Does COVID-19 Infection Increase the Risk of Diabetes? Current Evidence.

PURPOSE OF REVIEW: Multiple studies report an increased incidence of diabetes following SARS-CoV-2 infection. Given the potential increased global burden of diabetes, understanding the effect of SARS-CoV-2 in the epidemiology of diabetes is important. Our aim was to review the evidence pertaining to the risk of incident diabetes after COVID-19 infection. RECENT FINDINGS: Incident diabetes risk increased by approximately 60% compared to patients without SARS-CoV-2 infection. Risk also increased compared to non-COVID-19 respiratory infections, suggesting SARS-CoV-2-mediated mechanisms rather than general morbidity after respiratory illness. Evidence is mixed regarding the association between SARS-CoV-2 infection and T1D. SARS-CoV-2 infection is associated with an elevated risk of T2D, but it is unclear whether the incident diabetes is persistent over time or differs in severity over time. SARS-CoV-2 infection is associated with an increased risk of incident diabetes. Future studies should evaluate vaccination, viral variant, and patient- and treatment-related factors that influence risk.

Data Science Implementation Trends in Nursing Practice: A Review of the 2021 Literature.

OBJECTIVES: The goal of this work was to provide a review of the implementation of data science driven applications focused on structural or outcome-related nurse sensitive indicators in the literature in 2021. By conducting this review, we aim to inform readers of on trends in the nursing indicators being addressed, the patient populations and settings of focus, and lessons and challenges identified during the implementation of these tools. METHODS: We conducted a rigorous descriptive review of the literature to identify relevant research published in 2021. We extracted data on model development, implementation-related; lessons learned and challenges and stakeholder involvement. We also assessed whether reports of data science application implementations currently follow the guidelines of the Developmental and Exploratory Clinical Investigations of DEcision support systems driven by AI (DECIDE-AI) framework. RESULTS: Of 4,943 articles found in PubMed (NLM) and CINAHL (EBSCOhost), 11 were included in the final review and data extraction. Systems leveraging data science were developed for adult patient populations and were primarily deployed in hospital settings. The clinical domains targeted included mortality/deterioration, utilization/resource allocation and hospital acquired infections/COVID-19. The composition of development teams and types of stakeholders involved varied. Research teams more frequently reported on implementation methods than implementation results. Most studies provided lessons learned that could help inform future implementations of data science systems in healthcare. CONCLUSIONS: In 2021, very few studies report on the implementation of data science driven applications focused on structural- or outcome-related nurse sensitive indicators. This gap in the sharing of implementation strategies needs to be addressed in order for these systems to be successfully adopted in health care settings.

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.

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.

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 parameters and data-related modeling choices are also both crucial and challenging. In this paper we propose a novel framework to numerically evaluate strategies for handling missing data in the context of statistical analysis, with a particular focus on multiple imputation techniques. We demonstrate the feasibility of our approach on a large cohort of type-2 diabetes patients provided by the National COVID Cohort Collaborative (N3C) Enclave, where we explored the influence of various patient characteristics on outcomes related to COVID-19. Our analysis included classic multiple imputation techniques as well as simple complete-case Inverse Probability Weighted models. Extensive experiments show that our approach can effectively highlight the most promising and performant missing-data handling strategy for our case study. Moreover, our methodology allowed a better understanding of the behavior of the different models and of how it changed as we modified their parameters. Our method is general and can be applied to different research fields and on datasets containing heterogeneous types.

Severe COVID-19 outcomes in pediatrics: An observational cohort analysis comparing Alpha, Delta, and Omicron variants.

Objective: COVID-19 can rarely lead to severe illness in pediatric patients. The aim of this study was to determine if severe outcomes in pediatric COVID-19 have changed over the course of the pandemic. Methods: This was a multicenter, observational cohort analysis from a large regional healthcare system in metro Detroit using electronic health record data to evaluate emergency visits, hospitalization, and severe COVID-19 disease in pediatric patients. Consecutive pediatric patients presenting to the emergency department with a primary diagnosis of COVID-19 were included. Outcomes data was gathered from three distinct time intervals that coincided with Alpha, Delta, and Omicron variant predominance (Time interval 1 (T1) 1/1/2021-6/30/2021: Alpha, T2 7/1/2021-12/31/2021: Delta, T3 1/1/2022-6/16/2022): Omicron. The primary outcome was severe disease inclusive of composite intensive care unit admission, mechanical ventilation, multisystem inflammatory syndrome in children (MIS-C), myocarditis, or death. Secondary outcomes included severe outcomes considering viral coinfection and vaccination status. Results: Between 1/1/2021 and 6/16/2022, there were 4517 emergency COVID-19 visits, of which 12.5% (566) of children were hospitalized. 24.4% (138), 31.6% (179), and 44.0% (249) of admissions occurred during T1, T2 and T3 respectively. Most patients were male (55.1%) and 59.9% identified as Caucasian. The median age was 5.0 (interquartile range 1.0, 13.0) with infants comprising 22.8% (129), toddlers 25.1% (142), children 23.0% (130), and teenagers 29.2% (165). Over the course of the pandemic, the proportion of infants in hospitalization increased from 16.7% in T1 to 19.6% in T2 to 28.5% in T3 (p < 0.01) while the proportion of teenagers in hospitalization decreased from 39.1% in T1 to 31.3% in T2 to 22.1% in T3 (p < 0.001). Oxygen therapy was required in a minority (29.9%) of cases with supplemental oxygen utilized the least in T3 (16.5%) and most in T2 (30.2%). Composite severe disease decreased throughout the pandemic occurring in 36.2% in T1, 27.4% in T2, and 18.9% in T3. A multivariable logistic regression analysis revealed the odds of composite severe disease was significantly lower in T3 compared to T1 (adjusted odds ratio [aOR] 0.35, 95% Confidence Interval 0.21-0.60, p < 0.001). Fully vaccinated or fully vaccinated and boosted admission rates remained low throughout all periods with 4.4% in T1, 4.5% in T2 and 8.4% in T3. Viral coinfection was most common during T2 (16.8%) followed by T3 (12.5%) and least common in T1 (5.1%) (p = 0.006). Coinfection occurred more commonly in younger children with a median age of 1.2 (0.0, 4.5) compared to those with mono-infection with a median age of 6 (1.0, 14.0) (p < 0.001). Severe outcomes occurred in 45.6% of coinfection cases compared to 22.1% without coinfection (p < 0.001). Conclusions: While Omicron cases had the highest admission frequency, severe illness was lower than Delta and Alpha variants. Coinfection with respiratory viruses increased the risk of severe outcomes and impacted infants more than older children. Funding: None.

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

BACKGROUND: While 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. METHODS: Conducted 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. RESULTS: 6,626 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. CONCLUSIONS: There 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.

Examining D-dimer and Empiric Anti-coagulation in COVID-19-Related Thrombosis.

Objective Thrombosis is thought to occur frequently in the setting of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. We aimed to elucidate the relationship between macro/microvascular thrombosis, D-dimer levels, and empiric anticoagulation in coronavirus disease 2019 (COVID-19). Methods This was an exploratory prospective, single-site, observational study. Adult emergency department patients with COVID-19 requiring hospitalization received a point-of-care lower extremity venous duplex ultrasound. The primary endpoint was thromboembolism and associated D-dimer level. Secondary endpoints included rates of micro and macro thrombotic complications as well as empiric anticoagulant use. Results Between January 13th and April 12th 2021, 52 patients were enrolled. Median D-dimer at presentation was 650 ng/mL (range 250-10,000 ng/mL) among patients with negative duplex studies. During hospitalization, 18 patients underwent 20 additional studies assessing for venous thromboembolism (VTE). These studies yielded one deep vein thrombosis (DVT) diagnosis. Among patients with negative studies median D-dimer was 1,246 ng/mL (range 329-10,000 ng/mL). Two patients experienced microvascular complications. Seven patients were started on empiric full dose anticoagulation. Conclusion While VTE remains a major concern amongst patients with COVID-19, the normal D-dimer cut off of >500 ng/mL likely should not be used to initiate further VTE workup. Additionally, moderately elevated D-dimer did not correlate strongly with microvascular complications and may not be relevant in the decision to initiate empiric anticoagulation.

Effect of SARS-CoV-2 Infection and Infection Severity on Longer-Term Glycemic Control and Weight in People With Type 2 Diabetes.

OBJECTIVE: To evaluate the association of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and severity of infection with longer-term glycemic control and weight in people with type 2 diabetes (T2D) in the U.S. RESEARCH DESIGN AND METHODS: We conducted a retrospective cohort study using longitudinal electronic health record data of patients with SARS-CoV-2 infection from the National COVID Cohort Collaborative (N3C). Patients were ≥18 years old with an ICD-10 diagnosis of T2D and at least one HbA1c and weight measurement prior to and after an index date of their first coronavirus disease 2019 (COVID-19) diagnosis or negative SARS-CoV-2 test. We used propensity scores to identify a matched cohort balanced on demographic characteristics, comorbidities, and medications used to treat diabetes. The primary outcome was the postindex average HbA1c and postindex average weight over a 1 year time period beginning 90 days after the index date among patients who did and did not have SARS-CoV-2 infection. Secondary outcomes were postindex average HbA1c and weight in patients who required hospitalization or mechanical ventilation. RESULTS: There was no significant difference in the postindex average HbA1c or weight in patients who had SARS-CoV-2 infection compared with control subjects. Mechanical ventilation was associated with a decrease in average HbA1c after COVID-19. CONCLUSIONS: In a multicenter cohort of patients in the U.S. with preexisting T2D, there was no significant change in longer-term average HbA1c or weight among patients who had COVID-19. Mechanical ventilation was associated with a decrease in HbA1c after COVID-19.

Examining D-dimer and Empiric Anti-coagulation in COVID-19-Related Thrombosis

Objective Thrombosis is thought to occur frequently in the setting of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. We aimed to elucidate the relationship between macro/microvascular thrombosis, D-dimer levels, and empiric anticoagulation in coronavirus disease 2019 (COVID-19). Methods This was an exploratory prospective, single-site, observational study. Adult emergency department patients with COVID-19 requiring hospitalization received a point-of-care lower extremity venous duplex ultrasound. The primary endpoint was thromboembolism and associated D-dimer level. Secondary endpoints included rates of micro and macro thrombotic complications as well as empiric anticoagulant use. Results Between January 13th and April 12th 2021, 52 patients were enrolled. Median D-dimer at presentation was 650 ng/mL (range 250-10,000 ng/mL) among patients with negative duplex studies. During hospitalization, 18 patients underwent 20 additional studies assessing for venous thromboembolism (VTE). These studies yielded one deep vein thrombosis (DVT) diagnosis. Among patients with negative studies median D-dimer was 1,246 ng/mL (range 329-10,000 ng/mL). Two patients experienced microvascular complications. Seven patients were started on empiric full dose anticoagulation. Conclusion While VTE remains a major concern amongst patients with COVID-19, the normal D-dimer cut off of >500 ng/mL likely should not be used to initiate further VTE workup. Additionally, moderately elevated D-dimer did not correlate strongly with microvascular complications and may not be relevant in the decision to initiate empiric anticoagulation.

Predictors of hospitalization and severe disease due to breakthrough SARS-CoV-2 infection in fully vaccinated individuals.

Objective: We aimed to identify risk factors for hospital admission and severe disease among fully vaccinated (FV) individuals with COVID-19. Further, we investigated if risk factors for hospitalization and severe disease are similar between unvaccinated (UV) and vaccinated individuals. Methods: This was a multicenter, observational cohort analysis from a large regional healthcare system in metro Detroit using electronic health record data to evaluate risk factors for hospitalization and severe COVID-19 disease. Vaccination data were retrieved using electronic medical records linked to our statewide immunization database. Consecutive adult FV and UV patients with a primary admission diagnosis of COVID-19 were included in the comparative analysis. Partially vaccinated patients and patients who had received a booster dose were excluded. The primary outcome of this study was hospital admission and severe disease inclusive of intensive care unit (ICU) admission, mechanical ventilation, or death. Results: Between December 15, 2020 and December 19, 2021, 20,584 emergency department visits met our inclusion criteria. Among these, 2005 (9.7%) visits consisted of FV individuals, 18,579 (90.3%) were UV, and 40.3% of UV and 52.7% of FV required hospitalization with similar (12.7% and 12.6%, respectively) rates of severe disease. Hospitalized UV patients with severe disease were younger than their FV counterparts (49.5% <65 years vs. 13.5% p < 0.001). Risk factors for severe disease on UV and FV included age ≥65 years (UV: adjusted odds ratio [aOR] 1.49, 95% confidence interval [CI] 1.28-1.73, p < 0.001 and FV: aOR 2.50, 95% CI 1.44-4.36 p = 0.001) and weighted Elixhauser score >10 (UV: aOR 9.11, 95% CI 6.92-12.00, p < 0.001 and FV: aOR 6.04, 95% CI 2.68-13.26, p < 0.001). However, only on UV status, body mass index (BMI) ≥30 kg/m2 was associated with increased odds of severe disease (aOR 2.59, 95% CI 2.09-3.22, p < 0.001). Conclusions: FV patients with breakthrough SARS-CoV-2 infection who require hospitalization and have severe disease are older and have more medical comorbidities compared to UV patients. When comparing risk factors for severe disease between UV and FV individuals, FV status is particularly associated with reduced risk among patients with a BMI ≥30 kg/m2 and a moderate number of medical comorbidities, regardless of age, highlighting the importance of vaccination in these particularly vulnerable groups.

Boosters reduce in-hospital mortality in patients with COVID-19: An observational cohort analysis.

Background: Real-world data on the effectiveness of boosters against COVID-19, especially as new variants continue to emerge, is limited. Our objective was to assess demographic, clinical, and outcome variables of patients requiring hospitalization for severe SARS-CoV-2 infection comparing fully vaccinated and boosted (FV&B), fully vaccinated (FV), and unvaccinated (UV) patients. Methods: This multicenter observational cohort analysis compared demographic, clinical, and outcome variables in FV&B, FV, and UV adults hospitalized for COVID-19. Partially vaccinated (PV) and individuals still hospitalized beyond the designated follow-up date of February 1, 2022 were excluded. The primary endpoint was in-hospital mortality. Secondary endpoints included characteristics and outcomes in subpopulations of intensive care and geriatric (age >65) patients. Findings: Between August 12th, 2021 and January 20th, 2022, 8232 patient encounters had a primary diagnosis of COVID-19 and required inpatient treatment. Of the 8232 encounters requiring hospitalization, 448 (5.8%) were FV&B, 2257 (29.2%) were FV, and 5023 (65.0%) were UV; 357 PV and 147 still hospitalized were excluded. The median age of FV&B cohort was 73 (IQR 62, 82) compared to 70 (IQR 59, 80) for FV and 59 (IQR 45, 71) for UV (0.001). Most patients were female in both the FB&V and UV groups with 51.1% and 51.8%, respectively, while the FV group had a majority of males (51.3%). The median Elixhauser weighted score was 12 (IQR 3, 22) for FV&B, 10 (IQR 2, 20) for FV, and 9 (IQR 0, 17) for UV groups (p < 0.001). In-hospital mortality was 7.1% in the FV&B, 10.3% in the FV group, and 12.8% in the UV group (p < 0.001). The FV&B group had lower in-hospital mortality than both FV and UV groups (p = 0.045 and p = 0.001, respectively). The FV group had lower in-hospital mortality than the UV group (p = 0.004). Interpretation: Fully vaccinated and boosted patients requiring hospital-level care for breakthrough COVID-19 have lower in-hospital mortality than fully vaccinated and unvaccinated patients despite being older and higher risk at baseline. Boosters offer added protection beyond full vaccination in preventing death. As COVID-19 continues to spread, larger expansive trials are needed to further identify risk factors for severe outcomes among the FV&B population. Funding: This research received no specific grant from any funding agency in public, commercial, or not-for-profit sectors.

Harmonizing units and values of quantitative data elements in a very large nationally pooled electronic health record (EHR) dataset.

OBJECTIVE: The goals of this study were to harmonize data from electronic health records (EHRs) into common units, and impute units that were missing. MATERIALS AND METHODS: The National COVID Cohort Collaborative (N3C) table of laboratory measurement data-over 3.1 billion patient records and over 19 000 unique measurement concepts in the Observational Medical Outcomes Partnership (OMOP) common-data-model format from 55 data partners. We grouped ontologically similar OMOP concepts together for 52 variables relevant to COVID-19 research, and developed a unit-harmonization pipeline comprised of (1) selecting a canonical unit for each measurement variable, (2) arriving at a formula for conversion, (3) obtaining clinical review of each formula, (4) applying the formula to convert data values in each unit into the target canonical unit, and (5) removing any harmonized value that fell outside of accepted value ranges for the variable. For data with missing units for all the results within a lab test for a data partner, we compared values with pooled values of all data partners, using the Kolmogorov-Smirnov test. RESULTS: Of the concepts without missing values, we harmonized 88.1% of the values, and imputed units for 78.2% of records where units were absent (41% of contributors' records lacked units). DISCUSSION: The harmonization and inference methods developed herein can serve as a resource for initiatives aiming to extract insight from heterogeneous EHR collections. Unique properties of centralized data are harnessed to enable unit inference. CONCLUSION: The pipeline we developed for the pooled N3C data enables use of measurements that would otherwise be unavailable for analysis.

Effectiveness of BNT162b2 and mRNA-1273 Second Doses and Boosters for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Infection and SARS-CoV-2-Related Hospitalizations: A Statewide Report From the Minnesota Electronic Health Record Consortium.

Using vaccine data combined with electronic health records, we report that mRNA boosters provide greater protection than a 2-dose regimen against SARS-CoV-2 infection and related hospitalizations. The benefit of a booster was more evident in the elderly and those with comorbidities.

Trends in COVID-19 Vaccine Administration and Effectiveness Through October 2021.

Importance: COVID-19 vaccines are effective, but inequities in vaccine administration and waning immunity may limit vaccine effectiveness. Objectives: To report statewide trends in vaccine administration and vaccine effectiveness in Minnesota. Design, Setting, and Participants: This cohort study used COVID-19 vaccine data from the Minnesota Immunization Information Connection from October 25, 2020, through October 30, 2021 that were linked with electronic health record (EHR) data from health systems collaborating as part of the Minnesota EHR Consortium (MNEHRC). Participants included individuals who were seen at a participating health system in Minnesota. Exposures: Individuals were considered fully vaccinated in the second week after receipt of a second dose of a BNT162b2 or mRNA-1273 vaccine or a single dose of an Ad26.COV.2.S vaccine. Main Outcomes and Measures: A completed vaccination series and vaccine breakthrough, defined as either a positive SARS-CoV-2 polymerase chain reaction (PCR) test or a hospital admission the same week or within the 3 weeks following a positive SARS-CoV-2 PCR test. A test-negative design and incident rate ratio were used to evaluate COVID-19 vaccine effectiveness separately for the BNT162b2, mRNA-1273, and Ad26.COV.2.S vaccines. Rurality and social vulnerability index were assessed at the area level. Results: This study included 4 431 190 unique individuals at participating health systems, and 3 013 704 (68%) of the individuals were fully vaccinated. Vaccination rates were lowest among Minnesotans who identified as Hispanic (116 422 of 217 019 [54%]), multiracial (30 066 of 57 412 [52%]), American Indian or Alaska Native (22 190 of 41 437 [54%]), and Black or African American (158 860 of 326 595 [49%]) compared with Minnesotans who identified as Asian or Pacific Islander (159 999 of 210 994 [76%]) or White (2 402 928 of 3 391 747 [71%]). Among individuals aged 19 to 64 years, vaccination rates were lower in rural areas (196 479 of 308 047 [64%]) compared with urban areas (151 541 of 1 951 265 [77%]) and areas with high social vulnerability (544 433 of 774 952 [70%]) compared with areas with low social vulnerability (571 613 of 724 369 [79%]). In the 9 weeks ending October 30, 2021, vaccine effectiveness as assessed by a test-negative design was 33% (95% CI, 30%-37%) for Ad26.COV.2.S; 53% (95% CI, 52%-54%) for BNT162b2; and 66% (95% CI, 65%-67%) for mRNA-1273. For SARS-CoV-2-related hospitalizations, vaccine effectiveness in the 9 weeks ending October 30, 2021, was 78% (95% CI, 75%-81%) for Ad26.COV.2.S; 81% (95% CI, 79%-82%) for BNT162b2; and 81% (95% CI, 79%-82%) for mRNA-1273. Conclusions and Relevance: This cohort study of data from a Minnesota statewide consortium suggests disparities in vaccine administration and effectiveness. Vaccine effectiveness against infection was lower for Ad26.COV.2.S and BNT162b2 but was associated with protection against SARS-CoV-2-related hospitalizations despite the increased prevalence of the Delta variant in Minnesota.

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

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 ≥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 >8%, and risk of invasive ventilation or ECMO plateaued >9%. 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.

Structure and function of a family of tick-derived complement inhibitors targeting properdin.

Activation of the serum-resident complement system begins a cascade that leads to activation of membrane-resident complement receptors on immune cells, thus coordinating serum and cellular immune responses. Whilst many molecules act to control inappropriate activation, Properdin is the only known positive regulator of the human complement system. By stabilising the alternative pathway C3 convertase it promotes complement self-amplification and persistent activation boosting the magnitude of the serum complement response by all triggers. In this work, we identify a family of tick-derived alternative pathway complement inhibitors, hereafter termed CirpA. Functional and structural characterisation reveals that members of the CirpA family directly bind to properdin, inhibiting its ability to promote complement activation, and leading to potent inhibition of the complement response in a species specific manner. We provide a full functional and structural characterisation of a properdin inhibitor, opening avenues for future therapeutic approaches.

Minnesota Electronic Health Record Consortium COVID-19 Project: Informing Pandemic Response Through Statewide Collaboration Using Observational Data.

OBJECTIVE: Robust disease and syndromic surveillance tools are underdeveloped in the United States, as evidenced by limitations and heterogeneity in sociodemographic data collection throughout the COVID-19 pandemic. To monitor the COVID-19 pandemic in Minnesota, we developed a federated data network in March 2020 using electronic health record (EHR) data from 8 multispecialty health systems. MATERIALS AND METHODS: In this serial cross-sectional study, we examined patients of all ages who received a COVID-19 polymerase chain reaction test, had symptoms of a viral illness, or received an influenza test from January 3, 2016, through November 7, 2020. We evaluated COVID-19 testing rates among patients with symptoms of viral illness and percentage positivity among all patients tested, in aggregate and by zip code. We stratified results by patient and area-level characteristics. RESULTS: Cumulative COVID-19 positivity rates were similar for people aged 12-64 years (range, 15.1%-17.6%) but lower for adults aged ≥65 years (range, 9.3%-10.7%). We found notable racial and ethnic disparities in positivity rates early in the pandemic, whereas COVID-19 positivity was similarly elevated across most racial and ethnic groups by the end of 2020. Positivity rates remained substantially higher among Hispanic patients compared with other racial and ethnic groups throughout the study period. We found similar trends across area-level income and rurality, with disparities early in the pandemic converging over time. PRACTICE IMPLICATIONS: We rapidly developed a distributed data network across Minnesota to monitor the COVID-19 pandemic. Our findings highlight the utility of using EHR data to monitor the current pandemic as well as future public health priorities. Building partnerships with public health agencies can help ensure data streams are flexible and tailored to meet the changing needs of decision makers.

Developing Treatment Guidelines During a Pandemic Health Crisis: Lessons Learned From COVID-19.

The development of the National Institutes of Health (NIH) COVID-19 Treatment Guidelines began in March 2020 in response to a request from the White House Coronavirus Task Force. Within 4 days of the request, the NIH COVID-19 Treatment Guidelines Panel was established and the first meeting took place (virtually-as did subsequent meetings). The Panel comprises 57 individuals representing 6 governmental agencies, 11 professional societies, and 33 medical centers, plus 2 community members, who have worked together to create and frequently update the guidelines on the basis of evidence from the most recent clinical studies available. The initial version of the guidelines was completed within 2 weeks and posted online on 21 April 2020. Initially, sparse evidence was available to guide COVID-19 treatment recommendations. However, treatment data rapidly accrued based on results from clinical studies that used various study designs and evaluated different therapeutic agents and approaches. Data have continued to evolve at a rapid pace, leading to 24 revisions and updates of the guidelines in the first year. This process has provided important lessons for responding to an unprecedented public health emergency: Providers and stakeholders are eager to access credible, current treatment guidelines; governmental agencies, professional societies, and health care leaders can work together effectively and expeditiously; panelists from various disciplines, including biostatistics, are important for quickly developing well-informed recommendations; well-powered randomized clinical trials continue to provide the most compelling evidence to guide treatment recommendations; treatment recommendations need to be developed in a confidential setting free from external pressures; development of a user-friendly, web-based format for communicating with health care providers requires substantial administrative support; and frequent updates are necessary as clinical evidence rapidly emerges.

Vaccination reduces need for emergency care in breakthrough COVID-19 infections: A multicenter cohort study.

BACKGROUND: While recent literature has shown the efficacy of the SARS-CoV-2 vaccine in preventing infection, it's impact on need for emergency care/hospitalization in breakthrough infections remain unclear, particularly in regions with a high rate of variant viral strains. We aimed to determine if vaccination reduces hospital visits in breakthrough COVID-19. METHODS: This observational cohort analysis compared unvaccinated (UV), partially vaccinated (PV), and fully vaccinated (FV) adult patients with SARS-CoV-2 infection requiring emergency care(EC)/hospitalization within an eight-hospital system in Michigan. Demographic and clinical variables were obtained from the electronic record. Vaccination data was obtained from the Michigan Care Improvement Registry and Centers for Disease Control vaccine tracker. Primary endpoint was rate of emergency care/hospitalization encounters among patients diagnosed with COVID-19. Secondary outcome was severe disease-composite outcome (ICU, mechanical ventilation, or in-hospital death). FINDINGS: Between December 15,2020 and April 30,2021, 11,834 EC encounters were included:10,880 (91.9%) UV, 825 (7%) PV, 129 (1.1%) FV. Average age was 53.0 ± 18.2 and 52.8% were female. Accounting for the SARS-CoV-2 vaccination population groups in Michigan, the ED encounters/hospitalizations rate relevant to COVID-19 was 96% lower in FV versus UV (multiplicative effect:0.04, 95% CI 0.03 to 0.06, p < 0.001) in negative binomial regression. COVID-19 EC visits rate peaked at 22.61, 12.88, and 1.29 visits per 100000 for the UV, PV, and FV groups, respectively. In the propensity-score matching weights analysis, FV had a lower risk of composite disease compared to UV but statistically insignificant (HR 0.84, 95% CI 0.52 to 1.38). INTERPRETATION: The need for emergency care/hospitalization due to breakthrough COVID-19 is an exceedingly rare event in fully vaccinated patients. As vaccination has increased regionally, EC visits amongst fully vaccinated individuals have remained low and occur much less frequently than unvaccinated individuals. If hospital-based treatment is required, elderly patients with significant comorbidities are at high-risk for severe outcomes regardless of vaccination status.