Impact of SARS-CoV-2 vaccination and booster on COVID-19 symptom severity over time in the COVID-OUT trial.

BACKGROUND: SARS-CoV-2 vaccination has decreasing protection from acquiring any infection with emergence of new variants; however, vaccination continues to protect against progression to severe COVID-19. The impact of vaccination status on symptoms over time is less clear. METHODS: Within a randomized trial on early outpatient COVID-19 therapy testing metformin, ivermectin, and/or fluvoxamine, participants recorded symptoms daily for 14 days. Participants were given a paper symptom diary allowing them to circle the severity of 14 symptoms as none (0), mild (1), moderate (2), or severe (3). This is a secondary analysis of clinical trial data on symptom severity over time using generalized estimating equations comparing those unvaccinated, SARS-CoV-2 vaccinated with primary vaccine series only, or vaccine-boosted. RESULTS: The parent clinical trial prospectively enrolled 1323 participants, of whom 1062 (80%) prospectively recorded some daily symptom data. Of these, 480 (45%) were unvaccinated, 530 (50%) were vaccinated with primary series only, and 52 (5%) vaccine-boosted. Overall symptom severity was least for the vaccine-boosted group and most severe for unvaccinated at baseline and over the 14 days (P < 0.001). Individual symptoms were least severe in the vaccine-boosted group including: cough, chills, fever, nausea, fatigue, myalgia, headache, and diarrhea, as well as smell and taste abnormalities. Results were consistent over delta and omicron variant time periods. CONCLUSIONS: SARS-CoV-2 vaccine-boosted participants had the least severe symptoms during COVID-19 which abated the quickest over time.

Incorporating Paid Caregivers Into Medical Education to Enhance Medical Student Exposure to This Essential Workforce.

The implications of the COVID-19 pandemic underscored the utility of home-based health care due in part to social distancing requirements, curtailment of elective hospital procedures, and patient apprehension of the health care setting. The pandemic particularly accentuated the integral role of paid caregivers (eg, home health aides, personal care attendants, and other home care workers) in caring for patients with chronic health conditions. Given the paradigm shift toward community- and value-based health care models, paid caregivers are likely to play an even greater role as care team members. Despite the increasingly prominent role paid caregivers are assuming in health care, especially for patients who are chronically ill, in our experience as medical students, we have very little exposure to these care team members, with most interactions occurring in brief, chance encounters. Specifically, we advocate for increased medical student exposure to paid caregivers to facilitate their recognition as valuable care team members. We propose to achieve this through (1) classroom-based module learning with live paid caregivers and (2) plain language communication training to enhance reciprocal engagement.

Practical management of esophageal varices in the context of SARS-CoV-2 (COVID-19): the Alberta protocol

The challenges of managing varices during the COVID-19 pandemic are reviewed, and a treatment algorithm is presented to best manage patients with advanced liver disease during periods of limited access to endoscopy.

Randomized Trial of Metformin, Ivermectin, and Fluvoxamine for Covid-19.

BACKGROUND: Early treatment to prevent severe coronavirus disease 2019 (Covid-19) is an important component of the comprehensive response to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic. METHODS: In this phase 3, double-blind, randomized, placebo-controlled trial, we used a 2-by-3 factorial design to test the effectiveness of three repurposed drugs - metformin, ivermectin, and fluvoxamine - in preventing serious SARS-CoV-2 infection in nonhospitalized adults who had been enrolled within 3 days after a confirmed diagnosis of infection and less than 7 days after the onset of symptoms. The patients were between the ages of 30 and 85 years, and all had either overweight or obesity. The primary composite end point was hypoxemia (≤93% oxygen saturation on home oximetry), emergency department visit, hospitalization, or death. All analyses used controls who had undergone concurrent randomization and were adjusted for SARS-CoV-2 vaccination and receipt of other trial medications. RESULTS: A total of 1431 patients underwent randomization; of these patients, 1323 were included in the primary analysis. The median age of the patients was 46 years; 56% were female (6% of whom were pregnant), and 52% had been vaccinated. The adjusted odds ratio for a primary event was 0.84 (95% confidence interval [CI], 0.66 to 1.09; P = 0.19) with metformin, 1.05 (95% CI, 0.76 to 1.45; P = 0.78) with ivermectin, and 0.94 (95% CI, 0.66 to 1.36; P = 0.75) with fluvoxamine. In prespecified secondary analyses, the adjusted odds ratio for emergency department visit, hospitalization, or death was 0.58 (95% CI, 0.35 to 0.94) with metformin, 1.39 (95% CI, 0.72 to 2.69) with ivermectin, and 1.17 (95% CI, 0.57 to 2.40) with fluvoxamine. The adjusted odds ratio for hospitalization or death was 0.47 (95% CI, 0.20 to 1.11) with metformin, 0.73 (95% CI, 0.19 to 2.77) with ivermectin, and 1.11 (95% CI, 0.33 to 3.76) with fluvoxamine. CONCLUSIONS: None of the three medications that were evaluated prevented the occurrence of hypoxemia, an emergency department visit, hospitalization, or death associated with Covid-19. (Funded by the Parsemus Foundation and others; COVID-OUT ClinicalTrials.gov number, NCT04510194.).

Practical management of esophageal varices in the context of SARS-CoV-2 (COVID-19): the Alberta protocol.

The challenges of managing varices during the COVID-19 pandemic are reviewed, and a treatment algorithm is presented to best manage patients with advanced liver disease during periods of limited access to endoscopy.

Evaluation of Patients with Vaccine Allergies Prior to mRNA-Based COVID-19 Vaccination.

During the initial rollout of coronavirus disease 2019 (COVID-19) vaccination in Singapore, the Ministry of Health (MOH) issued a recommendation that patients with a history of any previous vaccine allergy be referred to an allergist for further review of their suitability to proceed with mRNA-based COVID-19 vaccines. Patients fulfilling the above criterion were divided into three groups: immediate reaction (Group A), delayed reaction (Group B) and no/irrelevant reaction (Group C). They were subjected to either a skin prick test (SPT) and intradermal test (IDT) with polyethylene glycol (PEG) or polysorbate-containing products; direct injection with the Pfizer BNT162b2 vaccine in the allergy clinic; or injection at community vaccination centres, respectively. Groups A and B were also invited to complete a questionnaire survey on post-vaccination reactions, and blood sampling pre-vaccination and 1 h after the first dose of the BNT162b2 vaccine to measure immunoglobulin (Ig) G, IgM and IgE antibodies to the Pfizer BNT162b2 vaccine via ELISA assays immobilised with the BNT162b2 vaccine, as well as levels of allergic cytokines interleukin (IL)-4 and IL-33, complement C5a and the endothelial activation marker intercellular adhesion molecule-1 (ICAM-1). Groups A and B comprised 62 (20.5%) patients each. In Group A, two subjects (3.2%) with equivocal IDT results tolerated both doses of the BNT162b2 vaccine without major allergic reactions. The remaining 60 (96.8%) in Group A and 62 (100%) in Group B completed both doses of BNT162b2 vaccination without major adverse reactions. Among the 99 who completed the questionnaire survey, 13 (13%) patients reported mild allergic reactions after the first dose of the vaccine. Immunoglobulin (Ig) G and M antibodies, but not IgE antibodies to the Pfizer BNT162b2 vaccine were detected in 67 subjects prior to vaccination. The presence of anti-Pfizer BNT162b2 IgG and IgM prior to vaccination did not result in major allergic reactions nor increases in Th2-related cytokines (IL-4, IL-33), complement activation products (C5a) or endothelial activation (ICAM-1). The majority of those with suspected reactions to non-COVID-19 polysorbate-containing vaccines tolerated the BNT162b2 vaccine. Excipient skin tests for PEG and polysorbate prior to vaccination are unnecessary.

ECHO+: Improving access to hepatitis C care within Indigenous communities in Alberta, Canada.

BACKGROUND: Indigenous populations experience higher rates of hepatitis C virus (HCV) infections in Canada. The Extension for Community Health Outcomes+ (ECHO+) telehealth model was implemented in Alberta to support HCV screening and treatment, using Zoom technology to support Indigenous patient access to specialist care closer to home. Our goal was to expand this program to more Indigenous communities in Alberta, using various Indigenous-led or co-designed methods. METHODS: The ECHO+ team implemented a Two-Eyed Seeing framework, incorporating Indigenous wholistic approaches alongside Western treatment. This approach works with principles of respect, reciprocity, and relationality. The ECHO+ team identified Indigenous-specific challenges, including access to liver specialist care, HCV awareness, stigma, barriers to screening and lack of culturally relevant approaches. RESULTS: Access to HCV care via this program significantly increased HCV antiviral use in the past 5 years. Key lessons learned include Indigenous-led relationship building and development of project outputs in response to community needs influences impact and increases relevant changes increasing access to HCV care. Implementation of ECHO+ was carried out through biweekly telehealth sessions, problem solving in partnership with Indigenous communities, increased HCV awareness, and flexibility resulting from the impacts of COVID-19. CONCLUSION: Improving Indigenous patient lives and reducing inequity requires supporting local primary health care providers to create and sustain integrated HCV prevention, diagnosis, treatment, and support services within a culturally safe and reciprocal model. ECHO+ uses telehealth and culturally appropriate methodology and interventions alongside multiple stakeholder collaborations to improve health outcomes for HCV.

Impact of the COVID-19 Pandemic on Hospitalizations for Alcoholic Hepatitis or Cirrhosis in Alberta, Canada.

BACKGROUND & AIMS: Coronavirus disease 2019 (COVID-19) pandemic lockdown and restrictions had significant disruption to patient care. We aimed to evaluate the impact of COVID-19 restrictions on hospitalizations of patients with alcoholic and nonalcoholic cirrhosis as well as alcoholic hepatitis (AH) in Alberta, Canada. METHODS: We used validated International Classification of Diseases (ICD-9 and ICD-10) coding algorithms to identify liver-related hospitalizations for nonalcoholic cirrhosis, alcoholic cirrhosis, and AH in the province of Alberta between March 2018 and September 2020. We used the provincial inpatient discharge and laboratory databases to identify our cohorts. We used elevated alanine aminotransferase or aspartate aminotransferase, elevated international normalized ratio, or bilirubin to identify AH patients. We compared COVID-19 restrictions (April-September 2020) with prior study periods. Joinpoint regression was used to evaluate the temporal trends among the 3 cohorts. RESULTS: We identified 2916 hospitalizations for nonalcoholic cirrhosis, 2318 hospitalizations for alcoholic cirrhosis, and 1408 AH hospitalizations during our study time. The in-hospital mortality rate was stable in relation to the pandemic for alcoholic cirrhosis and AH. However, nonalcoholic cirrhosis patients had lower in-hospital mortality rate after March 2020 (8.5% vs 11.5%; P = .033). There was a significant increase in average monthly admissions in the AH cohort (22.1/10,000 admissions during the pandemic vs 11.6/10,000 admissions before March 2020; P < .001). CONCLUSIONS: Before and during COVID-19 monthly admission rates were stable for nonalcoholic and alcoholic cirrhosis; however, there was a significant increase in AH admissions. Because alcohol sales surged during the pandemic, future impact on alcoholic liver disease could be detrimental.

Pseudo-Anaphylactic Reactions to Pfizer BNT162b2 Vaccine: Report of 3 Cases of Anaphylaxis Post Pfizer BNT162b2 Vaccination.

Anaphylactic reactions were observed after Singapore's national coronavirus disease 2019 (COVID-19) vaccination programme started in December 2020. We report the clinical and laboratory features of three patients in our institution who developed anaphylactic reactions after receiving the Pifzer BNT162b2 vaccine. IgM and IgG antibodies, but not IgE antibodies to the Pfizer BNT162b2 vaccine, were detected in all subjects. Similarly, mild to high elevated levels of anti-polyethylene glycol (PEG) IgG (1035-19709 U/mL, vs. vaccine-naive < 265 U/mL, vaccine-tolerant < 785 U/mL) and IgM (1682-5310 U/mL, vs. vaccine-naive < 1011 U/mL, vaccine-tolerant < 1007 U/mL) were detected in two out of three patients via commercial ELISA. High levels of serum anaphylatoxin C3a (79.0 ± 6.3 µg/mL, mean ± SD, vs. normal < 10 µg/mL) were observed in all three patients during the acute phase of the reaction, while tryptase levels, a marker of mast cell activation, were not elevated. Finally, one patient with the highest levels of anti-PEG IgG, IgM, and anti-Pfizer BNT162b2 IgG and IgM exhibited an enhanced Th2 cytokine serum profile during an acute reaction, with high levels of IL-4 (45.7 pg/mL, vs. vaccine-naive/tolerant < 2.30 pg/mL), IL-33 (86.4 pg/mL, vs. vaccine-naive/tolerant < 5.51 pg/mL) and IL-10 (22.9 pg/mL, vs. vaccine-naive/tolerant < 12.49 pg/mL) diminishing over time following corticosteroid treatment. Taken together, we propose these cases of anaphylaxis described are driven by a complement activation-related pseudoallergy (CAPRA), rather than classical IgE-mediated mechanisms.

Federated Learning of Electronic Health Records to Improve Mortality Prediction in Hospitalized Patients With COVID-19: Machine Learning Approach.

BACKGROUND: Machine learning models require large datasets that may be siloed across different health care institutions. Machine learning studies that focus on COVID-19 have been limited to single-hospital data, which limits model generalizability. OBJECTIVE: We aimed to use federated learning, a machine learning technique that avoids locally aggregating raw clinical data across multiple institutions, to predict mortality in hospitalized patients with COVID-19 within 7 days. METHODS: Patient data were collected from the electronic health records of 5 hospitals within the Mount Sinai Health System. Logistic regression with L1 regularization/least absolute shrinkage and selection operator (LASSO) and multilayer perceptron (MLP) models were trained by using local data at each site. We developed a pooled model with combined data from all 5 sites, and a federated model that only shared parameters with a central aggregator. RESULTS: The LASSOfederated model outperformed the LASSOlocal model at 3 hospitals, and the MLPfederated model performed better than the MLPlocal model at all 5 hospitals, as determined by the area under the receiver operating characteristic curve. The LASSOpooled model outperformed the LASSOfederated model at all hospitals, and the MLPfederated model outperformed the MLPpooled model at 2 hospitals. CONCLUSIONS: The federated learning of COVID-19 electronic health record data shows promise in developing robust predictive models without compromising patient privacy.

Elevated levels of IgA and IgG2 in individuals with chronic spinal cord injury.

OBJECTIVES: To determine circulating levels of antibodies (IgA, IgM, IgG1-4) in individuals with SCI as compared to uninjured individuals. STUDY DESIGN: Prospective, observational study. SETTING: Outpatient clinic of a Department of Physical Medicine and Rehabilitation and research institute in an academic medical center. PARTICIPANTS: Individuals with chronic (≥ 1 year from injury) SCI and uninjured individuals. OUTCOME MEASURES: Serum antibody titers were determined by commercial multiplex ELISA. RESULTS: Blood samples were collected from individuals with chronic SCI (N = 29, 83% males) and uninjured individuals (N = 25, 64% males). Among participants with SCI, the distribution of American Spinal Injury Association Impairment Scale (AIS) grades was: A (n = 15), B (n = 2), C (n = 4), D (n = 8). Neurological levels of injury were: cervical (n = 17), thoracic (n = 10), and lumbar (n = 2). IgA levels were significantly elevated in participants with SCI compared to uninjured participants (median: 1.98 vs. 1.21 mg/ml, P < 0.0001), with levels most elevated in individuals with motor complete injuries compared to uninjured participants (P < 0.0003). IgG2 antibodies were also significantly elevated in participants with SCI compared to uninjured participants (median: 5.98 vs. 4.37 mg/ml, P < 0.018). CONCLUSIONS: To our knowledge, this study provides the first evidence of elevated IgA, the antibody type most prevalent at respiratory, genitourinary and gastrointestinal tracts, common sites of infections in individuals with SCI. IgG2 levels were also elevated in individuals with SCI. These data support further investigations of IgA and other antibody types in individuals with chronic SCI, which may be increasingly important in the context of emerging novel infectious diseases such as SARS-CoV-2.

Machine Learning to Predict Mortality and Critical Events in a Cohort of Patients With COVID-19 in New York City: Model Development and Validation.

BACKGROUND: COVID-19 has infected millions of people worldwide and is responsible for several hundred thousand fatalities. The COVID-19 pandemic has necessitated thoughtful resource allocation and early identification of high-risk patients. However, effective methods to meet these needs are lacking. OBJECTIVE: The aims of this study were to analyze the electronic health records (EHRs) of patients who tested positive for COVID-19 and were admitted to hospitals in the Mount Sinai Health System in New York City; to develop machine learning models for making predictions about the hospital course of the patients over clinically meaningful time horizons based on patient characteristics at admission; and to assess the performance of these models at multiple hospitals and time points. METHODS: We used Extreme Gradient Boosting (XGBoost) and baseline comparator models to predict in-hospital mortality and critical events at time windows of 3, 5, 7, and 10 days from admission. Our study population included harmonized EHR data from five hospitals in New York City for 4098 COVID-19-positive patients admitted from March 15 to May 22, 2020. The models were first trained on patients from a single hospital (n=1514) before or on May 1, externally validated on patients from four other hospitals (n=2201) before or on May 1, and prospectively validated on all patients after May 1 (n=383). Finally, we established model interpretability to identify and rank variables that drive model predictions. RESULTS: Upon cross-validation, the XGBoost classifier outperformed baseline models, with an area under the receiver operating characteristic curve (AUC-ROC) for mortality of 0.89 at 3 days, 0.85 at 5 and 7 days, and 0.84 at 10 days. XGBoost also performed well for critical event prediction, with an AUC-ROC of 0.80 at 3 days, 0.79 at 5 days, 0.80 at 7 days, and 0.81 at 10 days. In external validation, XGBoost achieved an AUC-ROC of 0.88 at 3 days, 0.86 at 5 days, 0.86 at 7 days, and 0.84 at 10 days for mortality prediction. Similarly, the unimputed XGBoost model achieved an AUC-ROC of 0.78 at 3 days, 0.79 at 5 days, 0.80 at 7 days, and 0.81 at 10 days. Trends in performance on prospective validation sets were similar. At 7 days, acute kidney injury on admission, elevated LDH, tachypnea, and hyperglycemia were the strongest drivers of critical event prediction, while higher age, anion gap, and C-reactive protein were the strongest drivers of mortality prediction. CONCLUSIONS: We externally and prospectively trained and validated machine learning models for mortality and critical events for patients with COVID-19 at different time horizons. These models identified at-risk patients and uncovered underlying relationships that predicted outcomes.

Prognostic Impact of Prior Heart Failure in Patients Hospitalized With COVID-19.

BACKGROUND: Patients with pre-existing heart failure (HF) are likely at higher risk for adverse outcomes in coronavirus disease-2019 (COVID-19), but data on this population are sparse. OBJECTIVES: This study described the clinical profile and associated outcomes among patients with HF hospitalized with COVID-19. METHODS: This study conducted a retrospective analysis of 6,439 patients admitted for COVID-19 at 1 of 5 Mount Sinai Health System hospitals in New York City between February 27 and June 26, 2020. Clinical characteristics and outcomes (length of stay, need for intensive care unit, mechanical ventilation, and in-hospital mortality) were captured from electronic health records. For patients identified as having a history of HF by International Classification of Diseases-9th and/or 10th Revisions codes, manual chart abstraction informed etiology, functional class, and left ventricular ejection fraction (LVEF). RESULTS: Mean age was 63.5 years, and 45% were women. Compared with patients without HF, those with previous HF experienced longer length of stay (8 days vs. 6 days; p < 0.001), increased risk of mechanical ventilation (22.8% vs. 11.9%; adjusted odds ratio: 3.64; 95% confidence interval: 2.56 to 5.16; p < 0.001), and mortality (40.0% vs. 24.9%; adjusted odds ratio: 1.88; 95% confidence interval: 1.27 to 2.78; p = 0.002). Outcomes among patients with HF were similar, regardless of LVEF or renin-angiotensin-aldosterone inhibitor use. CONCLUSIONS: History of HF was associated with higher risk of mechanical ventilation and mortality among patients hospitalized for COVID-19, regardless of LVEF.