prolonged presyncopal events.

Objective. This analysis focuses on the effect of depression on the cost of hospitalization of stroke patients. Methods. Data on 17,010 stroke patients (primary diagnosis) were extracted from 2008 Tennessee Hospital Discharge Data System. Three groups of patients were compared: (1) stroke only (SO, n=7,850), (2) stroke + depression (S+D, n=3,965), and (3) stroke + other mental health diagnoses (S+M, n=5,195). Results. Of all adult patients, 4.3% were diagnosed with stroke. Stroke was more prevalent among blacks than whites (4.5% versus 4.2%, P

Background. Undiagnosed intracranial hypotension can result in several complications including subdural hematoma (SDH), subarachnoid hemorrhage (SAH), dural venous sinuses thrombosis (CVT), cranial nerve palsies, and stupor resulting from sagging of the brain. It is rare to see all the complications in one patient. Furthermore, imaging of the brain vasculature may reveal incidental asymptomatic small aneurysms. Given the combination of these imaging findings and a severe headache, the patients are often confused to have a primary subarachnoid hemorrhage. Case Report. We present a patient with spontaneous intracranial hypotension (SIH) who had an incidental ophthalmic artery aneurysm on MR imaging, and this presentation led to coiling of the aneurysm. The key aspect in the history “postural headaches” was missed, and this led to life threatening complications and unnecessary interventions. Revisiting the history and significant improvement in symptoms following an epidural blood patch resulted in the diagnosis of SIH. Conclusion. We strongly emphasize that appropriate history taking is the key in the diagnosis of SIH and providing timely treatment with an epidural blood patch could prevent potentially life threatening complications.

In performing statistical analysis in clinical trials, the conventional method is to conduct univariate analysis for variable selection, followed by multivariate logistic regression to find more details about the variables. While this approach is widely used, and does deliveruseful explanations of the data, it has several shortcomings. In this paper, we compare the results obtained with conventional methods with those of alternative machine learning algorithms in terms of their ability to predict stroke outcome of patients. We also examine the different models constructed by the algorithms, and compare them with the logistic regression model. We find that machine learning can be used to predict more precise outcomes and reveal more variables than previously known that may play an important role in determining stroke outcomes. [ABSTRACT FROM AUTHOR]