The Virtual Team Member: Remote Engagement of Medical Students in COVID-19 Care.

Background: Medical education abruptly changed in the setting of the COVID-19 pandemic, impacting experiential learning in clinical clerkship as medical students were removed from direct patient interactions and care team participation. Re-configuring a hospital clinical rotation using virtual care platforms allowed students to re-engage in the clinical environment and actively participate in patient care. Methods: During the height of the pandemic, we implemented a 4-week "virtual team member" (VTM) inpatient medicine elective for medical students in their second year and above to participate in acute patient care during the height of the COVID-19 pandemic. Tasks included providing daily updates to patients and family members along and care coordination. Faculty experts in infectious disease, mental health, ethics, and patient safety incorporated weekly didactic video talks throughout the elective. Student feedback was obtained anonymously through pre-, mid-, and post-elective questionnaires. Results: A total of 26 students enrolled in the two 4-week blocks, with 85% in the 2nd year. Survey response rates for the pre, mid, and post-rotation questionnaires were 96%, 77%, 58% respectively. Of the 15 students who completed the post-survey, the majority strongly and somewhat agreed that the elective met expectations (12/15, 80%), was worthwhile (14/15, 93%) and met goals (12/15, 80%). Best parts of the elective most frequently cited by students were patient care and teamwork. Working remotely was the greatest challenge. Conclusions: Designing a virtual role for students successfully allowed students to re-engage in the acute care setting and connect with patients and participate in COVID-19 care. Supplementary Information: The online version contains supplementary material available at 10.1007/s40670-021-01422-8.

The association between immunosuppressants use and COVID-19 adverse outcomes: national COVID-19 cohort in South Korea.

BACKGROUND: There is uncertainty of the effect of immunosuppression, including corticosteroids, before COVID-19 infection on COVID-19 outcomes. The aim of this study was to investigate the relationship between prehospitalization immunosuppressants use (exposure) and COVID-19 patient outcomes. METHODS: We conducted a population-based retrospective cohort study using a nationwide healthcare claims database of South Korea as of May 15, 2020. Confirmed COVID-19 infection in hospitalized individuals aged 40 years or older were included for analysis. We defined exposure variable by using inpatient and outpatient prescription records of immunosuppressants from the database. Our primary endpoint was a composite endpoint of all-cause death, intensive care unit (ICU) admission, and mechanical ventilation use. Inverse probability of treatment weighting (IPTW)-adjusted logistic regression analyses were used, to estimate odds ratio (OR) and 95% confidence intervals (CI), comparing immunosuppressants users and non-users. RESULTS: We identified 4,349 patients, for which 1,356 were immunosuppressants users and 2,993 were non-users. Patients who used immunosuppressants were at increased odds of the primary endpoint of all-cause death, ICU admission and mechanical ventilation use (IPTW OR =1.32; 95% CI: 1.06-1.63), driven by higher odds of all-cause mortality (IPTW OR =1.63; 95% CI: 1.21-2.26). Patients who used corticosteroids (n=1,340) were at increased odds of the primary endpoint (IPTW OR =1.33; 95% CI: 1.07-1.64). CONCLUSIONS: Immunosuppressant use was associated with worse outcomes among COVID-19 patients. These findings support the latest guidelines from the CDC that people on immunosuppressants are at high risk of severe COVID-19 and that immunocompromised people may benefit from booster COVID-19 vaccinations.

The prognostic role of anticoagulants in COVID-19 patients: national COVID-19 cohort in South Korea.

BACKGROUND: There currently exists a paucity of data on whether pre-admission anticoagulants use may have benefits among COVID-19 patients by preventing COVID-19 associated thromboembolism. The aim of this study was to assess the association between pre-admission anticoagulants use and COVID-19 adverse outcomes. METHODS: We conducted a population-based cohort studying using the Health Insurance Review and Assessment Service (HIRA) claims data released by the South Korean government. Our study population consisted of South Koreans who were aged 40 years or older and hospitalized with COVID-19 between 1 January 2020 through 15 May 2020. We defined anticoagulants users as individuals with inpatient and outpatient prescription records in 120 days before cohort entry. Our primary endpoint was a composite of all-cause death, intensive care unit (ICU) admission, and mechanical ventilation use. Individual components of the primary endpoint were secondary endpoints. We compared the risk of endpoints between the anticoagulants users and non-users by logistic regression models, with the standardized mortality ratio weighting (SMRW) adjustment. RESULTS: In our cohort of 4,349 patients, for the primary endpoint of mortality, mechanical ventilation and ICU admission, no difference was noted between anticoagulants users and non-users (SMRW OR 1.11, 95% CI: 0.60-2.05). No differences were noted, among individual components. No effect modification was observed by age, sex, history of atrial fibrillation and thromboembolism, and history of cardiovascular disease. When applying the inverse probability of treatment weighting (IPTW) and SMRW with doubly robust methods in sensitivity analysis, anticoagulants use was associated with increased odds of the primary endpoint. CONCLUSIONS: Pre-admission anticoagulants were not determined to have a protective role against severe COVID-19 outcomes.

The association between statin and COVID-19 adverse outcomes: national COVID-19 cohort in South Korea.

BACKGROUND: There currently exist limited and conflicting clinical data on the use of statins in coronavirus disease 2019 (COVID-19) patients. The aim of this paper was to compare hospitalized patients with COVID-19 who did and did not receive statins. METHODS: We performed a population-based retrospective cohort study using South Korea's nationwide healthcare claim database. We identified consecutive patients hospitalized with COVID-19 and aged 40 years or older. Statin users were individuals with inpatient and outpatient prescription records of statins in the 240 days before cohort entry to capture patients who are chronic statin users and, therefore, receive statin prescriptions as infrequently as every 8 months. Our primary endpoint was a composite of all-cause death, intensive care unit (ICU) admission, mechanical ventilation use and cardiovascular outcomes [myocardial infarction (MI), transient cerebral ischemic attacks (TIA) or stroke]. We compared the risk of outcomes between statin users and non-users using logistic regression models after inverse probability of treatment weighting (IPTW) adjustment. RESULTS: Of 234,427 subjects in the database, 4,349 patients were hospitalized with COVID-19 and aged 40+ years. In total, 1,115 patients were statin users (mean age =65.9 years; 60% female), and 3,234 were non-users (mean age =58.3 years; 64% female). Pre-hospitalization statin use was not significantly associated with increased risk of the primary endpoint [IPTW odds ratio (OR) 0.82; 95% confidence interval (CI): 0.60-1.11]. Subgroup analysis showed a protective role of antecedent statin use for individuals with hypertension (IPTW OR 0.40; 95% CI: 0.23-0.69, P for interaction: 0.0087). CONCLUSIONS: Pre-hospitalization statin use is not detrimental and may be beneficial amongst hypertensive COVID-19 patients. Further investigation into statin is needed for more conclusive effects of statins for treatment of COVID-19.

Colchicine use in patients with COVID-19: A systematic review and meta-analysis.

INTRODUCTION: Colchicine may inhibit inflammasome signaling and reduce proinflammatory cytokines, a purported mechanism of COVID-19 pneumonia. The aim of this systematic review and meta-analysis is to report on the state of the current literature on the use of colchicine in COVID-19 and to investigate the reported clinical outcomes in COVID-19 patients by colchicine usage. METHODS: The literature was searched from January 2019 through January 28, 2021. References were screened to identify studies that reported the effect of colchicine usage on COVID-19 outcomes including mortality, intensive care unit (ICU) admissions, or mechanical ventilation. Studies were meta-analyzed for mortality by the subgroup of trial design (RCT vs observational) and ICU status. Studies reporting an risk ratio (RR), odds ratio (OR) and hazard ratio (HR) were analyzed separately. RESULTS: Eight studies, reporting on 16,248 patients, were included in this review. The Recovery trial reported equivalent mortality between colchicine and non-colchicine users. Across the other studies, patients who received colchicine had a lower risk of mortality-HR of 0.25 (95% CI: 0.09, 0.66) and OR of 0.22 (95% CI: 0.09, 0.57). There was no statistical difference in risk of ICU admissions between patients with COVID-19 who received colchicine and those who did not-OR of 0.26 (95% CI: 0.06, 1.09). CONCLUSION: Colchicine may reduce the risk of mortality in individuals with COVID-19. Further prospective investigation may further determine the efficacy of colchicine as treatment in COVID-19 patients in various care settings of the disease, including post-hospitalization and long-term care.

The protective association between statins use and adverse outcomes among COVID-19 patients: A systematic review and meta-analysis.

INTRODUCTION: Statins may reduce a cytokine storm, which has been hypothesized as a possible mechanism of severe COVID-19 pneumonia. The aim of this study was to conduct a systematic review and meta-analysis to report on adverse outcomes among COVID-19 patients by statin usage. METHODS: Literatures were searched from January 2019 to December 2020 to identify studies that reported the association between statin usage and adverse outcomes, including mortality, ICU admissions, and mechanical ventilation. Studies were meta-analyzed for mortality by the subgroups of ICU status and statin usage before and after COVID-19 hospitalization. Studies reporting an odds ratio (OR) and hazard ratio (HR) were analyzed separately. RESULTS: Thirteen cohorts, reporting on 110,078 patients, were included in this meta-analysis. Individuals who used statins before their COVID-19 hospitalization showed a similar risk of mortality, compared to those who did not use statins (HR 0.80, 95% CI: 0.50, 1.28; OR 0.62, 95% CI: 0.38, 1.03). Patients who were administered statins after their COVID-19 diagnosis were at a lower risk of mortality (HR 0.53, 95% CI: 0.46, 0.61; OR 0.57, 95% CI: 0.43, 0.75). The use of statins did not reduce the mortality of COVID-19 patients admitted to the ICU (OR 0.65; 95% CI: 0.26, 1.64). Among non-ICU patients, statin users were at a lower risk of mortality relative to non-statin users (HR 0.53, 95% CI: 0.46, 0.62; OR 0.64, 95% CI: 0.46, 0.88). CONCLUSION: Patients administered statins after COVID-19 diagnosis or non-ICU admitted patients were at lower risk of mortality relative to non-statin users.

A predictive model of clinical deterioration among hospitalized COVID-19 patients by harnessing hospital course trajectories.

From early March through mid-May 2020, the COVID-19 pandemic overwhelmed hospitals in New York City. In anticipation of ventilator shortages and limited ICU bed capacity, hospital operations prioritized the development of prognostic tools to predict clinical deterioration. However, early experience from frontline physicians observed that some patients developed unanticipated deterioration after having relatively stable periods, attesting to the uncertainty of clinical trajectories among hospitalized patients with COVID-19. Prediction tools that incorporate clinical variables at one time-point, usually on hospital presentation, are suboptimal for patients with dynamic changes and evolving clinical trajectories. Therefore, our study team developed a machine-learning algorithm to predict clinical deterioration among hospitalized COVID-19 patients by extracting clinically meaningful features from complex longitudinal laboratory and vital sign values during the early period of hospitalization with an emphasis on informative missing-ness. To incorporate the evolution of the disease and clinical practice over the course of the pandemic, we utilized a time-dependent cross-validation strategy for model development. Finally, we validated our prediction model on an external validation cohort of COVID-19 patients served in a demographically distinct population from the training cohort. The main finding of our study is the identification of risk profiles of early, late and no clinical deterioration during the course of hospitalization. While risk prediction models that include simple predictors at ED presentation and clinical judgement are able to identify any deterioration vs. no deterioration, our methodology is able to isolate a particular risk group that remain stable initially but deteriorate at a later stage of the course of hospitalization. We demonstrate the superior predictive performance with the utilization of laboratory and vital sign data during the early period of hospitalization compared to the utilization of data at presentation alone. Our results will allow efficient hospital resource allocation and will motivate research in understanding the late deterioration risk group.