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Objective To describe the clinical data from the first 108 patients seen in the Mayo Clinic post–COVID-19 care clinic (PCOCC). Methods After Institutional Review Board approval, we reviewed the charts of the first 108 patients seen between January 19, 2021, and April 29, 2021, in the PCOCC and abstracted from the electronic medical record into a standardized database to facilitate analysis. Patients were grouped into phenotypes by expert review. Results Most of the patients seen in our clinic were female (75%; 81/108), and the median age at presentation was 46 years (interquartile range, 37 to 55 years). All had post-acute sequelae of SARS-CoV-2 infection, with 6 clinical phenotypes being identified: fatigue predominant (n=69), dyspnea predominant (n=23), myalgia predominant (n=6), orthostasis predominant (n=6), chest pain predominant (n=3), and headache predominant (n=1). The fatigue-predominant phenotype was more common in women, and the dyspnea-predominant phenotype was more common in men. Interleukin 6 (IL-6) was elevated in 61% of patients (69% of women; P=.0046), which was more common than elevation in C-reactive protein and erythrocyte sedimentation rate, identified in 17% and 20% of cases, respectively. Conclusion In our PCOCC, we observed several distinct clinical phenotypes. Fatigue predominance was the most common presentation and was associated with elevated IL-6 levels and female sex. Dyspnea predominance was more common in men and was not associated with elevated IL-6 levels. IL-6 levels were more likely than erythrocyte sedimentation rate and C-reactive protein to be elevated in patients with post-acute sequelae of SARS-CoV-2 infection.

Predictive models have played a critical role in local, national, and international response to the COVID-19 pandemic. In the United States, health care systems and governmental agencies have relied on several models, such as the Institute for Health Metrics and Evaluation, Youyang Gu (YYG), Massachusetts Institute of Technology, and Centers for Disease Control and Prevention ensemble, to predict short- and long-term trends in disease activity. The Mayo Clinic Bayesian SIR model, recently made publicly available, has informed Mayo Clinic practice leadership at all sites across the United States and has been shared with Minnesota governmental leadership to help inform critical decisions during the past year. One key to the accuracy of the Mayo Clinic model is its ability to adapt to the constantly changing dynamics of the pandemic and uncertainties of human behavior, such as changes in the rate of contact among the population over time and by geographic location and now new virus variants. The Mayo Clinic model can also be used to forecast COVID-19 trends in different hypothetical worlds in which no vaccine is available, vaccinations are no longer being accepted from this point forward, and 75% of the population is already vaccinated. Surveys indicate that half of American adults are hesitant to receive a COVID-19 vaccine, and lack of understanding of the benefits of vaccination is an important barrier to use. The focus of this paper is to illustrate the stark contrast between these 3 scenarios and to demonstrate, mathematically, the benefit of high vaccine uptake on the future course of the pandemic.

To evaluate the cost-effectiveness of an artificial intelligence electrocardiogram (AI-ECG) algorithm under various clinical and cost scenarios when used for universal screening at age 65.We used decision analytic modeling to perform a cost-effectiveness analysis of the use of AI-ECG to screen for asymptomatic left ventricular dysfunction (ALVD) once at age 65 compared with no screening. This screening consisted of an initial screening decision tree and subsequent construction of a Markov model. One-way sensitivity analysis on various disease and cost parameters to evaluate cost-effectiveness at both $50,000 per quality-adjusted life year (QALY) and $100,000 per QALY willingness-to-pay threshold.We found that for universal screening at age 65, the novel AI-ECG algorithm would cost $43,351 per QALY gained, test performance, disease characteristics, and testing cost parameters significantly affect cost-effectiveness, and screening at ages 55 and 75 would cost $48,649 and $52,072 per QALY gained, respectively. Overall, under most of the clinical scenarios modeled, coupled with its robust test performance in both testing and validation cohorts, screening with the novel AI-ECG algorithm appears to be cost-effective at a willingness-to-pay threshold of $50,000.Universal screening for ALVD with the novel AI-ECG appears to be cost-effective under most clinical scenarios with a cost of$50,000 per QALY. Cost-effectiveness is particularly sensitive to both the probability of disease progression and the cost of screening and downstream testing. To improve cost-effectiveness modeling, further study of the natural progression and treatment of ALVD and external validation of AI-ECG should be undertaken.

Contains fulltext : 235066.pdf (Publisher’s version ) (Open Access) To determine the effect of COVID-19 convalescent plasma on mortality, we aggregated patient outcome data from 10 randomized clinical trials, 20 matched control studies, 2 dose-response studies, and 96 case reports or case series. Studies published between January 1, 2020, and January 16, 2021, were identified through a systematic search of online PubMed and MEDLINE databases. Random effects analyses of randomized clinical trials and matched control data demonstrated that patients with COVID-19 transfused with convalescent plasma exhibited a lower mortality rate compared with 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 patients with COVID-19.

In March 2020, our institution developed an interdisciplinary predictive analytics task force to provide coronavirus disease 2019 (COVID-19) hospital census forecasting to help clinical leaders understand the potential impacts on hospital operations. As the situation unfolded into a pandemic, our task force provided predictive insights through a structured set of visualizations and key messages that have helped the practice to anticipate and react to changing operational needs and opportunities. The framework shared here for the deployment of a COVID-19 predictive analytics task force could be adapted for effective implementation at other institutions to provide evidence-based messaging for operational decision-making. For hospitals without such a structure, immediate consideration may be warranted in light of the devastating COVID-19 third-wave which has arrived for winter 2020-2021.

OBJECTIVE: To provide an update on key safety metrics after transfusion of convalescent plasma in hospitalized coronavirus 2019 (COVID-19) patients, having previously demonstrated safety in 5000 hospitalized patients. PATIENTS AND METHODS: From April 3 to June 2, 2020, the US Food and Drug Administration Expanded Access Program for COVID-19 convalescent plasma transfused a convenience sample of 20,000 hospitalized patients with COVID-19 convalescent plasma. RESULTS: The incidence of all serious adverse events was low; these included transfusion reactions (n=78

Objective To estimate the seroprevalence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibodies in health care personnel. Methods The Mayo Clinic Serology Screening Program was created to provide a voluntary, two-stage testing program for SARS-CoV-2 antibodies to health care personnel. The first stage used a dried blood spot screening test initiated on June 15, 2020. Those participants identified as reactive were advised to have confirmatory testing via a venipuncture. Venipuncture results through August 8, 2020, were considered. Consent and authorization for testing was required to participate in the screening program. This report, which was conducted under an institutional review board–approved protocol, only includes employees who have further authorized their records for use in research. Results A total of 81,113 health care personnel were eligible for the program, and of these 29,606 participated in the screening program. A total of 4284 (14.5%) of the dried blood spot test results were "reactive" and warranted confirmatory testing. Confirmatory testing was completed on 4094 (95.6%) of the screen reactive with an overall seroprevalence rate of 0.60% (95% CI, 0.52% to 0.69%). Significant variation in seroprevalence was observed by region of the country and age group. Conclusion The seroprevalence for SARS-CoV-2 antibodies through August 8, 2020, was found to be lower than previously reported in other health care organizations. There was an observation that seroprevalence may be associated with community disease burden.

Artificial intelligence (AI) is a nontechnical, popular term that refers to machine learning of various types but most often to deep neural networks. Cardiology is at the forefront of AI in medicine. For this review, we searched PubMed and MEDLINE databases with no date restriction using search terms related to AI and cardiology. Articles were selected for inclusion on the basis of relevance. We highlight the major achievements in recent years in nearly all areas of cardiology and underscore the mounting evidence suggesting how AI will take center stage in the field. Artificial intelligence requires a close collaboration among computer scientists, clinical investigators, clinicians, and other users in order to identify the most relevant problems to be solved. Best practices in the generation and implementation of AI include the selection of ideal data sources, taking into account common challenges during the interpretation, validation, and generalizability of findings, and addressing safety and ethical concerns before final implementation. The future of AI in cardiology and in medicine in general is bright as the collaboration between investigators and clinicians continues to excel.

Objective To examine the effect of intravenous iodinated contrast material administration on the subsequent development of acute kidney injury (AKI), emergent dialysis, and short-term mortality using a propensity score–adjusted analysis of computed tomographic scan recipients with chronic kidney disease (CKD). Patients and Methods In this institutional review board–approved retrospective study, all patients with CKD who received a contrast-enhanced (contrast group) or unenhanced (noncontrast group) computed tomographic scan from January 1, 2000, to August 1, 2013 were identified. Patients were subdivided into CKD stage III (baseline estimated glomerular filtration rate, 30-59 mL/min per 1.73 m 2 ) and CKD stage IV-V (baseline estimated glomerular filtration rate, 2 ) subgroups and separately underwent propensity score generation, stratification, and 1:1 matching. Rates of AKI, 30-day emergent dialysis, and mortality were compared between contrast and noncontrast groups. Sensitivity analyses examining only patients with stable prescan serum creatinine levels and incorporating intravenous fluid administration at the time of the CT scan into the model were also performed. Results A total of 6902 patients (4496 CKD stage III, matched: 1220 contrast and 1220 noncontrast; 2086 CKD stage IV-V, matched: 491 contrast and 491 noncontrast) were included in the study. After propensity score adjustment, rates of AKI, emergent dialysis, and mortality were not significantly higher in the contrast group than in the noncontrast group in either CKD subgroup (CKD stage III: OR, 0.65-1.00; P P =.22-.99). Both sensitivity analyses revealed similar results. Conclusion Intravenous contrast material administration was not associated with an increased risk of AKI, emergent dialysis, and short-term mortality in a cohort of patients with diminished renal function.

Objectives To evaluate focal treatment of melanoma metastases and to explore whether any potential extended survival benefit exists in a select patient population. Patients and Methods All patients who underwent image-guided local thermal ablation of metastatic melanoma over an 11-year period (January 1, 2002, to December 31, 2013) were retrospectively identified using an internally maintained clinical registry. Only patients with oligometastatic stage IV disease amenable to complete ablation of all clinical disease at the time of ablation were included in the analysis. Overall survival and median progression-free survival periods were calculated. Results Thirty-three patients with primary ocular or nonocular melanoma had 66 metastases treated in the lungs, liver, bones, or soft tissues. Eleven (33%) patients were on systemic medical therapy at the time of the procedure. The median survival time was 3.8 years (range, 0.5-10.5 years), with a 4-year estimated survival of 44.1% (95% CI, 28%-68%). Local recurrence at the ablation site developed in 15.1% (5 of 33) of the patients and 13.6% of the tumors (9 of 66). The median progression-free survival time was 4.4 months (95% CI, 1.4 months to 10.5 years), with an estimated 1-year progression-free survival of 30.3% (95% CI, 18%-51%). A subgroup analysis identified 11 patients with primary ocular melanoma and 22 with nonocular melanoma, with a median survival time of 3.9 years (range, 0.9-4.7 years) and 3.8 years (range, 0.5-10.5 years), respectively ( P =.58). There were no major complications and no deaths within 30 days of the procedure. Conclusion Selective use of image-guided thermal ablation of oligometastatic melanoma may provide results similar to surgical resection in terms of technical effectiveness and oncologic outcomes with minimal risk.

To determine whether targeted pharmacological improvement of insulin sensitivity will normalize the associated elevations of thrombotic and inflammatory cardiovascular disease (CVD) biomarkers in individuals with insulin resistance.Study 1 was a cross-sectional study of Asian Indians with and without diabetes mellitus and Northern European Americans without diabetes (n=14 each) conducted between December 11, 2003, and July 14, 2006. Study 2 was a secondary analysis of a double-blind randomized controlled study conducted between August 19, 2005, and August 24, 2010, that included 25 individuals with untreated diabetes or impaired fasting glucose who were randomized to receive placebo (n=13) or a combination of metformin, 1000 mg twice daily, and pioglitazone, 45 mg daily (n=12), for 3 months. In both studies, measurements of insulin sensitivity (euglycemic-hyperinsulinemic clamp) and plasma inflammatory and thrombotic factor concentrations were obtained on enrollment (studies 1 and 2) and after intervention (study 2).Study 1 demonstrated significant correlations between insulin sensitivity and plasma adiponectin, high-density lipoprotein cholesterol, plasminogen activator inhibitor 1, interleukin 6, tumor necrosis factor α, and triglycerides. Insulin sensitizer therapy significantly improved insulin sensitivity, inflammatory cytokines except interleukin 6, and thrombotic factors except fibrinogen, without concomitant changes in weight, blood pressure, or body composition.Insulin sensitizer therapy ameliorates inflammatory and thrombotic factors implicated in developing CVD. Interventions to improve insulin sensitivity may thus be considered as therapeutic options to reduce CVD burden in insulin-resistant states, although further research is needed to determine long-term effects on morbidity and mortality.