BACKGROUND. Convalescent plasma is the only antibody-based therapy currently available for patients with coronavirus disease 2019 (COVID-19). It has robust historical precedence and sound biological plausibility. Although promising, convalescent plasma has not yet been shown to be safe as a treatment for COVID-19. METHODS. Thus, we analyzed key safety metrics after transfusion of ABO-compatible human COVID-19 convalescent plasma in 5000 hospitalized adults with severe or life-threatening COVID-19, with 66% in the intensive care unit, as part of the US FDA expanded access program for COVID-19 convalescent plasma. RESULTS. The incidence of all serious adverse events (SAEs), including mortality rate (0.3%), in the first 4 hours after transfusion was <1%. Of the 36 reported SAEs, there were 25 reported incidences of related SAEs, including mortality (n = 4), transfusion-associated circulatory overload (n = 7), transfusion-related acute lung injury (n = 11), and severe allergic transfusion reactions (n = 3). However, only 2 of 36 SAEs were judged as definitely related to the convalescent plasma transfusion by the treating physician. The 7-day mortality rate was 14.9%. CONCLUSION. Given the deadly nature of COVID-19 and the large population of critically ill patients included in these analyses, the mortality rate does not appear excessive. These early indicators suggest that transfusion of convalescent plasma is safe in hospitalized patients with COVID-19. TRIAL REGISTRATION. ClinicalTrials.gov NCT04338360. FUNDING. Mayo Clinic, Biomedical Advanced Research and Development Authority (75A50120C00096), National Center for Advancing Translational Sciences (UL1TR002377), National Heart, Lung, and Blood Institute (5R35HL139854 and R01 HL059842), National Institute of Diabetes and Digestive and Kidney Diseases (5T32DK07352), Natural Sciences and Engineering Research Council of Canada (PDF-532926-2019), National Institute of Allergy and Infectious Disease (R21 AI145356, R21 AI152318, and AI152078), Schwab Charitable Fund, United Health Group, National Basketball Association, Millennium Pharmaceuticals, and Octapharma USA Inc.

Aims : Early detection of aortic stenosis (AS) is becoming increasingly important with a better outcome after aortic valve replacement in asymptomatic severe AS patients and a poor outcome in moderate AS. We aimed to develop artificial intelligence-enabled electrocardiogram (AI-ECG) using a convolutional neural network to identify patients with moderate to severe AS. Methods and results : Between 1989 and 2019, 258 607 adults [mean age 63 ± 16.3 years; women 122 790 (48%)] with an echocardiography and an ECG performed within 180 days were identified from the Mayo Clinic database. Moderate to severe AS by echocardiography was present in 9723 (3.7%) patients. Artificial intelligence training was performed in 129 788 (50%), validation in 25 893 (10%), and testing in 102 926 (40%) randomly selected subjects. In the test group, the AI-ECG labelled 3833 (3.7%) patients as positive with the area under the curve (AUC) of 0.85. The sensitivity, specificity, and accuracy were 78%, 74%, and 74%, respectively. The sensitivity increased and the specificity decreased as age increased. Women had lower sensitivity but higher specificity compared with men at any age groups. The model performance increased when age and sex were added to the model (AUC 0.87), which further increased to 0.90 in patients without hypertension. Patients with false-positive AI-ECGs had twice the risk for developing moderate or severe AS in 15 years compared with true negative AI-ECGs (hazard ratio 2.18, 95% confidence interval 1.90–2.50). Conclusion : An AI-ECG can identify patients with moderate or severe AS and may serve as a powerful screening tool for AS in the community.

Importance: Passive antibody transfer is a longstanding treatment strategy for infectious diseases that involve the respiratory system. In this context, human convalescent plasma has been used to treat coronavirus disease 2019 (COVID-19), but the efficacy remains uncertain. Objective: To explore potential signals of efficacy of COVID-19 convalescent plasma. Design: Open-label, Expanded Access Program (EAP) for the treatment of COVID-19 patients with human convalescent plasma. Setting: Multicenter, including 2,807 acute care facilities in the US and territories. Participants: Adult participants enrolled and transfused under the purview of the US Convalescent Plasma EAP program between April 4 and July 4, 2020 who were hospitalized with (or at risk of) severe or life threatening acute COVID-19 respiratory syndrome. Intervention: Transfusion of at least one unit of human COVID-19 convalescent plasma using standard transfusion guidelines at any time during hospitalization. Convalescent plasma was donated by recently-recovered COVID-19 survivors, and the antibody levels in the units collected were unknown at the time of transfusion. Main Outcomes and Measures: Seven and thirty-day mortality. Results: The 35,322 transfused patients had heterogeneous demographic and clinical characteristics. This cohort included a high proportion of critically-ill patients, with 52.3% in the intensive care unit (ICU) and 27.5% receiving mechanical ventilation at the time of plasma transfusion. The seven-day mortality rate was 8.7% [95% CI 8.3%-9.2%] in patients transfused within 3 days of COVID-19 diagnosis but 11.9% [11.4%-12.2%] in patients transfused 4 or more days after diagnosis (p<0.001). Similar findings were observed in 30-day mortality (21.6% vs. 26.7%, p18.45 S/Co), seven-day mortality was 8.9% (6.8%, 11.7%); for recipients of medium IgG plasma (4.62 to 18.45 S/Co) mortality was 11.6% (10.3%, 13.1%); and for recipients of low IgG plasma (<4.62 S/Co) mortality was 13.7% (11.1%, 16.8%) (p=0.048). This unadjusted dose-response relationship with IgG was also observed in thirty-day mortality (p=0.021). The pooled relative risk of mortality among patients transfused with high antibody level plasma units was 0.65 [0.47-0.92] for 7 days and 0.77 [0.63-0.94] for 30 days compared to low antibody level plasma units. Conclusions and Relevance: The relationships between reduced mortality and both earlier time to transfusion and higher antibody levels provide signatures of efficacy for convalescent plasma in the treatment of hospitalized COVID-19 patients. This information may be informative for the treatment of COVID-19 and design of randomized clinical trials involving convalescent plasma. Trial Registration: ClinicalTrials.gov Identifier: NCT04338360 Key Points: Question: Does transfusion of human convalescent plasma reduce mortality among hospitalized COVID-19 patients? Findings: Transfusion of convalescent plasma with higher antibody levels to hospitalized COVID-19 patients significantly reduced mortality compared to transfusions with low antibody levels. Transfusions within three days of COVID-19 diagnosis yielded greater reductions in mortality. Meaning: Embedded in an Expanded Access Program providing access to COVID-19 convalescent plasma and designed to assess its safety, several signals consistent with efficacy of convalescent plasma in the treatment of hospitalized COVID-19 patients emerged.

Background: Identification of systolic heart failure among patients presenting to the emergency department (ED) with acute dyspnea is challenging. The reasons for dyspnea are often multifactorial. A focused physical evaluation and diagnostic testing can lack sensitivity and specificity. The objective of this study was to assess the accuracy of an artificial intelligence-enabled ECG to identify patients presenting with dyspnea who have left ventricular systolic dysfunction (LVSD). Methods: We retrospectively applied a validated artificial intelligence-enabled ECG algorithm for the identification of LVSD (defined as LV ejection fraction ≤35%) to a cohort of patients aged ≥18 years who were evaluated in the ED at a Mayo Clinic site with dyspnea. Patients were included if they had at least one standard 12-lead ECG acquired on the date of the ED visit and an echocardiogram performed within 30 days of presentation. Patients with prior LVSD were excluded. We assessed the model performance using area under the receiver operating characteristic curve, accuracy, sensitivity, and specificity. Results: A total of 1606 patients were included. Median time from ECG to echocardiogram was 1 day (Q1: 1, Q3: 2). The artificial intelligence-enabled ECG algorithm identified LVSD with an area under the receiver operating characteristic curve of 0.89 (95% CI, 0.86–0.91) and accuracy of 85.9%. Sensitivity, specificity, negative predictive value, and positive predictive value were 74%, 87%, 97%, and 40%, respectively. To identify an ejection fraction 800 identified LVSD with an area under the receiver operating characteristic curve of 0.80 (95% CI, 0.76–0.84). Conclusions: The ECG is an inexpensive, ubiquitous, painless test which can be quickly obtained in the ED. It effectively identifies LVSD in selected patients presenting to the ED with dyspnea when analyzed with artificial intelligence and outperforms NT-proBNP. Graphic A graphic abstract is available for this article.

To determine the effect of COVID-19 convalescent plasma on mortality, we aggregated patient outcome data from 10 randomized clinical trials (RCT), 20 matched-control studies, two dose-response studies, and 96 case-reports or case-series. Studies published between January 1, 2020 – January 16, 2021 were identified through a systematic search of online PubMed and MEDLINE databases. Random-effects analyses of RCT and matched-control data demonstrated that COVID-19 patients transfused with convalescent plasma exhibited a lower mortality rate compared to patients receiving standard treatments. Additional analyses showed that early transfusion (within 3 days of hospital admission) of higher-titer plasma is associated with lower patient mortality. These data provide evidence favoring the efficacy of human convalescent plasma as a therapeutic agent in hospitalized COVID-19 patients.