ABSTRACT
Introduction: COVID-19 has been associated with venous and arterial thrombotic complications. The objective of our study was to determine whether markers of coagulation and hemostatic activation (MOCHA) on admission could identify COVID-19 patients at risk for thrombotic events. Methods: COVID-19 patients admitted to a tertiary academic healthcare system from April 3, 2020 to July 31, 2020 underwent admission testing of MOCHA profile parameters (plasma d-dimer, prothrombin fragment 1.2, thrombin-antithrombin complex, and fibrin monomer). For this analysis we excluded patients on outpatient anticoagulation therapy preceding admission. Prespecified endpoints monitored during hospitalization included deep vein thrombosis, pulmonary embolism, myocardial infarction, ischemic stroke and access line thrombosis. Results: During the study period, 276 patients were included in the analysis cohort (mean age 59 ± 6.3 years, 47% female, 83% non-white race). Arterial and venous thrombotic events occurred in 43 (16%) patients (see Table). Each coagulation marker was independently associated with the composite endpoint (p<0.05). Admission MOCHA with ≥ 2 abnormalities was associated with the composite endpoint (OR 3.1, 95% CI 1.2-8.3), ICU admission (OR 3.2, 95% CI 1.8-5.5) and intubation (OR 2.8, 95% CI 1.5-5.5). Admission MOCHA with < 2 abnormalities (26% of the cohort) had sensitivity of 88% and a negative predictive value of 93% for an in-hospital endpoint. Conclusion: Admission MOCHA with ≥ 2 abnormalities identified COVID-19 patients at risk for a thrombotic event, ICU admission and intubation while < 2 abnormalities identified a subgroup of patients who were at low risk for thrombotic events. Our results suggest that an admission MOCHA profile can be useful to risk stratify COVID-19 patients. Further studies are needed to determine whether an admission MOCHA profile can guide anticoagulation therapy and improve overall clinical outcomes.(Figure Presented).
ABSTRACT
Background and purpose: Coronavirus disease 2019 (COVID-19) is associated with a small but clinically significant risk of stroke, the cause of which is frequently cryptogenic. In a large multinational cohort of consecutive COVID-19 patients with stroke, we evaluated clinical predictors of cryptogenic stroke, short-term functional outcomes and in-hospital mortality among patients according to stroke etiology. Methods: We explored clinical characteristics and short-term outcomes of consecutively evaluated patients 18 years of age or older with acute ischemic stroke (AIS) and laboratory-confirmed COVID- 19 from 31 hospitals in 4 countries (3/1/20-6/16/20). Results: Of the 14.483 laboratory-confirmed patients with COVID-19, 156 (1.1%) were diagnosed with AIS. Sixty-one (39.4%) were female, 84 (67.2%) white, and 88 (61.5%) were between 60-79 years of age. The most frequently reported etiology of AIS was cryptogenic (55/129, 42.6%), which was associated with significantly higher white blood cell count, c-reactive protein, and D-dimer levels than non-cryptogenic AIS patients (p</=0.05 for all comparisons). In a multivariable backward stepwise regression model estimating the odds of in-hospital mortality, cryptogenic stroke mechanism was associated with a fivefold greater odds in-hospital mortality than strokes due to any other mechanism (adjusted OR 5.16, 95%CI 1.41-18.87, p=0.01). In that model, older age (aOR2.05 per decade, 95%CI 1.35-3.11, p<0.01) and higher baseline NIHSS (aOR 1.12, 95%CI 1.02-1.21, p=0.01) were also independently predictive of mortality. Conclusions: Our findings suggest that cryptogenic stroke among COVID-19 patients may berelated to more severe disease and carries a significant risk of early mortality.
ABSTRACT
Introduction: To evaluate overall ischemic stroke rates, specific subtypes, and clinical presentation during the COVID-19 pandemic in a multicenter observational study from eight states across US. Methods: We compared all ischemic strokes admitted between January 2019 and May 2020, grouped as;March-May 2020 (COVID-19 period), March-May 2019 (seasonal pre-COVID period) and November 2019-January 2020 (immediate pre-COVID-19 period). Primary outcome was stroke severity at admission measured by NIHSS stratified as mild (0-7), moderate (8-14), and severe (>14) symptoms. Secondary outcomes were number of large vessel occlusions (LVOs), stroke etiology, IV-tPA rates, and disposition. Results: Of the 7,969 patients diagnosed with acute stroke during the study period, 933 (12%) presented in the COVID-19 period, 1319 (17%), and 1254 (16%) presented in the seasonal pre- COVID-19 and immediate pre-COVID-19 periods, respectively. Significant decline was observed in the weekly mean volume of newly diagnosed strokes (98±7.3 vs 50±20, p<0.01 and 95±10.5 vs 50±20, p<0.01), LVOs (16.5±3.8 vs 8.3±5.9, p<0.01 and 14.3± 4.5 vs 8.3±5.9, p<0.01), and IV-tPA (5.3±2.9 vs 10.9±3.4 and 12.7±4.1, p<0.01). Mean weekly proportion of LVOs remained the same, when compared with seasonal pre-COVID-19 period (18%±5 vs 16%±7, p=0.24) and immediate pre-COVID-19 period (17.4%±4 vs. 16%±7, p=0.32). Additionally, these patients presented with less severe disease (NIHSS<14;aOR: 0.63, 95%CI: 0.41-0.97, p=0.035) during the COVID-19 period ascompared to immediate pre-COVID-19 period. Conclusions: We observed a decrease in newly diagnosed stroke cases and rates of IV-tPAadministration, while the LVO frequency remained unchanged during the COVID-19 pandemic.Additionally, these stroke patients had more severe presentations.
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.