Repurposing Metformin for Vascular Disease.

Metformin has seen use as an oral anti-hyperglycaemic drug since the late 1950s; however, following the release in 1998 of the findings of the 20-year United Kingdom Prospective Diabetes Study (UKPDS) metformin use rapidly increased and today is the first-choice anti-hyperglycaemic drug for patients with type 2 diabetes (T2D). Metformin is in daily use by an estimated 150 million people worldwide. Historically, the benefits of metformin as an anti-diabetic and cardiovascular-protective drug have been linked to effects in the liver, where it acts to inhibit gluconeogenesis and lipogenesis, as well as reducing insulin resistance and enhancing peripheral glucose utilization. However, direct protective effects on the endothelium and effects in the gut prior to metformin absorption are now recognized as being important. In the gut, metformin modulates the glucagon-like peptide-1 (GLP-1)- gut-brain axis as well as impacting the intestinal microbiota. As the apparent number of putative tissue and cellular targets for metformin has increased, so has interest in re-purposing metformin to treat other diseases that include polycystic ovary syndrome (PCOS), cancer, neurodegenerative diseases and COVID-19. Metformin is also being investigated as an anti-ageing drug. Of particular interest is whether metformin provides the same level of vascular protection in individuals other than those with T2D, including obese individuals with metabolic syndrome, or in the setting of vascular thromboinflammation caused by SARS-CoV-2. In this review we critically evaluate the literature to highlight clinical settings in which metformin might be therapeutically repurposed for the prevention and treatment of vascular disease.

Enabling accurate and early detection of recently emerged SARS-CoV-2 variants of concern in wastewater.

As clinical testing declines, wastewater monitoring can provide crucial surveillance on the emergence of SARS-CoV-2 variant of concerns (VoCs) in communities. In this paper we present QuaID, a novel bioinformatics tool for VoC detection based on quasi-unique mutations. The benefits of QuaID are three-fold: (i) provides up to 3-week earlier VoC detection, (ii) accurate VoC detection (>95% precision on simulated benchmarks), and (iii) leverages all mutational signatures (including insertions & deletions).

Effect of tele-COVID rounds and a tele-stewardship intervention on antibiotic use in COVID-19 patients admitted to 17 small community hospitals.

Antibiotic stewardship interventions are urgently needed to reduce antibiotic overuse in hospitalized COVID-19 patients, particularly in small community hospitals (SCHs), who often lack access to infectious diseases (ID) and stewardship resources. We implemented multidisciplinary tele-COVID rounds plus tele-antibiotic stewardship surveillance in 17 SCHs to standardize COVID management and evaluate concurrent antibiotics for discontinuation. Antibiotic use was compared in the 4 months preintervention versus 10 months postintervention. Interrupted time-series analysis demonstrated an immediate decrease in antibiotic use by 339 days of therapy/1000 COVID-19 patient days (p < .001), and an estimated 5258 antibiotic days avoided during the postintervention period. Thirty-day mortality was not significantly different, and a significant reduction in transfers was observed following the intervention (23.3% vs. 7.8%, p < .001). A novel tele-ID and tele-stewardship intervention significantly decreased antibiotic use and transfers among COVID-19 patients at 17 SCHs, demonstrating that telehealth is a feasible way to provide ID expertise in community and rural settings.

Understanding the role of COVID-19-related workplace stress and institutional betrayal on mental health in nurses: Some heroes wear scrubs.

This study examined the association of three specific COVID-19-related workplace stressors (percentage of nursing work with COVID-positive [COVID+] patients, number of COVID-19-related patient deaths witnessed, and living separately from family for safety) and their associations with posttraumatic stress symptoms (PTSS) and symptoms of major depressive disorder (MDD) and generalized anxiety disorder (GAD) among 391 nurses (93.6% White, 93.4% utilize she/her pronouns). Cross-sectional data were collected via an online survey. Institutional betrayal (i.e., the perception that an institution failed to protect a member who depends on and trusts it) was examined as a moderator of these associations. Although institutional betrayal was not a significant moderator in the three individual models, it held small-to-medium-sized positive main effects with PTSS and symptoms of GAD and MDD in both the individual and combined models. In the individual models, the percentage of nursing work with COVID+ patients was significantly positively associated with all three mental health conditions, f2 = .019-.195, whereas it only showed a significant effect with PTSS in the combined model, f2 = .138. Living separately from family was significantly positively associated with PTSS and MDD symptoms in both the individual, f2 = .037 and .015, respectively, and combined models, f2 = .025 and .013, respectively. Number of patient deaths held a significant positive association with PTSS alone, f2 = .022, in the individual model only. The findings are discussed in light of ways in which health care settings can better support and prioritize mental health among nursing staff.

Perceptions of burnout in medical dosimetry within a postpandemic work environment.

According to the World Health Organization, burnout is described as having a negative attitude regarding one's work and being exhausted. Previous studies have shown that occupational burnout exists amongst medical dosimetrists, however, the incidence of medical dosimetrist burnout before and after a pandemic warrant continued research. Medical dosimetrists could be experiencing increased burnout in the workplace postpandemic due to staffing shortages and increased remote planning, which may reduce work performance. The researchers utilized a survey to answer research questions regarding whether staffing shortages or remote planning influenced perceived occupational burnout among medical dosimetrists in a post COVID-19 pandemic environment. The survey was intended to assess levels of emotional exhaustion (EE), depersonalization (DP) and personal accomplishment (PA). It was distributed electronically to 2591 certified medical dosimetrists in the United States through the American Association of Medical Dosimetrists (AAMD) membership database. A total of 160 responses were recorded, resulting in a response rate of 6% (160/2591). The results of this study indicated that increased staffing shortages have a direct relationship with increased burnout incidence. Increased remote work appears to be inversely related to the incidence of burnout among medical dosimetrists.

Olivar: fully automated and variant aware primer design for multiplex tiled amplicon sequencing of pathogen genomes (preprint)

Tiled amplicon sequencing has served as an essential tool for tracking the spread and evolution of SARS-CoV-2 in real-time directly from environmental and clinical samples. Over 14 million SARS-CoV-2 genomes are now available on GISAID, most sequenced and assembled via tiled amplicon sequencing. While computational tools for tiled amplicon design exist, they require downstream manual optimization both computationally and experimentally, which is slow, laborious, and costly. Here, we present Olivar, the first open-source computational tool capable of fully automating the design of tiled amplicons by integrating SNPs, non-specific amplification, etc. into a "risk score" for each single nucleotide of the target genome. Oli- var evaluates thousands sets of possible tiled amplicons and minimizes primer dimer in parallel. In a direct in-silico com- parison with PrimalScheme, we show that Olivar has fewer SNPs overlapping with primers and predicted PCR byproducts. We also compared Olivar head-to-head with ARTIC v4.1, the most widely used tiled amplicons for SARS-CoV-2 sequencing. We next tested Olivar on real wastewater samples and found that our automated approach had up to 3-fold higher map- ping rates compared to ARTIC v4.1 while retaining similar coverage. To the best of our knowledge, Olivar represents the first open-source, fully automated design tool that simultaneously evaluates and optimizes risks of known primer design issues for robust tiled amplicon sequencing. Olivar is available as a web application at https://olivar.rice.edu/. Olivar can also be installed locally as a command line tool with Bioconda. Source code, installation guide and usage are available at https: //gitlab.com/treangenlab/olivar.

Evaluation of strategies to modify Anti-SARS-CoV-2 monoclonal antibodies for optimal functionality as therapeutics.

The current global COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has resulted in a public health crisis with more than 168 million cases reported globally and more than 4.5 million deaths at the time of writing. In addition to the direct impact of the disease, the economic impact has been significant as public health measures to contain or reduce the spread have led to country wide lockdowns resulting in near closure of many sectors of the economy. Antibodies are a principal determinant of the humoral immune response to COVID-19 infections and may have the potential to reduce disease and spread of the virus. The development of monoclonal antibodies (mAbs) represents a therapeutic option that can be produced at large quantity and high quality. In the present study, a mAb combination mixture therapy was investigated for its capability to specifically neutralize SARS-CoV-2. We demonstrate that each of the antibodies bind the spike protein and neutralize the virus, preventing it from infecting cells in an in vitro cell-based assay, including multiple viral variants that are currently circulating in the human population. In addition, we investigated the effects of two different mutations in the Fc portion (YTE and LALA) of the antibody on Fc effector function and the ability to alleviate potential antibody-dependent enhancement of disease. These data demonstrate the potential of a combination of two mAbs that target two different epitopes on the SARS-CoV2 spike protein to provide protection against SARS-CoV-2 infection in humans while extending serum half-life and preventing antibody-dependent enhancement of disease.

Prognostic models for COVID-19 needed updating to warrant transportability over time and space.

BACKGROUND: Supporting decisions for patients who present to the emergency department (ED) with COVID-19 requires accurate prognostication. We aimed to evaluate prognostic models for predicting outcomes in hospitalized patients with COVID-19, in different locations and across time. METHODS: We included patients who presented to the ED with suspected COVID-19 and were admitted to 12 hospitals in the New York City (NYC) area and 4 large Dutch hospitals. We used second-wave patients who presented between September and December 2020 (2137 and 3252 in NYC and the Netherlands, respectively) to evaluate models that were developed on first-wave patients who presented between March and August 2020 (12,163 and 5831). We evaluated two prognostic models for in-hospital death: The Northwell COVID-19 Survival (NOCOS) model was developed on NYC data and the COVID Outcome Prediction in the Emergency Department (COPE) model was developed on Dutch data. These models were validated on subsequent second-wave data at the same site (temporal validation) and at the other site (geographic validation). We assessed model performance by the Area Under the receiver operating characteristic Curve (AUC), by the E-statistic, and by net benefit. RESULTS: Twenty-eight-day mortality was considerably higher in the NYC first-wave data (21.0%), compared to the second-wave (10.1%) and the Dutch data (first wave 10.8%; second wave 10.0%). COPE discriminated well at temporal validation (AUC 0.82), with excellent calibration (E-statistic 0.8%). At geographic validation, discrimination was satisfactory (AUC 0.78), but with moderate over-prediction of mortality risk, particularly in higher-risk patients (E-statistic 2.9%). While discrimination was adequate when NOCOS was tested on second-wave NYC data (AUC 0.77), NOCOS systematically overestimated the mortality risk (E-statistic 5.1%). Discrimination in the Dutch data was good (AUC 0.81), but with over-prediction of risk, particularly in lower-risk patients (E-statistic 4.0%). Recalibration of COPE and NOCOS led to limited net benefit improvement in Dutch data, but to substantial net benefit improvement in NYC data. CONCLUSIONS: NOCOS performed moderately worse than COPE, probably reflecting unique aspects of the early pandemic in NYC. Frequent updating of prognostic models is likely to be required for transportability over time and space during a dynamic pandemic.

Development and validation of self-monitoring auto-updating prognostic models of survival for hospitalized COVID-19 patients.

Clinical prognostic models can assist patient care decisions. However, their performance can drift over time and location, necessitating model monitoring and updating. Despite rapid and significant changes during the pandemic, prognostic models for COVID-19 patients do not currently account for these drifts. We develop a framework for continuously monitoring and updating prognostic models and apply it to predict 28-day survival in COVID-19 patients. We use demographic, laboratory, and clinical data from electronic health records of 34912 hospitalized COVID-19 patients from March 2020 until May 2022 and compare three modeling methods. Model calibration performance drift is immediately detected with minor fluctuations in discrimination. The overall calibration on the prospective validation cohort is significantly improved when comparing the dynamically updated models against their static counterparts. Our findings suggest that, using this framework, models remain accurate and well-calibrated across various waves, variants, race and sex and yield positive net-benefits.

High Frequency of COVID-19 Vaccine Hesitancy among Canadians Immunized for Influenza: A Cross-Sectional Survey.

We assessed the frequency and correlates of COVID-19 vaccine hesitancy before Canada's vaccine rollout. A cross-sectional vaccine hesitancy survey was completed by consecutive patients/family members/staff who received the influenza vaccine at McGill University affiliated hospitals. Based on the self-reported likelihood of receiving a future vaccine (scale 0-10), the following three groups were defined: non-hesitant (score 10), mildly hesitant (7.1-9.9), and significantly hesitant (0-7). Factors associated with vaccine hesitancy were assessed with multivariate logistic regression analyses and binomial logistic regression machine learning modelling. The survey was completed by 1793 people. Thirty-seven percent of participants (n = 669) were hesitant (mildly: 315 (17.6%); significantly: 354 (19.7%)). Lower education levels, opposition and uncertainty about vaccines being mandatory, feelings of not receiving enough information about COVID-19 prevention, perceived social pressure to get a future vaccine, vaccine safety concerns, uncertainty regarding the vaccine risk-benefit ratio, and distrust towards pharmaceutical companies were factors associated with vaccine hesitancy. Vaccine safety concerns and opposition to mandatory vaccinations were the strongest correlates of vaccine hesitancy in both the logistic regressions and the machine learning model. In conclusion, in this study, over a third of people immunized for influenza before the COVID-19 vaccine rollout expressed some degree of vaccine hesitancy. Effectively addressing COVID-19 vaccine safety concerns may enhance vaccine uptake.

At-home ECG monitoring with a real-time outpatient cardiac telemetry system during the COVID-19 pandemic.

CONTEXT: During the COVID-19 pandemic, essential in-person electrocardiogram (ECG) recordings became unfeasible, while patients continued to suffer from cardiac conditions. To circumvent these challenges, the cardiology clinic (Long Island Heart Rhythm Center [LIHRC]) at the New York Institute of Technology College of Osteopathic Medicine (NYITCOM) transitioned to a remote real-time outpatient cardiac telemetry (ROCT) service. OBJECTIVES: The goal of this study is to test the hypothesis that at-home ROCT, provided by the LIHRC, is an effective method of providing ECG monitoring to symptomatic patients during the COVID-19 pandemic. METHODS: Seventeen patients at the LIHRC that required ECGs between March 11 and August 1, 2020, were included in this study. The patients' medical records were de-identified and reviewed for age, gender, ROCT indications, findings, patient comfort, and ease of use. A retrospective analysis of observational de-identified data obtained from the LIHRC was approved and permitted by the NYITCOM Institutional Review Board (BHS-1465). These FDA-cleared medical devices (DMS-300, DM Software, Stateline, NV) were shipped to the patients' homes and were self-applied through adhesive chest patches. The devices communicated with a cloud-based system that produced reports including a continuous 6-lead ECG and many other cardiovascular parameters. Additionally, a patient-activated symptom recorder was available to correlate symptoms to ECG findings. RESULTS: Seventeen patients (15 women) from the LIHRC were included in the analysis with an average monitoring duration of 27 h (range, 24-72 h). The patients' ages ranged from 21 to 85 years old with a mean of 37 years old and a standard deviation of 19. ROCT indications included palpitations (n=9), presyncope (n=8), chest pain (n=5), syncope (n=3), and shortness of breath (n=2). One also received ROCT due to short PR intervals observed on a prepandemic ECG. Two patients experienced palpitations while wearing the ROCT device: one had supraventricular tachycardia at 150 beats per minute; the other had unifocal premature ventricular contractions (PVCs) and eventually underwent a successful cardiac ablation. Most patients experienced no symptomatic episodes during ROCT (n=15). The 6-lead ROCT ECG for five of those patients showed arrhythmias including wandering atrial pacemaker (n=2), PVCs (n=2), sinus tachycardia (n=1), premature atrial contractions (PACs) (n=1), ectopic atrial rhythms (n=1), and sinus arrhythmia (n=1). One patient who experienced issues with our device was able to obtain a device from a separate clinic and was found to have bradycardia, PVCs, and nonsustained ventricular tachycardia. Overall, 16/17 (94.1%) patients were monitored effectively with the LIHRC ROCT system, and all (17/17, 100%) patients were monitored effectively with a ROCT system either from the LIHRC or a separate clinic. CONCLUSIONS: With the unique challenges of the COVID-19 pandemic, physicians can use this innovative ROCT method to prevent infection and diagnose cardiac diseases. Most patients and staff were able to utilize the system without issues. Therefore, this system may also be utilized to deliver patient-centered care to those with limited mobility when coupled with a telemedicine visit.

IMPROVING COMMUNICATION AT NHS NIGHTINGALE HOSPITAL NORTHWEST: MEDICAL UPDATES TO NEXTOF- KIN

The Nightingale Northwest (NNW) is a UK temporary field hospital set up to provide extra capacity during the COVID- 19 pandemic. Policies and standard operating procedures were undeveloped. Visitors were permitted only in exceptional circumstances, resulting in heightened anxiety for patients, and their family/carers. Recognising the crucial importance of effective communication at this time, we led a quality improvement project aiming to improve telephone communication between the medical team and next of kin (NOK). NOK satisfaction with communication received from doctors (rating 1-5, plus qualitative feedback) was the primary outcome measure and was surveyed through standardised phone-calls. We identified a wide, four point (1-5) variability in satisfaction. Less satisfied NOK predominantly reported reduced frequency of medical communication. We used PDSA methodology and introduced three interventions: 1) 'Gold standard' for frequency of routine medical updates;2) Record date of most recent NOK update on the doctors' list;3) Disseminate a light-hearted informative video of the 'gold standard' to increase awareness and motivation. Early post-intervention data showed reduced variability in satisfaction, with levels consistently reported as 4 or 5 towards the end of data collection. Process measures demonstrated excellent uptake of interventions with 81.3% adherence to the 'gold standard' and 95.7% compliance to accurately updating the doctors' list. Early data indicates a promising tool for improving doctor- NOK communication primarily by prompting doctors to update NOK more regularly. Our timeline was very limited but the excellent uptake of interventions suggests a potential for sustainable improvement. The lack of defined protocols and openness to rapid change at the NNW encouraged us as junior doctors to take the initiative and lead quality improvement work.

Mitigation of SARS-CoV-2 transmission at a large public university.

In Fall 2020, universities saw extensive transmission of SARS-CoV-2 among their populations, threatening health of the university and surrounding communities, and viability of in-person instruction. Here we report a case study at the University of Illinois at Urbana-Champaign, where a multimodal "SHIELD: Target, Test, and Tell" program, with other non-pharmaceutical interventions, was employed to keep classrooms and laboratories open. The program included epidemiological modeling and surveillance, fast/frequent testing using a novel low-cost and scalable saliva-based RT-qPCR assay for SARS-CoV-2 that bypasses RNA extraction, called covidSHIELD, and digital tools for communication and compliance. In Fall 2020, we performed >1,000,000 covidSHIELD tests, positivity rates remained low, we had zero COVID-19-related hospitalizations or deaths amongst our university community, and mortality in the surrounding Champaign County was reduced more than 4-fold relative to expected. This case study shows that fast/frequent testing and other interventions mitigated transmission of SARS-CoV-2 at a large public university.

Health care access among self-employed workers in nonmetropolitan counties

Access to health care involves affordability, which is often tied to health insurance coverage, as well as availability of health care facilities and providers. Self-employed workers are less likely to have access to employer-sponsored health insurance plans, and rural areas may have fewer options for local health care. Through the lens of availability and affordability, this report studies health care access for self-employed individuals, their families, and their households in nonmetropolitan (nonmetro) counties, using data collected between 2014 and 2020. The results indicate that health insurance coverage rates and sources differ more by age and whether workers are self-employed than by whether they live in a metro or nonmetro location. Self-employed workers ages 26 to 64 are more likely to be uninsured than those employed by government or private industry, but more of these working-age adults are insured through employer-based plans than any other insurance source. Few self-employed workers over age 65 are uninsured, and more of them are insured by public plans than any other source of insurance. Family medical expenditures differ more by age and source of health insurance coverage than by whether a family member is self-employed or lives in a metro or nonmetro location. The availability of health care facilities and services varies among U.S. counties by region, metro status, and whether a large share of workers are self-employed. Uninsured rates were higher for all workers at the beginning of the Coronavirus (COVID-19) pandemic in April and May of 2020 than in 2018 and continued to increase through the pandemic in 2020, mainly due to a decline in coverage from employer-sponsored plans.

SeqScreen: accurate and sensitive functional screening of pathogenic sequences via ensemble learning.

The COVID-19 pandemic has emphasized the importance of accurate detection of known and emerging pathogens. However, robust characterization of pathogenic sequences remains an open challenge. To address this need we developed SeqScreen, which accurately characterizes short nucleotide sequences using taxonomic and functional labels and a customized set of curated Functions of Sequences of Concern (FunSoCs) specific to microbial pathogenesis. We show our ensemble machine learning model can label protein-coding sequences with FunSoCs with high recall and precision. SeqScreen is a step towards a novel paradigm of functionally informed synthetic DNA screening and pathogen characterization, available for download at www.gitlab.com/treangenlab/seqscreen .

Categorizing Sequences of Concern by Function To Better Assess Mechanisms of Microbial Pathogenesis.

To identify sequences with a role in microbial pathogenesis, we assessed the adequacy of their annotation by existing controlled vocabularies and sequence databases. Our goal was to regularize descriptions of microbial pathogenesis for improved integration with bioinformatic applications. Here, we review the challenges of annotating sequences for pathogenic activity. We relate the categorization of more than 2,750 sequences of pathogenic microbes through a controlled vocabulary called Functions of Sequences of Concern (FunSoCs). These allow for an ease of description by both humans and machines. We provide a subset of 220 fully annotated sequences in the supplemental material as examples. The use of this compact (∼30 terms), controlled vocabulary has potential benefits for research in microbial genomics, public health, biosecurity, biosurveillance, and the characterization of new and emerging pathogens.

The Impact of COVID-19 Related Social Distancing on Mental Health Outcomes: A Transdiagnostic Account.

The COVID-19 pandemic, and the social distancing practices that followed, have been associated with increased prevalence of emotional disorders. However, not all individuals affected by COVID-19-related social distancing experienced elevations in emotional disorder symptoms. Understanding this phenomenon is of crucial public health significance given the burden of emotional disorders on individuals and systems. In this narrative review, we consider the differential impact of COVID-19-related social distancing on mental health outcomes from a transdiagnostic perspective. We argue that individuals high in negative affect and aversive reactivity to emotion, that is, neuroticism, and who respond to such emotional experiences with emotion-motivated avoidant coping, are most likely to experience emotional disorders in the context of COVID-19 social distancing. We acknowledge the pro-social and adaptive function of some types of avoidance during the pandemic, which may have initially buffered against negative mental health outcomes. Implications of this conceptualization for treatment of emotional disorders in the present sociocultural context are discussed.

Use of a Viral Filter to Reduce Exposure to Exhaled Aerosol Does Not Affect Methacholine Dose Delivery During Bronchoprovocation Testing.

BACKGROUND: Methacholine challenge testing (MCT) is a common bronchoprovocation technique used to assess airway hyper-responsiveness. We previously demonstrated that the addition of a viral filter to the nebulizer exhalation limb substantially reduced expelled particles during MCT. Our aim was to evaluate whether this modification affects the delivered dose of methacholine. METHODS: A mechanical ventilator was connected to a lung simulator with breathing frequency 15 breaths/min, tidal volume 500 mL, inspiratory-expiratory ratio 1:1, with a sinusoidal waveform. We compared methacholine dose delivery using the Hudson Micro Mist or AeroEclipse II BAN nebulizers powered by either a dry gas source or a compressor system. A filter placed in line between the nebulizer and test lung was weighed before and after 1 min of nebulized methacholine delivery. Mean inhaled mass was measured with and without a viral filter on the exhalation limb. Dose delivery was calculated by multiplying the mean inhaled mass by the respirable fraction (particles < 5 µm) and inhalation time. Unpaired t test was used to compare methacholine dose delivery with and without viral filter placement. RESULTS: The addition of a viral filter did not significantly affect methacholine dose delivery across all devices tested. Using a 50-psi dry gas source, dose delivered with or without a viral filter did not differ with the Hudson (422.3 µg vs 282.0 µg, P = .11) or the AeroEclipse nebulizer (563.0 µg vs 657.6 µg, P = .59). Using the compressor, dose delivered with and without a viral filter did not differ with the Hudson (974.0 µg vs 868.0 µg, P = .03) or the AeroEclipse nebulizer (818.0 µg vs 628.5 µg, P = .42). CONCLUSIONS: The addition of a viral filter to the nebulizer exhalation limb did not affect methacholine dose during bronchoprovocation testing. Routine use of a viral filter should be considered to improve pulmonary function technician safety and infection control measures during the ongoing COVID-19 pandemic.