15 research outputs found

    Are fewer cases of diabetes mellitus diagnosed in the months after SARS-CoV-2 infection? A population-level view in the EHR-based RECOVER program

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    Long-term sequelae of severe acute respiratory coronavirus-2 (SARS-CoV-2) infection may include increased incidence of diabetes. Here we describe the temporal relationship between new type 2 diabetes and SARS-CoV-2 infection in a nationwide database. We found that while the proportion of newly diagnosed type 2 diabetes increased during the acute period of SARS-CoV-2 infection, the mean proportion of new diabetes cases in the 6 months post-infection was about 83% lower than the 6 months preinfection. These results underscore the need for further investigation to understand the timing of new diabetes after COVID-19, etiology, screening, and treatment strategies

    A method for comparing multiple imputation techniques: A case study on the U.S. national COVID cohort collaborative.

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    Healthcare datasets obtained from Electronic Health Records have proven to be extremely useful for assessing associations between patients’ predictors and outcomes of interest. However, these datasets often suffer from missing values in a high proportion of cases, whose removal may introduce severe bias. Several multiple imputation algorithms have been proposed to attempt to recover the missing information under an assumed missingness mechanism. Each algorithm presents strengths and weaknesses, and there is currently no consensus on which multiple imputation algorithm works best in a given scenario. Furthermore, the selection of each algorithm’s pa- rameters and data-related modeling choices are also both crucial and challenging

    Characterizing Long COVID: Deep Phenotype of a Complex Condition

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    BACKGROUND: Numerous publications describe the clinical manifestations of post-acute sequelae of SARS-CoV-2 (PASC or long COVID ), but they are difficult to integrate because of heterogeneous methods and the lack of a standard for denoting the many phenotypic manifestations. Patient-led studies are of particular importance for understanding the natural history of COVID-19, but integration is hampered because they often use different terms to describe the same symptom or condition. This significant disparity in patient versus clinical characterization motivated the proposed ontological approach to specifying manifestations, which will improve capture and integration of future long COVID studies. METHODS: The Human Phenotype Ontology (HPO) is a widely used standard for exchange and analysis of phenotypic abnormalities in human disease but has not yet been applied to the analysis of COVID-19. FINDINGS: We identified 303 articles published before April 29, 2021, curated 59 relevant manuscripts that described clinical manifestations in 81 cohorts three weeks or more following acute COVID-19, and mapped 287 unique clinical findings to HPO terms. We present layperson synonyms and definitions that can be used to link patient self-report questionnaires to standard medical terminology. Long COVID clinical manifestations are not assessed consistently across studies, and most manifestations have been reported with a wide range of synonyms by different authors. Across at least 10 cohorts, authors reported 31 unique clinical features corresponding to HPO terms; the most commonly reported feature was Fatigue (median 45.1%) and the least commonly reported was Nausea (median 3.9%), but the reported percentages varied widely between studies. INTERPRETATION: Translating long COVID manifestations into computable HPO terms will improve analysis, data capture, and classification of long COVID patients. If researchers, clinicians, and patients share a common language, then studies can be compared/pooled more effectively. Furthermore, mapping lay terminology to HPO will help patients assist clinicians and researchers in creating phenotypic characterizations that are computationally accessible, thereby improving the stratification, diagnosis, and treatment of long COVID. FUNDING: U24TR002306; UL1TR001439; P30AG024832; GBMF4552; R01HG010067; UL1TR002535; K23HL128909; UL1TR002389; K99GM145411

    Are fewer cases of diabetes mellitus diagnosed in the months after SARS-CoV-2 infection? A population-level view in the EHR-based RECOVER program

    Get PDF
    Long-term sequelae of severe acute respiratory coronavirus-2 (SARS-CoV-2) infection may include increased incidence of diabetes. Here we describe the temporal relationship between new type 2 diabetes and SARS-CoV-2 infection in a nationwide database. We found that while the proportion of newly diagnosed type 2 diabetes increased during the acute period of SARS-CoV-2 infection, the mean proportion of new diabetes cases in the 6 months post-infection was about 83% lower than the 6 months preinfection. These results underscore the need for further investigation to understand the timing of new diabetes after COVID-19, etiology, screening, and treatment strategies

    Characterizing Long COVID: Deep Phenotype of a Complex Condition.

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    BACKGROUND: Numerous publications describe the clinical manifestations of post-acute sequelae of SARS-CoV-2 (PASC or long COVID ), but they are difficult to integrate because of heterogeneous methods and the lack of a standard for denoting the many phenotypic manifestations. Patient-led studies are of particular importance for understanding the natural history of COVID-19, but integration is hampered because they often use different terms to describe the same symptom or condition. This significant disparity in patient versus clinical characterization motivated the proposed ontological approach to specifying manifestations, which will improve capture and integration of future long COVID studies. METHODS: The Human Phenotype Ontology (HPO) is a widely used standard for exchange and analysis of phenotypic abnormalities in human disease but has not yet been applied to the analysis of COVID-19. FINDINGS: We identified 303 articles published before April 29, 2021, curated 59 relevant manuscripts that described clinical manifestations in 81 cohorts three weeks or more following acute COVID-19, and mapped 287 unique clinical findings to HPO terms. We present layperson synonyms and definitions that can be used to link patient self-report questionnaires to standard medical terminology. Long COVID clinical manifestations are not assessed consistently across studies, and most manifestations have been reported with a wide range of synonyms by different authors. Across at least 10 cohorts, authors reported 31 unique clinical features corresponding to HPO terms; the most commonly reported feature was Fatigue (median 45.1%) and the least commonly reported was Nausea (median 3.9%), but the reported percentages varied widely between studies. INTERPRETATION: Translating long COVID manifestations into computable HPO terms will improve analysis, data capture, and classification of long COVID patients. If researchers, clinicians, and patients share a common language, then studies can be compared/pooled more effectively. Furthermore, mapping lay terminology to HPO will help patients assist clinicians and researchers in creating phenotypic characterizations that are computationally accessible, thereby improving the stratification, diagnosis, and treatment of long COVID. FUNDING: U24TR002306; UL1TR001439; P30AG024832; GBMF4552; R01HG010067; UL1TR002535; K23HL128909; UL1TR002389; K99GM145411

    Polysorbate 80 Inhibition of Pseudomonas aeruginosa Biofilm Formation and Its Cleavage by the Secreted Lipase LipAâ–¿

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    Surface-associated bacterial communities known as biofilms are an important source of nosocomial infections. Microorganisms such as Pseudomonas aeruginosa can colonize the abiotic surfaces of medical implants, leading to chronic infections that are difficult to eradicate. Our study demonstrates that polysorbate 80 (PS80), a surfactant commonly added to food and medicines, is able to inhibit biofilm formation by P. aeruginosa on a variety of surfaces, including contact lenses. Many clinical isolates of P. aeruginosa, as well as gram-negative and gram-positive clinical isolates, were also inhibited in their ability to form biofilms in the presence of PS80. A P. aeruginosa mutant able to form biofilms in the presence of this surfactant was identified and characterized, and it was revealed that this mutant overexpresses a lipase, LipA. Surfactants such as PS80 can be cleaved by lipases, and we demonstrate that PS80 is cleaved by LipA at its ester bond. Finally, polyethoxylated(20) oleyl alcohol, a chemical with a structure that is similar to that of PS80 but that lacks the ester bond of PS80, can inhibit the biofilm formation of P. aeruginosa strains, including the mutant overexpressing LipA. Our results demonstrate that surfactants such as PS80 can inhibit bacterial biofilm formation on medically relevant materials at concentrations demonstrated to be safe in humans and suggest that the understanding of the mechanisms of bacterial resistance to such surfactants will be important in developing clinically effective derivatives

    Anti-obesity medication prescriptions by race/ethnicity and use of an interpreter in a pediatric weight management clinic.

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    BackgroundRace/ethnicity and low English proficiency healthcare disparities are well established in the United States. We sought to determine if there are race/ethnicity differences in anti-obesity medication (AOM) prescription rates among youth with severe obesity treated in a pediatric weight management clinic and if, among youth from non-primary English speaking families, there are differences in prescriptions between those using interpreters during visits versus not.MethodsWe reviewed electronic health records of 2- to 18-year-olds with severe obesity seen from 2012 to 2021. Race/ethnicity was self-report, and AOMs included topiramate, stimulants (e.g. phentermine, lisdexamfetamine), naltrexone (±bupropion), glucagon-like peptide-1 agonists, and orlistat. We used general linear regression models with log-link to compare incidence rate ratios (IRRs) within the first 1 and 3 years of being followed, controlling for age, percent of the 95th BMI percentile (%BMIp95), number of obesity-related comorbidities (e.g. insulin resistance, hypertension), median household income, and interpreter use. We repeated similar analyses among youth from non-primary English speaking families, comparing those using interpreters versus not.Results1,725 youth (mean age 11.5 years; %BMIp95 142%; 53% non-Hispanic White, 20% Hispanic/Latino, 16% non-Hispanic black; 6% used interpreters) were seen, of which 15% were prescribed AOMs within 1 year. The IRR for prescriptions was lower among Hispanic/Latino compared to non-Hispanic White youth at one (IRR 0.70; CI: 0.49-1.00; p = 0.047) but not 3 years. No other statistically significant differences by race/ethnicity were found. Among non-primary English speaking families, the IRR for prescriptions was higher at 1 year (IRR 2.49; CI: 1.32-4.70; p = 0.005) in those using interpreters versus not.ConclusionsAmong youth seen in a pediatric weight management clinic, AOM prescription incidence rates were lower in Hispanics/Latinos compared to non-Hispanic Whites. Interpreter use was associated with higher prescription incidence rates among non-primary English speakers. Interventions to achieve equity in AOM prescriptions may help mitigate disparities in pediatric obesity

    Provider Advice and Patient Perceptions on Weight Across Five Health Systems.

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    INTRODUCTION: To improve the management of overweight and obesity in the primary care setting, an analysis of patient perceptions of weight status and predictors of weight loss attempts for those with overweight and obesity is needed. METHODS: Primary care patients (n=949) across 5 health systems in the Mid-Atlantic region of the U.S. were surveyed in 2015; data analysis was performed in 2018. Survey data was combined with data via the electronic health record to understand patients\u27 perceptions of weight, factors associated with weight loss efforts, and provider counseling practices. RESULTS: Most participants with overweight or obesity perceived themselves as weighing too much and reported trying to lose weight. Furthermore, most participants with obesity reported receiving advice to lose weight by a provider in the past 12 months. However, less than half of patients with overweight reported receiving advice to lose weight, maintain weight, or develop healthy eating and physical activity patterns from a health professional in the past 12 months. Among participants with overweight and obesity, multivariable logistic regression analysis demonstrated that the perception of being overweight and receiving healthcare advice to lose weight had the highest odds of reporting attempted weight loss (OR=5.5, 95% CI=2.7, 11.2 and OR=3.9, 95% CI=1.9, 7.9, respectively). CONCLUSIONS: The findings emphasize the importance of provider attention to weight management counseling and identifies patients with overweight as needing increased attention by providers

    Glycemic Control and Clinical Outcomes in U.S. Patients With COVID-19: Data From the National COVID Cohort Collaborative (N3C) Database

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    OBJECTIVE: The purpose of the study is to evaluate the relationship between HbA1c and severity of coronavirus disease 2019 (COVID-19) outcomes in patients with type 2 diabetes (T2D) with acute COVID-19 infection. RESEARCH DESIGN AND METHODS: We conducted a retrospective study using observational data from the National COVID Cohort Collaborative (N3C), a longitudinal, multicenter U.S. cohort of patients with COVID-19 infection. Patients were \u3e /=18 years old with T2D and confirmed COVID-19 infection by laboratory testing or diagnosis code. The primary outcome was 30-day mortality following the date of COVID-19 diagnosis. Secondary outcomes included need for invasive ventilation or extracorporeal membrane oxygenation (ECMO), hospitalization within 7 days before or 30 days after COVID-19 diagnosis, and length of stay (LOS) for patients who were hospitalized. RESULTS: The study included 39,616 patients (50.9% female, 55.4% White, 26.4% Black or African American, and 16.1% Hispanic or Latino, with mean +/- SD age 62.1 +/- 13.9 years and mean +/- SD HbA1c 7.6% +/- 2.0). There was an increasing risk of hospitalization with incrementally higher HbA1c levels, but risk of death plateaued at HbA1c \u3e 8%, and risk of invasive ventilation or ECMO plateaued \u3e9%. There was no significant difference in LOS across HbA1c levels. CONCLUSIONS: In a large, multicenter cohort of patients in the U.S. with T2D and COVID-19 infection, risk of hospitalization increased with incrementally higher HbA1c levels. Risk of death and invasive ventilation also increased but plateaued at different levels of glycemic control

    Diabetes medications and associations with Covid-19 outcomes in the N3C database: A national retrospective cohort study.

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    BackgroundWhile vaccination is the most important way to combat the SARS-CoV-2 pandemic, there may still be a need for early outpatient treatment that is safe, inexpensive, and currently widely available in parts of the world that do not have access to the vaccine. There are in-silico, in-vitro, and in-tissue data suggesting that metformin inhibits the viral life cycle, as well as observational data suggesting that metformin use before infection with SARS-CoV2 is associated with less severe COVID-19. Previous observational analyses from single-center cohorts have been limited by size.MethodsConducted a retrospective cohort analysis in adults with type 2 diabetes (T2DM) for associations between metformin use and COVID-19 outcomes with an active comparator design of prevalent users of therapeutically equivalent diabetes monotherapy: metformin versus dipeptidyl-peptidase-4-inhibitors (DPP4i) and sulfonylureas (SU). This took place in the National COVID Cohort Collaborative (N3C) longitudinal U.S. cohort of adults with +SARS-CoV-2 result between January 1 2020 to June 1 2021. Findings included hospitalization or ventilation or mortality from COVID-19. Back pain was assessed as a negative control outcome.Results6,626 adults with T2DM and +SARS-CoV-2 from 36 sites. Mean age was 60.7 +/- 12.0 years; 48.7% male; 56.7% White, 21.9% Black, 3.5% Asian, and 16.7% Latinx. Mean BMI was 34.1 +/- 7.8kg/m2. Overall 14.5% of the sample was hospitalized; 1.5% received mechanical ventilation; and 1.8% died. In adjusted outcomes, compared to DPP4i, metformin had non-significant associations with reduced need for ventilation (RR 0.68, 0.32-1.44), and mortality (RR 0.82, 0.41-1.64). Compared to SU, metformin was associated with a lower risk of ventilation (RR 0.5, 95% CI 0.28-0.98, p = 0.044) and mortality (RR 0.56, 95%CI 0.33-0.97, p = 0.037). There was no difference in unadjusted or adjusted results of the negative control.ConclusionsThere were clinically significant associations between metformin use and less severe COVID-19 compared to SU, but not compared to DPP4i. New-user studies and randomized trials are needed to assess early outpatient treatment and post-exposure prophylaxis with therapeutics that are safe in adults, children, pregnancy and available worldwide
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