ABSTRACT
Introduction Cerebral venous thrombosis (CVT) may occur due to a number of common etiologies such as thromboembolism, atherosclerotic disease, or small vessel disease. When these are ruled out or considered unlikely, a hypercoagulability workup is performed. We describe a series of 30 patients with CVT and medical and/or genetic basis for the underlying hypercoagulable state and thrombophilia. Methods A retrospective review of all CVT cases treated with venous thrombectomy between June 2016 and August 2021 was performed within our institutional, neuroendovascular database. Results Of the 30 patients identified, 18 were associated with a hypercoagulable state and/or thrombophilia. Underlying illness was present in seven (36.8%) patients due to polycythemia vera, systemic lupus erythematosus, a combination of nephrotic syndrome and morbid obesity, a combination of rheumatoid arthritis and diabetes, chronic rejection of a small bowel transplant further complicated by acute renal failure and ARDS, a combination of diabetes, DVT, and a dyslipidemic state, and Covid-19. Hypercoagulable states were identified in seven (36.8%) patients due to elevated Factor VIII (1/ 7), antiphospholipid syndrome (3/7), and Protein S deficiency (3/7). Genetic thrombophilia was identified in four (16.4%) patients in the form of a heterozygous Factor V mutation in R506Q (2/4), a heterozygous Prothrombin Factor II mutation in G20210A (1/4), and a homozygous 4G/4G promoter Plasminogen Activator inhibitor I deletion mutation (1/4). Overall, no subset of hypercoagulability (I.e. mutation, disease, transient state) nor hypercoagulability overall was predictive of outcome as measured by recanalization, discharge disposition, or reocclusion likelihood. Conclusion The most common cause of hypercoagulability was underlying disease or transient antiphospholipid syndrome/elevated pro-coagulation factor. While we are unable to report hypercoagulability as a predictive variable of outcome in our cohort, we outline the presence of various coagulopathies within this medically refractory, CVT cohort. While CVT may occur due to many common pathologies, in cases where the cause is unknown a hypercoagulability workup my shed light on mitigating factors underlying the thrombosis.
ABSTRACT
Objective: We report the burden of long haul COVID-19 associated dysautonomia and emphasize impact on activities of daily living and mental health, with the goal of developing interventions. Background: Dysautonomia is an established neurological effect of COVID-19 and has been reported in long-haul COVID-19 patients. It is imperative to understand the impact of this condition from the patient perspective to appreciate individual illness experience, clinical course, and disease burden to develop neurological, psychiatric, and social interventions. Design/Methods: 18 long-haul patients in a COVID-19 Remote Patient Monitoring Program (Precision Recovery: Mount Sinai Health System) were interviewed regarding their experience with COVID-19. Patients were asked about their experiences navigating diagnoses, the health care system, and their recovery process, with emphasis on long-haul symptom course and impact. References to dysautonomia within their long haul COVID-19 experience (symptoms persisting greater than four weeks post initial infection) were analyzed for statistical and qualitative significance. Results: The following symptoms of long-haul COVID-19 dysautonomia were reported: fluctuating fevers 12/18 (67%);heart palpitations/tachycardia: 12/18 (67%);digestion problems 8/18 (44%);dizziness 6/18 (33%);and fluctuations in blood pressure 4/18 (22%). 7/18 (39%) of patients reported 3 or more dysautonmic symptoms. Patients reported three categories of impact on daily activities: (1) routine physical exertion intolerance;(2) impaired ability to care for self (nutrition, hygiene);and (3) impacted social interaction due to physical impedance and/or isolation in experience. The main mental health effects associated with long-haul dysautonomia included: (1) depression and suicide ideation, (2) intense anxiety, and (3) self doubt. Conclusions: Dysautonomia in long haul COVID-19 patients has a devastating impact on daily living and mental health. It is imperative to recognize these effects and understand them from the patient perspective in order to develop compassionate, validating, and efficacious neurological, psychological, and social interventions for this population.
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Objective: Here, we emphasize the debilitating effects on daily life of post covid cognitive impairment, from the patient perspective. In this, we will gain deeper insight into the post-acute illness phase of COVID-19 to formulate more compassionate, supportive, and efficacious treatment protocols. Background: Post Covid-19 acute infection neurological impairment has been shown to be a long term effect of the disease. 18 months after the onset of the COVID-19 pandemic, with over 230 million cases worldwide, it has never been more critical to understand such long term effects. Design/Methods: 46 Patients in a COVID-19 Remote Patient Monitoring Program (Precision Recovery: Mount Sinai Health System) were interviewed regarding their experience with COVID-19. Patients were asked about their experiences navigating COVID-19 diagnoses, the health care system, and their recovery process. Patients were not pointedly asked about cognitive impairment post covid and all mentions were unprompted. References to post-cognitive impairment were analyzed for statistical and qualitative significance. Results: 20/46 (43%) of patients reported cognitive impairment after the acute phase of their covid illness. 8/20 of these individuals (40%) were self identified long-haul covid patients. Patients identified three patterns of impairment: (1) memory;(2) attention;and (3) mental stamina. These new cognitive deficits impacted daily life in four key ways: (1) failure to adhere to daily responsibilities;(2) necessitated decrease in employment responsibilities;(3) insecurity in social interactions;and (4) development of coping strategies. Conclusions: Post covid cognitive impairment significantly impacted both acute and long-haul covid patients. It is therefore critical to acknowledge this potential long-term effect as an outcome for anyone who experiences Covid-19 for improved understanding of patient illness experience and development of covid-19 treatment post-acute infection.
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Objective: Here, we report the impact of COVID-19 associated extreme fatigue on activities of daily living from the patient perspective in both mild and long haul COVID-19 patients. This narrative emphasis will offer opportunities for the development of neurological protocols and interventions for the treatment and support of affected individuals. Background: Extreme fatigue has been shown to be a neurological effect of COVID-19 infection. It is critical to better understand the impact this symptom has on daily functioning across the spectrum of morbidity associated with COVID-19 infection. Patient perspective on extreme fatigue affords deeper insight into illness experience, clinical course of COVID-19 associated fatigue, and opportunities for neurological and social intervention. Design/Methods: 46 Patients in a COVID-19 Remote Patient Monitoring Program (Precision Recovery: Mount Sinai Health System) were interviewed regarding their experience with COVID-19. Patients were asked about their experiences navigating COVID-19 diagnoses, the health care system, and their recovery process. References to fatigue were analyzed for statistical and qualitative significance. Results: 34/46 patients (74%) reported extreme fatigue as a symptom of their COVID-19 infection. 16/34 patients (47%) were self-reported long haul COVID-19 patients, which represented 16/18 (89%) of the long haul patients in the study. Patients reported three categories of impact on activities of daily living: (1) care for self;(2) care for others;and (3) employment responsibilities and continuation. The critical secondary effects of this fatigue included: (1) barrier to healthcare;(2) social isolation;(3) malnutrition;(4) necessity of outside caretakers for children;and (5) employment termination. Conclusions: COVID-19 extreme fatigue had debilitating effects on activities of daily living for both mild and long-haul patients. This is critical to acknowledge, not only for development of protocol and interventional treatment, but also for the development of social support for impacted individuals, including food access, child care, and employment response.
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Background and Purpose: Randomized controlled trials have demonstrated the importance of time to endovascular therapy (EVT) on clinical outcomes in large vessel occlusion (LVO) acute ischemic stroke. Delays to treatment are particularly prevalent when patients require a transfer from hospitals without EVT capability onsite. A novel computer aided triage system, Viz LVO, has the potential to streamline workflows. This platform includes an image viewer, communication system, and an artificial intelligence (AI) algorithm that automatically identifies suspected LVO strokes on CTA imaging and rapidly triggers alerts. We hypothesize that the Viz application will decrease timeto- treatment. Methods: A prospective database was assessed for patients who presented to a stroke center utilizing Viz LVO in the Mount Sinai Health System in New York and underwent EVT following transfer for LVO stroke between July 2018 and March 2020. This time period was chosen due to the COVID-19 pandemic affecting stroke workflow after March 2020. Time intervals were compared for 55 patients divided into Pre- and Post-Viz cohorts. Results: The median initial door-to-neuroendovascular team (NT) notification time interval was significantly faster (25.0 minutes [IQR=12.0] vs 40.0 minutes [IQR=61.0];p=0.01) with significantly less variation (p<0.05). The median initial door-to-skin puncture time interval was 25 minutes shorter in the Post-Viz cohort, although not statistically significant (p=0.15). Post Viz LVO implementation, the Viz notification was the first NT notification 38% (10/26) of the time. Conclusions: Our preliminary results have shown that Viz LVO implementation is associated with earlier, more consistent NT notification times and potentially treatment times. This platform presents a novel application of AI that can serve as an early warning system and a failsafe to ensure that no LVO is left behind. Further studies are warranted.(Figure Presented).
ABSTRACT
Background: The degree to which the COVID-19 pandemic has affected systems of care, in particular those for time-sensitive conditions such as stroke, remains poorly quantified. We sought to evaluate the impact of COVID-19 in the overall screening for acute stroke utilizing a commercial clinical artificial intelligence (AI) platform. Methods: Data were derived from the Viz Platform, an AI application designed to optimize the workflow of acute stroke patients. Neuroimaging data on suspected stroke patients across 97 hospitals in 20 US states were collected in real-time and retrospectively analyzed with the number of patients undergoing imaging screening serving as a surrogate for the amount of stroke care. The main outcome measures were the number of CTA, CTP, Large vessel occlusions (LVOs) (defined according to the automated software detection), and severe strokes on CTP (defined as those with hypoperfusion volumes>70mL) normalized as number of patients per day per hospital. Data from the pre-pandemic (November 4, 2019 to February 29, 2020) and pandemic (March 1 to May 10, 2020) periods were compared at national and state levels. Correlations were made between the inter-period changes in imaging screening, stroke hospitalizations, and thrombectomy procedures using state-specific sampling. Results: A total of 23,223 patients were included. The incidence of LVO on CTA and severe strokes on CTP were 11.2%(n=2,602) and 14.7%(n=1,229/8,328), respectively. There were significant declines in the overall number of CTAs (-22.8%;1.39 to 1.07 patients/day/hospital,p<0.001) and CTPs (-26.1%;0.50 to 0.37 patients/day/hospital,p<0.001) as well as in the incidence of LVO (-17.1%;0.15 to 0.13 patients/day/hospital,p<0.001) and severe strokes on CTP (-16.7%;0.12 to 0.10 patients/day/hospital, p<0.005). The sampled cohort showed similar declines in the rates of LVOs versus thrombectomy (18.8%vs.19.5%, p=0.9) and CSC hospitalizations (18.8%vs.11.0%, p=0.4). Conclusions: A significant decline in stroke imaging screening has occurred during the COVID-19 pandemic. This underscores the broader application of AI neuroimaging platforms for the real-time monitoring of stroke systems of care.