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Background: The worldwide market for continuing medical education (CME) was severely affected by the COVID-19 pandemic, which precipitated an increase in web-based CME course attendance. Virtual education methods may be effective for engaging learners and changing behaviors. However, more information is needed about physician preferences for in-person vs. livestreamed CME courses in the postpandemic era. Because of the paucity of data regarding this topic, the current study was designed to evaluate CME participant characteristics, preferences, engagement, and satisfaction with traditional in-person vs. virtual educational methods., Methods: A cross-sectional study was performed of attendees of two large internal medicine CME courses held in 2021. Both CME courses were offered via in-person and livestream options, and were taught by Mayo Clinic content experts. Participants, who consisted of practicing physicians seeking CME, completed a 41-question survey after CME course completion. Statistical comparisons were performed by using Fisher exact tests for all survey items, except for those with ordinal response sets, which were compared with Cochran-Armitage trend tests., Results: A total of 146 participants completed the survey (response rate, 30.2%). Among the 77 respondents who attended in-person courses, the most frequent reasons indicated were the opportunity to travel (66%) and collaboration/networking with others (25%). Among the 68 respondents who attended the livestream courses, the most frequent reasons indicated included COVID-19-related concerns (65%), convenience (46%), and travel costs (34%). The percentage of respondents who indicated that they would choose the same mode of attendance if given the option again was higher for those who attended in person than for those who attended via livestream (91% vs. 65%, P < .001)., Conclusions: These data suggest that in-person course offerings will continue to be a preferred learning method for some physicians. However, most respondents who attended virtually preferred that method. Therefore, hybrid CME models offering both in-person and virtual options may be most beneficial for meeting the needs of all CME learners., (© 2024. The Author(s).)

Background: We applied machine learning (ML) algorithms to generate a risk prediction tool [Collaboration for Risk Evaluation in COVID-19 (CORE-COVID-19)] for predicting the composite of 30-day endotracheal intubation, intravenous administration of vasopressors, or death after COVID-19 hospitalization and compared it with the existing risk scores., Methods: This is a retrospective study of adults hospitalized with COVID-19 from March 2020 to February 2021. Patients, each with 92 variables, and one composite outcome underwent feature selection process to identify the most predictive variables. Selected variables were modeled to build four ML algorithms (artificial neural network, support vector machine, gradient boosting machine, and Logistic regression) and an ensemble model to generate a CORE-COVID-19 model to predict the composite outcome and compared with existing risk prediction scores. The net benefit for clinical use of each model was assessed by decision curve analysis., Results: Of 1796 patients, 278 (15%) patients reached primary outcome. Six most predictive features were identified. Four ML algorithms achieved comparable discrimination (P > 0.827) with c-statistics ranged 0.849-0.856, calibration slopes 0.911-1.173, and Hosmer-Lemeshow P > 0.141 in validation dataset. These 6-variable fitted CORE-COVID-19 model revealed a c-statistic of 0.880, which was significantly (P < 0.04) higher than ISARIC-4C (0.751), CURB-65 (0.735), qSOFA (0.676), and MEWS (0.674) for outcome prediction. The net benefit of the CORE-COVID-19 model was greater than that of the existing risk scores., Conclusion: The CORE-COVID-19 model accurately assigned 88% of patients who potentially progressed to 30-day composite events and revealed improved performance over existing risk scores, indicating its potential utility in clinical practice., (© 2023. The Author(s).)

Objective: To compare clinical characteristics, treatment patterns, and 30-day all-cause readmission and mortality between patients hospitalized for heart failure (HF) before and during the coronavirus disease 2019 (COVID-19) pandemic., Patients and Methods: The study was conducted at 16 hospitals across 3 geographically dispersed US states. The study included 6769 adults (mean age, 74 years; 56% [5033 of 8989] men) with cumulative 8989 HF hospitalizations: 2341 hospitalizations during the COVID-19 pandemic (March 1 through October 30, 2020) and 6648 in the pre-COVID-19 (October 1, 2018, through February 28, 2020) comparator group. We used Poisson regression, Kaplan-Meier estimates, multivariable logistic, and Cox regression analysis to determine whether prespecified study outcomes varied by time frames., Results: The adjusted 30-day readmission rate decreased from 13.1% (872 of 6648) in the pre-COVID-19 period to 10.0% (234 of 2341) in the COVID-19 pandemic period (relative risk reduction, 23%; hazard ratio, 0.77; 95% CI, 0.66 to 0.89). Conversely, all-cause mortality increased from 9.7% (645 of 6648) in the pre-COVID-19 period to 11.3% (264 of 2341) in the COVID-19 pandemic period (relative risk increase, 16%; number of admissions needed for one additional death, 62.5; hazard ratio, 1.19; 95% CI, 1.02 to 1.39). Despite significant differences in rates of index hospitalization, readmission, and mortality across the study time frames, the disease severity, HF subtypes, and treatment patterns remained unchanged (P>0.05)., Conclusion: The findings of this large tristate multicenter cohort study of HF hospitalizations suggest lower rates of index hospitalizations and 30-day readmissions but higher incidence of 30-day mortality with broadly similar use of HF medication, surgical interventions, and devices during the COVID-19 pandemic compared with the pre-COVID-19 time frame., (Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)

Purpose of Review: The COVID-19 pandemic has been associated with significant morbidity and mortality worldwide. In addition to those with advanced age and co-morbidities such as heart disease or cancer, obese individuals have also had very high rates of hospitalization, critical illness, need for ventilator support, as well as mortality. A number of factors associated with obesity have led to devastating consequences as these two pandemics have interacted., Recent Findings: Obese individuals through a combination of structural and cellular level changes have greater risk of ischemic heart disease, diabetes, cancer, and respiratory disease, which are themselves risk-factors for acquiring COVID-19 disease. These structural changes also result in increased intra-abdominal and intra-thoracic pressure as well as a restrictive lung physiology that leads to reduction in total lung capacity, functional residual capacity, and increase in airway hyper-reactivity. Adipose tissue is also impacted in obese individuals leading to local as well as systemic inflammation, which can contribute to increased release of free fatty acids and systemic insulin resistance. Additionally, angiotensin-converting enzyme 2 and dipeptidyl peptidase 4, which act as receptors for SARS-CoV-2 are also significantly increased in obese individuals. The present manuscript reviews these structural, immune, and molecular changes associated with obesity that make obese individuals more vulnerable to acquiring severe COVID-19 and more challenging to manage associated complications., (© 2021. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Purpose: The purpose of the present study was to investigate body mass index, multi-morbidity, and COVID-19 Risk Score as predictors of severe COVID-19 outcomes., Patients: Patients from this study are from a well-characterized patient cohort collected at Mayo Clinic between January 1, 2020 and May 23, 2020; with confirmed COVID-19 diagnosis defined as a positive result on reverse-transcriptase-polymerase-chain-reaction (RT-PCR) assays from nasopharyngeal swab specimens., Measures: Demographic and clinical data were extracted from the electronic medical record. The data included: date of birth, gender, ethnicity, race, marital status, medications (active COVID-19 agents), weight and height (from which the Body Mass Index (BMI) was calculated, history of smoking, and comorbid conditions to calculate the Charlson Comorbidity Index (CCI) and the U.S Department of Health and Human Services (DHHS) multi-morbidity score. An additional COVID-19 Risk Score was also included. Outcomes included hospital admission, ICU admission, and death., Results: Cox proportional hazards models were used to determine the impact on mortality or hospital admission. Age, sex, and race (white/Latino, white/non-Latino, other, did not disclose) were adjusted for in the model. Patients with higher COVID-19 Risk Scores had a significantly higher likelihood of being at least admitted to the hospital (HR = 1.80; 95% CI = 1.30, 2.50; P  < .001), or experiencing death or inpatient admission (includes ICU admissions) (HR = 1.20; 95% CI = 1.02, 1.42; P  = .028). Age was the only statistically significant demographic predictor, but obesity was not a significant predictor of any of the outcomes., Conclusion: Age and COVID-19 Risk Scores were significant predictors of severe COVID-19 outcomes. Further work should examine the properties of the COVID-19 Risk Factors Scale.

Objective: To describe the process and outcome of creating a patient cohort in the early stages of the COVID-19 pandemic in order to better understand the process of and predict the outcomes of COVID-19., Patients and Methods: A total of 1169 adults aged 18 years of age or older who tested positive in Mayo Clinic Rochester or the Mayo Clinic Midwest Health System between January 1 and May 23 of 2020., Results: Patients were on average 43.9 years of age and 50.7% were female. Most patients were white (69.0%), and Blacks (23.4%) and Asians (5.8%) were also represented in larger numbers. Hispanics represented 16.3% of the sample. Just under half of patients were married (48.4%). Common comorbid conditions included: cardiovascular diseases (25.1%), dyslipidemia (16.0%), diabetes mellitus (11.2%), chronic obstructive pulmonary disease (6.6%), asthma (7.5%), and cancer (5.1%). All other comorbid conditions were less the 5% in prevalence. Data on 3 comorbidity indices are also available including the: DHHS multi-morbidity score, Charlson Comorbidity Index, and Mayo Clinic COVID-19 Risk Factor Score., Conclusion: In addition to managing the ever raging pandemic and growing death rates, it is equally important that we develop adequate resources for the investigation and understanding of COVID-19-related predictors and outcomes.

Background: Before the COVID-19 pandemic began, medical staff and academic department workers reported increasing levels of stress and burnout because of strain on the health care system. The COVID-19 pandemic exacerbated this strain and introduced several novel stressors, which included transitioning to remote work. Safe and scalable strategies are needed to help health care workers cope with these stressors. Aromatherapy may help address this need. Objectives: To assess the effect of 2 aromatherapy interventions (essential oil blends termed STILL and FOCUS) on perceived mental/psychological health parameters for academic department workers working from home during the COVID-19 pandemic. Methods: Participants were advised to use STILL for 5 days (Monday through Friday). After a 2-day washout period (Saturday and Sunday), participants were instructed to use FOCUS for 5 days (Monday through Friday). Participants completed a visual analog scale survey evaluating restlessness, fatigue, anxiety, stress, happiness, energy, relaxation, calmness, and well-being before and after each of the 2 intervention periods. Results: Twenty academic department remote workers participated in the study. Mental/psychological health surveys were completed by 6 participants before and after using STILL and by 10 before and after using FOCUS. Five participants answered all survey questions before and after both interventions. Although mean (SD) perceived stress scores improved after both the STILL (4.3 [2.3] vs 1.8 [1.7], P =.03) and FOCUS (2.9 [2.3] vs 1.5 [1.4], P =.02) interventions, this improvement was not statistically significant after Bonferroni correction (adjusted α =.006). Most participants (73.3%) reported that participating in the study was worthwhile, and 81.3% indicated that they would recommend aromatherapy to others. Conclusions: The STILL and FOCUS aromatherapy interventions did not significantly improve mental/psychological health parameters for remote academic department workers, although perceived stress was marginally improved and participants reported a perceived benefit from using aromatherapy. [ABSTRACT FROM AUTHOR]