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BACKGROUND: Evidence of the effectiveness of treatment for obesity delivered in primary care settings in underserved populations is lacking. METHODS: We conducted a cluster-randomized trial to test the effectiveness of a high-intensity, lifestyle-based program for obesity treatment delivered in primary care clinics in which a high percentage of the patients were from low-income populations. We randomly assigned 18 clinics to provide patients with either an intensive lifestyle intervention, which focused on reduced caloric intake and increased physical activity, or usual care. Patients in the intensive-lifestyle group participated in a high-intensity program delivered by health coaches embedded in the clinics. The program consisted of weekly sessions for the first 6 months, followed by monthly sessions for the remaining 18 months. Patients in the usual-care group received standard care from their primary care team. The primary outcome was the percent change from baseline in body weight at 24 months. RESULTS: All 18 clinics (9 assigned to the intensive program and 9 assigned to usual care) completed 24 months of participation; a median of 40.5 patients were enrolled at each clinic. A total of 803 adults with obesity were enrolled: 452 were assigned to the intensive-lifestyle group, and 351 were assigned to the usual-care group; 67.2% of the patients were Black, and 65.5% had an annual household income of less than $40,000. Of the enrolled patients, 83.4% completed the 24-month trial. The percent weight loss at 24 months was significantly greater in the intensive-lifestyle group (change in body weight, −4.99%; 95% confidence interval [CI], −6.02 to −3.96) than in the usual-care group (−0.48%; 95% CI, −1.57 to 0.61), with a mean between-group difference of −4.51 percentage points (95% CI, −5.93 to −3.10) (P

Background Clinicians who work in primary care are potentially the most influential healthcare professionals to address the problem of antibiotic resistance because this is where most antibiotics are prescribed. Despite a number of evidence based interventions targeting the management of community infections, the inappropriate antibiotic prescribing rates remain high. Discussion The question is how can appropriate prescribing of antibiotics through the use of Antimicrobial Stewardship (AMS) programs be successfully implemented in primary care. We discuss that a top-down approach utilising a combination of strategies to ensure the sustainable implementation and uptake of AMS interventions in the community is necessary to support clinicians and ensure a robust implementation of AMS in primary care. Specifically, we recommend a national accreditation standard linked to the framework of Core Elements of Outpatient Antibiotic Stewardship, supported by resources to fund the implementation of AMS interventions that are connected to quality improvement initiatives. This article debates how this can be achieved. Summary The paper highlights that in order to support the sustainable uptake of AMS programs in primary care, an approach similar to the hospital and post-acute care settings needs to be adopted, utilising a combination of behavioural and regulatory processes supported by sustainable funding. Without these strategies the problem of inappropriate antibiotic prescribing will not be adequately addressed in the community and the successful implementation and uptake of AMS programs will remain a dream.

AIM To compare the cardiovascular risks between users and non-users of sodium-glucose co-transporter-2 (SGLT2) inhibitors based on electronic medical record data from a large integrated healthcare system in South Louisiana. MATERIALS AND METHODS Demographic, anthropometric, laboratory and medication prescription information for patients with type 2 diabetes who were new users of SGLT2 inhibitors, either as initial treatments or as add-on treatments, were obtained from electronic health records. Mediation analysis was performed to evaluate the association of use of SGLT2 inhibitors and changes of metabolic risk factors with the risk of incident ischaemic heart disease. RESULTS A total of 5338 new users of SGLT2 inhibitors were matched with 13 821 non-users. During a mean follow-up of 3.26 years, 2302 incident cases of ischaemic heart disease were defined. After adjusting for multiple confounding factors, patients using SGLT2 inhibitors had a lower risk of incident ischaemic heart disease compared to patients not using SGLT2 inhibitors (hazard ratio [HR] 0.63, 95% confidence interval [CI] 0.54-0.73). Patients using SGLT2 inhibitors also had a lower risk of incident ischaemic heart disease within 6 months (HR 0.36, 95% CI 0.25-0.44), 12 months (HR 0.40, 95% CI 0.32-0.49), 24 months (HR 0.53, 95% CI 0.43-0.60) and 36 months (HR 0.65, 95% CI 0.54-0.73), respectively. Reductions in systolic blood pressure partly mediated lowering risk of ischaemic heart disease among patients using SGLT2 inhibitors. CONCLUSIONS The real-world data in the present study show the contribution of SGLT2 inhibitors to reducing risk of ischaemic heart disease, and their benefits beyond glucose-lowering.

Background Following the high morbidity and mortality due to Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) infections in New Orleans, Louisiana, we sought to assess progress toward herd immunity. Methods Ochsner Health employees and patients who volunteered for Abbott SARS-CoV-2 immunoglobulin G (IgG) antibody test between March 1 and May 1, 2020 were included. We estimated IgG prevalence and used logistic regression to estimate odds ratios (OR) and 95% confidence intervals (CI) for variables associated with IgG test status. Results Of the 13,343 participants with IgG test results, 78.6% were women, 70.6% were non-Hispanic White, 21.1% non-Hispanic Black, 2.9% Hispanic Americans and 5.4% belonged to other races. Overall, 7.99% (95% CI: 7.53-8.45%) of the participants tested IgG positive. In age-, sex- and body mass index (BMI)-adjusted analyses, non-Hispanic Blacks were 2.7-times more likely to test positive than non-Hispanic Whites (OR=2.72; 95% CI: 2.33-3.19). Corresponding ORs (95% CIs) were 1.29 (0.84-1.99) for Hispanic Americans and 1.22 (0.85-1.75) for Other race/ethnicities. Compared to participants in administrative occupations, physician assistants (OR=7.14; 95% CI: 1.72-29.6) and therapists (OR=4.74; 95% CI: 1.49-15.03) were significantly more likely to have IgG antibodies while the association among nurses was not significant (OR=2.35; 95% CI: 0.96-5.77). Relative to 1.40, the test threshold for positivity, our measurements indicate a strong immune response (5.38±1.69), especially among those with a higher BMI. Conclusions SARS-COV-2 IgG antibodies were prevalent only in 8% of the participants. IgG prevalence was highest among non-Hispanic Blacks and participants with higher BMI but was lower among older participants.

Patients with diabetes have a 10-fold higher risk of lower-extremity amputation (LEA) than people without diabetes (1). LEA is associated with the greatest reduction in quality of life and the greatest increase in mortality and medical costs in all diabetes complications. Previous studies suggested that the mean hemoglobin A1c (HbA1c) level was associated with an increased LEA risk among patients with type 2 diabetes (2). However, emerging evidence indicates that long-term glycemic variability evaluated by clinical visit-to-visit HbA1c variability may be a better predictor of diabetes complications (3). So far, the definitions of long-term HbA1c variability are inconsistent. In most studies, standard deviation of serial HbA1c measurements (HbA1c SD) and the intrapersonal coefficient of variation of HbA1c (HbA1c CV) are often used to represent HbA1c variability. In the current study, we added a new marker—HbA1c variability score (HVS) (4)—which is more easily applied to clinical practice. We collected data from electronic health records for patients with type 2 diabetes between 2013 and 2019 in the Louisiana Experiment Assessing Diabetes outcomes (LEAD) cohort study (5). We excluded patients who had LEA diagnosis before entry and within 2 years after the first date of diabetes diagnosis, those with incomplete baseline data, those who did not have at least four HbA1c tests within 2 …

Introduction When and how to intensify treatment in patients with type 2 diabetes (T2D) not achieving glycated hemoglobin (HbA1c) targets with oral antidiabetic drugs (OADs) in clinical practice remains a matter of clinical preference. This pilot study was conducted using the retrospective observational data from such patients to evaluate the impact on HbA1c of three treatment sequences: simultaneous initiation of basal insulin (BI) and a glucagon-like peptide-1 receptor agonist (GLP-1 RA; Cohort 1); BI followed by GLP-1 RA initiation within a 90-day timeframe (Cohort 2); or BI followed by GLP-1 RA initiation beyond 90 days (Cohort 3). Methods Data from the regional US electronic medical records database, Research Action for Health Network (REACHnet), were extracted for all patients with T2D aged ≥ 18 years who had encounter dates between January 2011 and August 2017 and ≥ 1 HbA1c laboratory value(s)

Background: In the early phases of the 2019 novel coronavirus (COVID-19) pandemic, health system leaders faced the urgent task of translating the unknown into forecasting models for hospital capacity. Our study objective was to demonstrate the application of a practical, locally informed model to estimate the hospital capacity needed even though the community COVID-19 caseload was unknown. Methods: We developed a susceptible-infected-recovered (SIR) model that was adopted from the University of Pennsylvania COVID-19 Hospital Impact Model for Epidemics and employed at 8 hospitals within Ochsner Health, the largest integrated delivery system in Louisiana, between March 16 and April 15, 2020. Intensive care unit (ICU) admissions of cases in the New Orleans area were used to estimate the community case load when testing was delayed. Results: Initially, the observed ICU census trended near R0=2.0, whereas the ventilator census trended between R0=2.0 and 3.0. After implementing social distancing, both the ICU and ventilator capacity trended toward R0=1.3, while non-ICU medical/surgical beds trended toward R0=1.5. The model accurately predicted peak ICU (n=250) and hospital bed (n=487) usage by April 6, 2020. In response to model trends, Ochsner added 130 ICU beds across its hospitals by opening a new ICU and converting operating rooms and parts of emergency departments to ICU beds. Conclusion: When disease testing is limited or results are delayed, ICU admissions data can inform SIR models of the rate of spread of COVID-19 in a community. Our model used various R0 plots to demonstrate an array of scenarios to guide planning for hospital and political leaders.

Background: Management of diabetes may be uniquely challenging for older individuals with multiple chronic conditions. Health systems and policymakers have attempted to reduce barriers to chronic care management (CCM) through incentives to provide non-face-to-face care. This qualitative study aimed to investigate and present views on non-face-to-face care management held by elderly patients with diabetes and other chronic conditions in order to contribute to improved programming for this population. Materials and methods: Semi-structured interviews were conducted with patients over the age of 64 who have been diagnosed with diabetes and at least one other chronic health condition. Interview recordings were transcribed and analyzed by experienced researchers using a thematic analytic approach, and an illustrative case study was developed. Results: Thirty individuals participated in this study. Participants were drawn from three health systems in south Louisiana, an area with high rates of morbidity and mortality related to chronic diseases. We identified themes related to lived experiences with diabetes and other medical conditions, perception of personal health status, perceived value of non-face-to-face programs, and support needs for future programming. Additionally, we present one case study describing in detail an individual patient's experience with non-face-to-face CCM. Conclusion: Health systems should consider intentionally recruiting participants who would benefit most from non-face-to-face care, including higher-need, less self-sufficient patients with resource constraints, while continuing to offer in-person services. Future research should examine whether tailoring non-face-to-face programming and support to address unique barriers can further enhance diabetes care at the population level.

Supplemental Digital Content is available in the text., OBJECTIVES: Critically ill patients with coronavirus disease 2019 have variable mortality. Risk scores could improve care and be used for prognostic enrichment in trials. We aimed to compare machine learning algorithms and develop a simple tool for predicting 28-day mortality in ICU patients with coronavirus disease 2019. DESIGN: This was an observational study of adult patients with coronavirus disease 2019. The primary outcome was 28-day inhospital mortality. Machine learning models and a simple tool were derived using variables from the first 48 hours of ICU admission and validated externally in independent sites and temporally with more recent admissions. Models were compared with a modified Sequential Organ Failure Assessment score, National Early Warning Score, and CURB-65 using the area under the receiver operating characteristic curve and calibration. SETTING: Sixty-eight U.S. ICUs. PATIENTS: Adults with coronavirus disease 2019 admitted to 68 ICUs in the United States between March 4, 2020, and June 29, 2020. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: The study included 5,075 patients, 1,846 (36.4%) of whom died by day 28. eXtreme Gradient Boosting had the highest area under the receiver operating characteristic curve in external validation (0.81) and was well-calibrated, while k-nearest neighbors were the lowest performing machine learning algorithm (area under the receiver operating characteristic curve 0.69). Findings were similar with temporal validation. The simple tool, which was created using the most important features from the eXtreme Gradient Boosting model, had a significantly higher area under the receiver operating characteristic curve in external validation (0.78) than the Sequential Organ Failure Assessment score (0.69), National Early Warning Score (0.60), and CURB-65 (0.65; p < 0.05 for all comparisons). Age, number of ICU beds, creatinine, lactate, arterial pH, and Pao2/Fio2 ratio were the most important predictors in the eXtreme Gradient Boosting model. CONCLUSIONS: eXtreme Gradient Boosting had the highest discrimination overall, and our simple tool had higher discrimination than a modified Sequential Organ Failure Assessment score, National Early Warning Score, and CURB-65 on external validation. These models could be used to improve triage decisions and clinical trial enrichment.

Introduction Increased utilization of electronic health records (EHR) has enriched databases for creating risk models. We used machine learning techniques to develop an EHR-based risk model locally fitted to patients with type 2 diabetes mellitus (T2DM) for predicting cardiovascular disease. Methods This retrospective observational study was conducted within Ochsner Health, Louisiana, USA, between 2013–2017. Data analysis included 6245 patients who had two outpatient diagnoses of T2DM recorded on separate days or a diagnosis recorded during an inpatient encounter. Baseline clinical data were limited to 180 days before the index diagnosis. Cardiovascular outcomes were coronary heart disease (CHD), heart failure and stroke. Machine learning approaches were used to select predictor variables into Cox proportional hazards models for each outcome. Locally fit equations were compared to “generalized” risk equations (RECODe, AS-CVD, QRISK3) using model discrimination and calibration. Results Among factors identified in the Ochsner (n = 11), RECODe (n = 14), AS-CVD (n = 15) and QRISK3 (n = 23), only age was common to all four risk equations. The Ochsner model had high internal discrimination for CHD (C-statistics 0.85) and better discrimination than RECODe (C-statistics 0.45), the QRISK3 (C-statistics 0.72) and AS-CVD (C-statistics 0.54). Conclusions The Ochsner model overestimated 5-year CHD risk, but had relatively higher calibration than the other models in CHD. Risk equations fitted for local populations improved cardiovascular risk stratification for patients with T2DM. Application of machine learning simplified the models compared to “generalized” risk equations. Supplementary Information The online version contains supplementary material available at 10.1007/s13300-021-01096-w.

Variation in hospital mortality has been described for coronavirus disease 2019 (COVID-19), but the factors that explain these differences remain unclear.Our objective was to utilize a large, nationally representative dataset of critically ill adults with COVID-19 to determine which factors explain mortality variability.In this multicenter cohort study, we examined adults hospitalized in intensive care units with COVID-19 at 70 United States hospitals between March and June 2020. The primary outcome was 28-day mortality. We examined patient-level and hospital-level variables. Mixed-effects logistic regression was used to identify factors associated with interhospital variation. The median odds ratio (OR) was calculated to compare outcomes in higher- vs. lower-mortality hospitals. A gradient boosted machine algorithm was developed for individual-level mortality models.A total of 4,019 patients were included, 1537 (38%) of whom died by 28 days. Mortality varied considerably across hospitals (0-82%). After adjustment for patient- and hospital-level domains, interhospital variation was attenuated (OR decline from 2.06 [95% CI, 1.73-2.37] to 1.22 [95% CI, 1.00-1.38]), with the greatest changes occurring with adjustment for acute physiology, socioeconomic status, and strain. For individual patients, the relative contribution of each domain to mortality risk was: acute physiology (49%), demographics and comorbidities (20%), socioeconomic status (12%), strain (9%), hospital quality (8%), and treatments (3%).There is considerable interhospital variation in mortality for critically ill patients with COVID-19, which is mostly explained by hospital-level socioeconomic status, strain, and acute physiologic differences. Individual mortality is driven mostly by patient-level factors. This article is open access and distributed under the terms of the Creative Commons Attribution Non-Commercial No Derivatives License 4.0 (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Objective Centralized remote fetal monitoring (CRFM) has been proposed as a method to improve the performance of intrapartum fetal heart rate (FHR) monitoring and perinatal outcomes. The purpose of this study is to determine whether CRFM was associated with a reduction in unexpected term neonatal intensive care unit (NICU) admissions. Study Design A pre–post design was used to examine the effectiveness of CRFM which was implemented in stages across five hospitals. The exposure group was all women who underwent intrapartum monitoring via CRFM. The unexposed group was of women who delivered at the same hospitals prior to implementation of CRFM. Pregnancies with expected NICU admissions, gestational age Results There were 19,392 live births included in this analysis. In the univariable analysis, the odds of unexpected term NICU admission was lower among the CRFM exposed group compared with the unexposed group (odds ratio [OR] = 0.86, 95% confidence interval [CI]: 0.75–0.99; p = 0.038). In multivariable analysis, this did not reach statistical significance (OR = 0.92, 95% CI: 0.79–1.06; p = 0.24). Cesarean and OVD were less likely in the exposed group (OR = 0.91, 95% CI: 0.85–0.97; p = 0.008) and (OR = 0.70, 95% CI: 0.59–0.83, p Conclusion In some practice settings, utilization of a CRFM system may decrease the risk of unexpected term NICU admission, cesarean, and OVD rate. Key Points

Summary: Many US states published crisis standards of care (CSC) guidelines for allocating scarce critical care resources during the COVID-19 pandemic. However, the performance of these guidelines in maximizing their population benefit has not been well tested. In 2,272 adults with COVID-19 requiring mechanical ventilation drawn from the Study of the Treatment and Outcomes in Critically Ill Patients with COVID-19 (STOP-COVID) multicenter cohort, we test the following three approaches to CSC algorithms: Sequential Organ Failure Assessment (SOFA) scores grouped into ranges, SOFA score ranges plus comorbidities, and a hypothetical approach using raw SOFA scores not grouped into ranges. We find that area under receiver operating characteristic (AUROC) curves for all three algorithms demonstrate only modest discrimination for 28-day mortality. Adding comorbidity scoring modestly improves algorithm performance over SOFA scores alone. The algorithm incorporating comorbidities has modestly worse predictive performance for Black compared to white patients. CSC algorithms should be empirically examined to refine approaches to the allocation of scarce resources during pandemics and to avoid potential exacerbation of racial inequities.

Background Coronavirus disease 2019 (COVID-19) has high infectivity and causes extensive morbidity and mortality. Cardiovascular disease is a risk factor for adverse outcomes in COVID-19, but baseline left ventricular ejection fraction (LVEF) in particular has not been evaluated thoroughly in this context. Methods We analyzed patients in our state's largest health system who were diagnosed with COVID-19 between March 20 and May 15, 2020. Inclusion required an available echocardiogram within one year prior to diagnosis. The primary outcome was all-cause mortality. LVEF was analyzed both as a continuous variable and using a cutoff of 40%. Results Among 396 patients (67±16 years, 191 [48%] male, 235 [59%] Black, 59 [15%] LVEF ≤40%), 289 (73%) required hospital admission, and 116 (29%) died during 85±63 days of follow-up. Echocardiograms, performed a median of 57 (IQR 11-122) days prior to COVID-19 diagnosis, showed a similar distribution of LVEF between survivors and decedents (p=0.84). Receiver operator characteristic analysis revealed no predictive ability of LVEF for mortality, and there was no difference in survival among those with LVEF ≤40% vs. >40% (p=0.49). Multivariable analysis did not change these relationships. Similarly, there was no difference in LVEF based on whether the patient required hospital admission (56±13 vs. 55±13, p=0.38), and patients with a depressed LVEF did not require admission more frequently than their preserved-LVEF peers (p=0.87). A premorbid history of dyspnea consistent with symptomatic heart failure was not associated with mortality (p=0.74). Conclusions Among patients diagnosed with COVID-19, pre-COVID-19 LVEF was not a risk factor for death or hospitalization.

Background: Intensive lifestyle interventions (ILIs) are the first-line approach to effectively treat obesity and manage associated cardiometabolic risk factors. Because few people have access to ILIs in academic health centers, primary care must implement similar approaches for a meaningful effect on obesity and cardiometabolic disease prevalence. To date, however, effective lifestyle-based obesity treatment in primary care is limited. We examined the effectiveness of a pragmatic ILI for weight loss delivered in primary care among a racially diverse, low-income population with obesity for improving cardiometabolic risk factors over 24 months. Methods: The PROPEL trial (Promoting Successful Weight Loss in Primary Care in Louisiana) randomly allocated 18 clinics equally to usual care or an ILI and subsequently enrolled 803 (351 usual care, 452 ILI) adults (67% Black, 84% female) with obesity from participating clinics. The usual care group continued to receive their normal primary care. The ILI group received a 24-month high-intensity lifestyle-based obesity treatment program, embedded in the clinic setting and delivered by health coaches in weekly sessions initially and monthly sessions in months 7 through 24. Results: As recently demonstrated, participants receiving the PROPEL ILI lost significantly more weight over 24 months than those receiving usual care (mean difference, −4.51% [95% CI, −5.93 to −3.10]; P P P =0.76). Increases in high-density lipoprotein cholesterol were greater in the ILI than in the usual care group at both time points (mean difference at 24 months, 4.6 mg/dL [95% CI, 2.9–6.3]; P z score) decreased more in the ILI group than in the usual care group at both time points, with significant mean differences of the change of −0.31 (95% CI, −0.47 to −0.14; P P =0.01) at 24 months, respectively. Changes in total cholesterol, low-density lipoprotein cholesterol, triglycerides, and blood pressure did not differ significantly between groups at any time point. Conclusions: A pragmatic ILI consistent with national guidelines and delivered by trained health coaches in primary care produced clinically relevant improvements in cardiometabolic health in an underserved population over 24 months. Registration: URL: https://www.clinicaltrials.gov ; Unique identifier: NCT02561221.

Rationale & Objective Underlying kidney disease is an emerging risk factor for more severe COVID-19 illness. We examined the clinical courses of critically ill COVID-19 patients with and without pre-existing kidney disease and investigated the association between degree of underlying kidney disease and in-hospital outcomes. Study Design Retrospective cohort study Settings & Participants 4,264 critically ill COVID-19 patients (143 dialysis patients, 521 chronic kidney disease [CKD] patients, and 3,600 patients without CKD) admitted to ICUs at 68 hospitals in the United States. Predictor(s) Presence (versus absence) of pre-existing kidney disease Outcome(s) In-hospital mortality (primary); respiratory failure, shock, ventricular arrhythmia/ cardiac arrest, thromboembolic event, major bleed, and acute liver injury (secondary) Analytical Approach We used standardized differences to compare patient characteristics (values >0.10 indicate a meaningful difference between groups) and multivariable adjusted Fine and Gray survival models to examine outcome associations. Results Dialysis patients had a shorter time from symptom onset to ICU admission compared to other groups (median [quartile 1-quartile 3] days: 4 [2-9] for dialysis patients; 7 [3-10] for CKD patients; 7 [4-10] for patients without pre-existing kidney disease). More dialysis patients (25%) reported altered mental status than those with CKD (20%, standardized difference = 0.12) and no kidney disease (12%, standardized difference = 0.36). Half of dialysis and CKD patients died within 28-days of ICU admission versus 35% of patients without pre-existing kidney disease. Compared to patients without pre-existing kidney disease, dialysis patients had a higher risk of 28-day in-hospital death (adjusted HR 1.41; 95% CI 1.09, 1.81), while patients with CKD had an intermediate risk (adjusted HR 1.25; 95% CI 1.08, 1.44). Limitations Potential residual confounding Conclusions Findings highlight the high mortality of individuals with underlying kidney disease and severe COVID-19, underscoring the importance of identifying safe and effective COVID-19 therapies for this vulnerable population., Individuals with underlying kidney disease may be particularly vulnerable to severe COVID-19 illness, marked by multi-system organ failure, thrombosis, and a heightened inflammatory response. Among 4,264 critically ill adults with COVID-19 admitted to 68 intensive care units across the U.S., we found that both chronic kidney disease and dialysis patients had a ∼50% 28-day in-hospital mortality rate. Patients with underlying kidney disease had higher in-hospital mortality than patients without kidney disease, with patients on maintenance dialysis having the highest risk. As evidenced by differences in symptoms and clinical trajectories, patients with pre-existing kidney disease may have unique susceptibility to COVID-19-related complications which warrants additional study and special consideration in the pursuit and development of targeted therapies.

Hypercoagulability may be a key mechanism of death in patients with COVID-19. This cohort study evaluated the incidence of venous thromboembolism and major bleeding in critically ill patients with COVID-19 and examined the observational effect of early therapeutic anticoagulation on survival., Visual Abstract. Early Anticoagulation in COVID-19 Hypercoagulability may be a key mechanism of death in patients with COVID-19. This cohort study evaluated the incidence of venous thromboembolism and major bleeding in critically ill patients with COVID-19 and examined the observational effect of early therapeutic anticoagulation on survival. Visual Abstract. Early Anticoagulation in COVID-19 Hypercoagulability may be a key mechanism of death in patients with COVID-19. This cohort study evaluated the incidence of venous thromboembolism and major bleeding in critically ill patients with COVID-19 and examined the observational effect of early therapeutic anticoagulation on survival., Background: Hypercoagulability may be a key mechanism of death in patients with coronavirus disease 2019 (COVID-19). Objective: To evaluate the incidence of venous thromboembolism (VTE) and major bleeding in critically ill patients with COVID-19 and examine the observational effect of early therapeutic anticoagulation on survival. Design: In a multicenter cohort study of 3239 critically ill adults with COVID-19, the incidence of VTE and major bleeding within 14 days after intensive care unit (ICU) admission was evaluated. A target trial emulation in which patients were categorized according to receipt or no receipt of therapeutic anticoagulation in the first 2 days of ICU admission was done to examine the observational effect of early therapeutic anticoagulation on survival. A Cox model with inverse probability weighting to adjust for confounding was used. Setting: 67 hospitals in the United States. Participants: Adults with COVID-19 admitted to a participating ICU. Measurements: Time to death, censored at hospital discharge, or date of last follow-up. Results: Among the 3239 patients included, the median age was 61 years (interquartile range, 53 to 71 years), and 2088 (64.5%) were men. A total of 204 patients (6.3%) developed VTE, and 90 patients (2.8%) developed a major bleeding event. Independent predictors of VTE were male sex and higher D-dimer level on ICU admission. Among the 2809 patients included in the target trial emulation, 384 (11.9%) received early therapeutic anticoagulation. In the primary analysis, during a median follow-up of 27 days, patients who received early therapeutic anticoagulation had a similar risk for death as those who did not (hazard ratio, 1.12 [95% CI, 0.92 to 1.35]). Limitation: Observational design. Conclusion: Among critically ill adults with COVID-19, early therapeutic anticoagulation did not affect survival in the target trial emulation. Primary Funding Source: None.

AIM: To investigate the association between visit-to-visit HbA1c variability and the risk of cardiovascular disease in patients with type 2 diabetes. MATERIALS AND METHODS: We performed a retrospective cohort study of 29 260 patients with at least four HbA1c measurements obtained within 2 years of their first diagnosis of type 2 diabetes. Different HbA1c variability markers were calculated, including the standard deviation (SD), coefficient of variation (CV) and adjusted SD. Cox proportional hazards regression models were used to estimate the association of these HbA1c variability markers with incident cardiovascular disease. RESULTS: During a mean follow-up of 4.18 years, a total of 3746 incident cardiovascular disease cases were diagnosed. Multivariate-adjusted hazard ratios for cardiovascular disease across the first, second, third and fourth quartiles of HbA1c SD values were 1.00, 1.30 (95% confidence interval [CI] 1.18–1.42), 1.40 (95% CI 1.26–1.55) and 1.59 (95% CI 1.41–1.77) (P for trend

Objective While many seroprevalence studies of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have been performed, few are demographically representative. This investigation focused on defining the nature and frequency of symptomatic and asymptomatic SARS-CoV-2 infection in a representative, cross-sectional sample of communities in Louisiana, USA. Methods A sample of 4,778 adults from New Orleans and Baton Rouge, Louisiana were given a survey of symptoms and comorbidities, nasopharyngeal swab to test for an active infection (PCR), and blood draw to test for a past infection (immunoglobulin G). Odds ratios, cluster analysis, quantification of virus and antibody, and linear modeling were used to understand whether certain symptoms were associated with a positive test, how symptoms grouped together, whether virus or antibody varied by symptom status, and whether being symptomatic was different across the age span. Results Reported anosmia/ageusia was strongly associated with a positive test; 40.6% (93/229) tested positive versus 4.8% (218/4,549) positivity in those who did not report anosmia/ageusia (Common OR: 13.6; CI 10.1, 18.3). Of the people who tested positive, 47.3% (147/311) were completely asymptomatic. Symptom presentation clustered into three groups; low/no symptoms (0.4±0.9 average ±SD), highly symptomatic (7.5±1.9) or moderately symptomatic (4.0±1.5). Quantity of virus was lower in the asymptomatic versus symptomatic group (cycle number 23.3±8.3 versus 17.3±9.0, average ±SD; p, Graphical abstract Image 1

Even though current prescribing trends reveal that high-dose opioid prescribing and opioid prescribing in general has decreased, sustained efforts are needed to help providers adopt and maintain safe prescribing behaviors. The purpose of this four-year type 2 effectiveness-implementation hybrid stepped wedge cluster randomized trial is to: (1) compare the clinical and cost effectiveness of electronic medical record-based clinical decision support [EMR-CDS] versus additional integrated, collaborative behavioral health [EMR-CDS + BHI-CCM] for opioid management of patients with co-morbid chronic non-cancer pain with depression or anxiety; and (2) examine facilitators and barriers to implementing these interventions within 35 primary care clinics in a integrated delivery health system. The EMR-CDS alerts providers to employ opioid risk mitigation and safe prescribing practices at the point of care. The BHI-CCM consists of primary care embedded community health workers for case management; licensed clinical social workers for cognitive behavioral therapy, and a clinical pharmacist for medication management who provide care management via telemedicine (virtual video or audio only visits) under the guidance of a consulting psychiatrist. The primary outcome is reduction in the percentage of patients with average daily opioid dose ≥50 mg morphine equivalent. Secondary outcomes include changes in service utilization, patient reported outcomes and processes of care. The investigators anticipate that study results will elucidate the role of technology versus care team optimization in changing opioid prescribing behaviors. The investigators further anticipate that integrated mental/behavioral health care will increase value-based care and the efficiency with which guideline concordant care is delivered.

Chronic diseases impact 117 million adults in the United States and account for $3.3 trillion in health care spending. This qualitative study investigated experiences with reimbursement structure for non-face-to-face (NFF) chronic care management (CCM) through diverse health system approaches in primary care settings in Southeastern Louisiana. In-depth interviews were conducted with 16 purposively selected key informants, and reflexive thematic analysis was utilized to explore findings. Variation in health system approaches for implementing and quality of NFF CCM programs were identified. Results included differences in health system motivation and methods for financial structuring and quality of third-party vendor and alternative models.

Background We compared the efficacy of the antiviral agent, remdesivir, versus standard-of-care treatment in adults with severe coronavirus disease 2019 (COVID-19) using data from a phase 3 remdesivir trial and a retrospective cohort of patients with severe COVID-19 treated with standard of care. Methods GS-US-540–5773 is an ongoing phase 3, randomized, open-label trial comparing two courses of remdesivir (remdesivir-cohort). GS-US-540–5807 is an ongoing real-world, retrospective cohort study of clinical outcomes in patients receiving standard-of-care treatment (non-remdesivir-cohort). Inclusion criteria were similar between studies: patients had confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, were hospitalized, had oxygen saturation ≤94% on room air or required supplemental oxygen, and had pulmonary infiltrates. Stabilized inverse probability of treatment weighted multivariable logistic regression was used to estimate the treatment effect of remdesivir versus standard of care. The primary endpoint was the proportion of patients with recovery on day 14, dichotomized from a 7-point clinical status ordinal scale. A key secondary endpoint was mortality. Results After the inverse probability of treatment weighting procedure, 312 and 818 patients were counted in the remdesivir- and non-remdesivir-cohorts, respectively. At day 14, 74.4% of patients in the remdesivir-cohort had recovered versus 59.0% in the non-remdesivir-cohort (adjusted odds ratio [aOR] 2.03: 95% confidence interval [CI]: 1.34–3.08, P < .001). At day 14, 7.6% of patients in the remdesivir-cohort had died versus 12.5% in the non-remdesivir-cohort (aOR 0.38, 95% CI: .22–.68, P = .001). Conclusions In this comparative analysis, by day 14, remdesivir was associated with significantly greater recovery and 62% reduced odds of death versus standard-of-care treatment in patients with severe COVID-19. Clinical Trials Registration NCT04292899 and EUPAS34303.

Using a novel recruitment method to reduce selection bias with paired molecular and antibody testing for SARS-CoV-2 infection, we determined point prevalence in a racially diverse municipality. Infections were highly variable by ZIP and differed by race. Overall census-weighted prevalence was 7.8% and the calculated infection fatality rate was 1.63%.

Aims: This study compares the cardiovascular benefits between SGLT2 inhibitors and other glucose-lowering drugs (oGLDs) based on electronic medical record data from a large integrated delivery health system in South Louisiana. Materials and Methods: Demographic, anthropometric, laboratory and medication prescription information for patients with type 2 diabetes who were new users of SGLT2 inhibitors either as initial treatments or as add-on treatments were obtained from electronic health records. Mediation analysis was performed in demonstrating the association of use of SGLT2 inhibitors and changes of metabolic risk factors with the risk of incident coronary heart disease. Results: A total of 5,338 new users of SGLT2 inhibitors were matched with 13,821 patients using oGLDs. During a mean follow up of 3.26 years, 2,303 incident cases of coronary heart disease were defined. After adjusting for multiple confounding factors, patients using SGLT2 inhibitors had a lower risk of incident coronary heart disease compared to patients using oGLDs (hazard ratio [HR] 0.63; 95% confidence interval [CI] 0.55-0.72). Patients using SGLT2 inhibitors also had a lower risk of incident coronary heart disease within 6 months (HR 0.32; 95% CI 0.23-0.43), 12 months (HR 0.38; 95% CI0.31-0.48), 24 months (HR 0.49; 95% CI 0.41-0.59) and 36 months (HR 0.59; 95% CI 0.51-0.69), respectively. Reductions in systolic blood pressure attributed the lower risk of coronary heart disease among patients using SGLT2 inhibitors. Conclusions: Evidence from real world data indicated the contribution of SGLT2 inhibitors to reducing risk of coronary heart disease, as well as the benefits beyond glucose-lowering. Disclosure Y. Shen: None. J. Zhou: None. L. Shi: None. E. Nauman: None. P.T. Katzmarzyk: None. E.G. Price-Haywood: None. S. Chu: None. S. Yang: None. A.N. Bazzano: None. S. Nigam: None. G. Hu: None.

Background and Purpose— Few studies have assessed the association of HDL (high-density lipoprotein) cholesterol with stroke risk among patients with type 2 diabetes mellitus. We aimed to investigate the association of HDL cholesterol with total and type-specific stroke risk in patients with type 2 diabetes mellitus. Methods— We performed a retrospective cohort study of 27 113 blacks and 40 431 whites with type 2 diabetes mellitus. Cox proportional hazards regression models were used to estimate the association of different levels of HDL cholesterol with stroke risk. Results— During a mean follow-up period of 3.0 years, 8496 patients developed stroke (8048 ischemic and 448 hemorrhagic). Multivariable-adjusted hazard ratios across levels of HDL at baseline (P trend P trend P trend =0.021) for hemorrhagic stroke, respectively. When we used an updated mean value of HDL cholesterol, the inverse association of HDL cholesterol with stroke risk did not change. This inverse association was consistent among patients of different ages, races, sexes, body mass index, hemoglobin A1c levels, never and past or current smokers, and patients with and without using glucose-lowering, cholesterol-lowering, or antihypertensive agents. Conclusions— The present study found consistent inverse associations between HDL cholesterol and the risk of total, ischemic and hemorrhagic stroke among patients with type 2 diabetes mellitus.

Background Obesity affects nearly half of adults in the United States and is contributing substantially to a pandemic of obesity-associated chronic conditions such as type 2 diabetes, hypertension, and arthritis. The obesity-associated chronic condition pandemic is particularly severe in low-income, medically underserved, predominantly African-American areas in the southern United States. Little is known regarding the impact of geographic, income, and racial disparities in continuity of care on major health outcomes for patients with obesity-associated chronic conditions. Objective The aim of this study is to assess, among patients with obesity-associated chronic conditions, and within this group, patients with type 2 diabetes, (1) whether continuity of care is associated with lower overall and potentially preventable emergency department and hospital utilization, (2) the effect of geographic, income, and racial disparities on continuity of care and on health care utilization, (3) whether continuity of care particularly protects individuals at risk for disparities from adverse health outcomes, and (4) whether characteristics of health systems are associated with higher continuity of care and better outcomes. Methods Using 2015-2018 data from 4 practice-based research networks participating in the Southern Obesity and Diabetes Coalition, we will conduct a retrospective cohort analysis and distributed meta-analysis. Patients with obesity-associated chronic conditions and with type 2 diabetes will be assessed within each health system, following a standardized study protocol. The primary study outcomes are overall and preventable emergency department visits and hospitalizations. Continuity of care will be calculated at the facility level using a modified version of the Bice-Boxerman continuity of care index. Race will be assessed using electronic medical record data. Residence in a low-income area or a health professional shortage area respectively will be assessed by linking patient residence ZIP codes to the Centers for Medicare & Medicaid Services database. Results In 4 regional health systems across Tennessee, Mississippi, Louisiana, and Arkansas, a total of 53 adult hospitals were included in the study. A total of 147,889 patients with obesity-associated chronic conditions who met study criteria were identified in these health systems, of which 45,453 patients met the type 2 diabetes criteria for inclusion. Results are expected by the end of 2020. Conclusions This study should reveal whether health system efforts to increase continuity of care for patients with obesity and diabetes have potential to improve outcomes and reduce costs. Analyzing disparities in continuity of care and their effect on major health outcomes can help demonstrate how to improve care and use of health care resources for vulnerable patients with obesity-associated chronic conditions, and within this group, patients with type 2 diabetes. Better understanding of the association between continuity and health care utilization for these vulnerable populations will contribute to the development of higher-value health systems in the southern United States. International Registered Report Identifier (IRRID) DERR1-10.2196/20788

Background Many reports on coronavirus disease 2019 (Covid-19) have highlighted age- and sex-related differences in health outcomes. More information is needed about racial and ethnic differences in outcomes from Covid-19. Methods In this retrospective cohort study, we analyzed data from patients seen within an integrated-delivery health system (Ochsner Health) in Louisiana between March 1 and April 11, 2020, who tested positive for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2, the virus that causes Covid-19) on qualitative polymerase-chain-reaction assay. The Ochsner Health population is 31% black non-Hispanic and 65% white non-Hispanic. The primary outcomes were hospitalization and in-hospital death. Results A total of 3626 patients tested positive, of whom 145 were excluded (84 had missing data on race or ethnic group, 9 were Hispanic, and 52 were Asian or of another race or ethnic group). Of the 3481 Covid-19–positive patients included in our analyses, 60.0% were female, 70.4% were black non-Hispanic, and 29.6% were white non-Hispanic. Black patients had higher prevalences of obesity, diabetes, hypertension, and chronic kidney disease than white patients. A total of 39.7% of Covid-19–positive patients (1382 patients) were hospitalized, 76.9% of whom were black. In multivariable analyses, black race, increasing age, a higher score on the Charlson Comorbidity Index (indicating a greater burden of illness), public insurance (Medicare or Medicaid), residence in a low-income area, and obesity were associated with increased odds of hospital admission. Among the 326 patients who died from Covid-19, 70.6% were black. In adjusted time-to-event analyses, variables that were associated with higher in-hospital mortality were increasing age and presentation with an elevated respiratory rate; elevated levels of venous lactate, creatinine, or procalcitonin; or low platelet or lymphocyte counts. However, black race was not independently associated with higher mortality (hazard ratio for death vs. white race, 0.89; 95% confidence interval, 0.68 to 1.17). Conclusions In a large cohort in Louisiana, 76.9% of the patients who were hospitalized with Covid-19 and 70.6% of those who died were black, whereas blacks comprise only 31% of the Ochsner Health population. Black race was not associated with higher in-hospital mortality than white race, after adjustment for differences in sociodemographic and clinical characteristics on admission.

Objectives The growing body of evidence suggesting that lifestyle changes and aggressive medical management reduce the risk of strokes in patients with carotid stenosis has fostered interest in noninvasive screening. The objective of this study was to develop recommendations for follow-up carotid ultrasound surveillance of patients with Methods This retrospective observational cohort study includes 2956 patients seen between August 1998 and March 2015 in 4440 visits. Data analysis was restricted to 7710 carotid ultrasounds. Primary outcome was progression of carotid stenosis as defined by the “bulb” method: baseline stenosis of 0%–39% progressed to 40%–59% on subsequent examination, baseline stenosis of 0%–39% progressed to ≥60%, or baseline of 40%–59% progressed to ≥60%. Progression was estimated using Cox proportional hazard ratios and the Kaplan-Meier method. Results More than 10% of patients progressed in the 40%–59% baseline group within 12 months compared to 78 months for the 0%–39% baseline group. Patients who progressed had a higher proportion of peripheral vascular disease, and current/former smoking compared to those who did not. While there were statistically significant correlations between medication classes and comorbidities, none of the medications studied appeared to slow carotid stenosis progression. Conclusions In our experience, for patients with a 0%–39% carotid stenosis, follow-up examination should be performed at 6-year intervals. For patients with 40%–59% carotid stenosis, follow-up should be obtained annually to identify those who progress to a level requiring intervention. Future studies should examine whether study findings can be replicated using other approaches for determining carotid stenosis.

Diabetes and its comorbidities are leading causes of morbidity and mortality in the United States and disproportionately in Louisiana. Chronic care management (CCM) efforts, such as care coordination models, are important initiatives in mitigating the impact of diabetes, such as poorer health outcomes and increased costs. This study examined one such effort, the Centers for Medicare & Medicaid Services' non-face-to-face CCM reimbursement program, for patients with diabetes and at least 1 other chronic condition in Louisiana. This qualitative study included interviews with patients in this program and health care providers and system leaders implementing the program. Results include lessons learned from health system leadership relating to CCM design and implementation, challenges experienced, overlapping initiatives, perceived benefits, performance, billing, and health information technology. Another key finding is that co-pays seem to be a barrier to patient interest in participation in non-face-to-face CCM, especially given that the value of the program is not completely clear to patients. A common strategy to address this co-pay barrier is to target dual eligibles, as Medicaid will cover the co-pay. However, widespread use of such strategies may indirectly exclude individuals who need and may also benefit from non-face-to-face CCM.

Given the global and economic burden of stroke as a major cause of long-term disability, patient-reported outcomes (PRO) data from clinical trials can elucidate differential benefits/harms of interventions from patients’ perspectives and influence clinical decision making in stroke care management. This systematic review examines stroke-related randomized controlled trials (RCT) published in 12 high-impact journals between 2002 and 2016 for (1) associations between trial characteristics and the reporting of PRO measures; and (2) psychometric properties of PRO instruments used in these studies. The study combines clinical trials identified in a prior review with trials identified with an updated literature search. Only 34 of 159 stroke-related RCTs reported PRO measures. Among the 34 trials, most were published in rehabilitation and general medical journals, were conducted in the United States or Europe, were funded by government/non-industry sponsors, and focused on post-stroke care. Thirty-one PRO instruments were employed in these studies. Only 5 instruments were stroke-specific measures, whereas the remaining 26 instruments were generic measures. Eight instruments assessed functional status, 9 measured quality of life, and 14 assessed symptoms. The most common health domains measured were emotional status and physical function. This study highlights the paucity of information from patients’ perspective in stroke-related RCTs. This trend may change over time as researchers increase adherence to reporting guidelines for clinical trial protocols.

BACKGROUND: U.S. health systems, incentivized by financial penalties, are designing programs such as case management to reduce service utilization among high-cost, high-need populations. The major challenge is identifying patients for whom targeted programs are most effective for achieving desired outcomes. OBJECTIVE: To evaluate a health system’s outpatient complex case management (OPCM) for Medicare beneficiaries for patients overall and for high-risk patients using system-tailored taxonomy, and examine whether OPCM lowers service utilization and healthcare costs. DESIGN: Retrospective case-control study using Medicare data collected between 2012 and 2016 for Ochsner Health System. PARTICIPANTS: Super-utilizers defined as Medicare patients with at least two hospital/ED encounters within 180 days of the index date including the index event. INTERVENTION: Outpatient complex case management. MAIN MEASURES: Propensity score-adjusted multivariable logistic regression analysis was conducted for primary outcomes (90-day hospital readmission; 90-day ED re-visit). A difference-in-difference analysis was conducted to examine changes in per membership per month (PMPM) costs based on OPCM exposure. KEY RESULTS: Among 18,882 patients, 1197 (6.3%) were identified as “high-risk” and 470 (2.5%) were OPCM participants with median enrollment of 49 days. High-risk OPCM cases compared to high-risk controls had lower odds of 90-day hospital readmissions (0.81 [0.40–1.61], non-significant) and lower odds of 90-day ED re-visits (0.50 [0.32–0.79]). Non-high-risk OPCM cases compared to non-high-risk controls had lower odds of 90-day hospital readmissions (0.20 [0.11–0.36]) and 90-day ED re-visits (0.66 [0.47–0.94]). Among OPCM cases, high-risk patients compared to non-high-risk patients had greater odds of 90-day hospital readmissions (4.44 [1.87–10.54]); however, there was no difference in 90-day ED re-visits (0.99 [0.58–1.68]). Overall, OPCM cases had lower total cost of care compared to controls (PMPM mean [SD]: − $1037.71 [188.18]). CONCLUSIONS: Use of risk stratification taxonomy for super-utilizers can identify patients most likely to benefit from case management. Future studies must further examine which OPCM components drive improvements in select outcome for specific populations.

Underserved and minority populations suffer from a disproportionately high prevalence of obesity and related comorbidities. Effective obesity treatment programs delivered in primary care that produce significant weight loss are currently lacking. The purpose of this trial is to test the effectiveness of a pragmatic, high intensity lifestyle-based obesity treatment program delivered within primary care among an underserved population. We hypothesize that, relative to patients who receive usual care, patients who receive a high-intensity, health literacy- and culturally-appropriate lifestyle intervention will have greater percent reductions in body weight over 24 months. Eighteen clinics (N = 803 patients) serving low income populations with a high proportion of African Americans in Louisiana were randomized to the intervention or usual car. Patients in the intervention participate in a high-intensity lifestyle program delivered by health coaches employed by an academic health center and embedded in the primary care clinics. The program consists of weekly (16 in-person/6 telephone) sessions in the first six months, followed by sessions held at least monthly for the remaining 18 months. Primary care practitioners in usual care receive information on weight management and the current Centers for Medicare and Medicaid Services reimbursement for obesity treatment. The primary outcome is percent weight loss at 24 months. Secondary outcomes include absolute 24-month changes in body weight, waist circumference, blood pressure, fasting glucose and lipids, health-related quality of life, and weight-related quality of life. The results will provide evidence on the effectiveness of implementing high-intensity lifestyle and obesity counseling in primary care settings among underserved populations. Trial Registration: ClinicalTrials.gov Identifier NCT02561221

Objective Determine whether an individual is at greater risk of severe acute respiratory distress syndrome coronavirus 2 (SARS-CoV-2) infection because of their community or their individual risk factors. Study design and setting 4,752 records from two large prevalence studies in New Orleans and Baton Rouge, Louisiana were used to assess whether zip code tabulation areas (ZCTA)-level area deprivation index (ADI) or individual factors accounted for risk of infection. Logistic regression models assessed associations of individual-level demographic and socioeconomic factors and the zip code-level ADI with SARS-CoV-2 infection. Results In the unadjusted model, there were increased odds of infection among participants residing in high versus low ADI (both cities) and high versus mid-level ADI (Baton Rouge only) zip codes. When individual-level covariates were included, the odds of infection remained higher only among Baton Rouge participants who resided in high versus mid-level ADI ZCTAs. Several individual factors contributed to infection risk. After adjustment for ADI, race and age (Baton Rouge) and race, marital status, household size, and comorbidities (New Orleans) were significant. Conclusions While higher ADI was associated with higher risk of SARS-CoV-2 infection, individual-level participant characteristics accounted for a significant proportion of this association. Additionally, stage of the pandemic may affect individual risk factors for infection.

ObjectiveWe assessed changes in the percentage of providers with positive perceptions of electronic health record (EHR) benefit before and after transition from a local basic to a commercial comprehensive EHR.MethodsChanges in the percentage of providers with positive perceptions of EHR benefit were captured via a survey of academic health care providers before (baseline) and at 6–12 months (short term) and 12–24 months (long term) after the transition. We analyzed 32 items for the overall group and by practice setting, provider age, and specialty using separate multivariable-adjusted random effects logistic regression models.ResultsA total of 223 providers completed all 3 surveys (30% response rate): 85.6% had outpatient practices, 56.5% were >45 years old, and 23.8% were primary care providers. The percentage of providers with positive perceptions significantly increased from baseline to long-term follow-up for patient communication, hospital transitions – access to clinical information, preventive care delivery, preventive care prompt, preventive lab prompt, satisfaction with system reliability, and sharing medical information (P ConclusionAfter a transition to a commercial comprehensive EHR, items with significant increases and significant decreases in the percentage of providers with positive perceptions of EHR benefit were identified, overall and by subgroup.

BACKGROUND: Electronic health records (EHRs) and claims records are widely used in defining type 2 diabetes mellitus (T2DM) complications across different types of health care encounters. OBJECTIVE: This study investigates whether using different EHR encounter types to define diabetes complications may lead to different results when examining associations between diabetes complications and their risk factors in patients with T2DM. RESEARCH DESIGN: The study cohort of 64,855 adult patients with T2DM was created from EHR data from the Research Action for Health Network (REACHnet), using the Surveillance Prevention, and Management of Diabetes Mellitus (SUPREME-DM) definitions. Incidence of coronary heart disease (CHD) and stroke events were identified using International Classification of Diseases (ICD)-9/10 codes and grouped by encounter types: (1) inpatient (IP) or emergency department (ED) type, or (2) any health care encounter type. Cox proportional hazards regression was used to estimate associations between diabetes complications (ie, CHD and stroke) and risk factors (ie, low-density lipoprotein cholesterol and hemoglobin A1c). RESULTS: The incidence rates of CHD and stroke in all health care settings were more than twice the incidence rates of CHD and stroke in IP/ED settings. The age-adjusted and multivariable-adjusted hazard ratios for incident CHD and stroke across different levels of low-density lipoprotein cholesterol and hemoglobin A1c were similar between IP/ED and all settings. CONCLUSION: While there are large variations in incidence rates of CHD and stroke as absolute risks, the associations between both CHD and stroke and their respective risk factors measured by hazard ratios as relative risks are similar, regardless of alternative definitions.

Background: While many surveillance studies of seroprevalence to SARS-CoV-2 rely on remnant blood samples obtained as medical waste, representative, prospective collection allows for analysis of a representative cross-section of symptomatic and asymptomatic presentation of infection in the community. Louisiana, and particularly New Orleans, were hard-hit in the early phase of the pandemic, and an ongoing outbreak was occurring in Baton Rouge throughout July. Methods: A representative, cross-sectional sample of subjects from two cities in Louisiana were sent to testing sites to complete a verbal consent, survey, nasopharyngeal swab, and blood draw. Swabs were tested for active viral shedding (PCR) and blood was tested for immunoglobulin G (IgG) specific to SARS-CoV-2. Findings: Anosmia was extremely predictive for a positive test (40·6% of those with anosmia tested positive, OR: 13·6; CI 10·1, 18·3) and 47·3% of the sample experienced no symptoms at all. A lower quantity of virus was noted during the contagious phase of infection in asymptomatic compared to symptomatic individuals. Symptom presentation clustered into three groups; low/no symptoms (0·4±0·9 symptoms on average), highly symptomatic (7·5±1·9) or moderately symptomatic (4·0±1·5). The probability of reporting symptoms changed with age; those under age 60 had a >50% probability of reporting symptoms while those 60 years and older had

Background: Individuals infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) who do not report symptoms throughout the course of infection

This prospective cohort study examines the clinical effectiveness of electronic medical record clinical decision support (EMR CDS) for opioid prescribing.Data analysis included primary care patients with chronic opioid therapy for noncancer pain seen within an integrated health delivery system in Louisiana between January 2017 and October 2018. EMR CDS incorporated an opioid health maintenance tool to display the status of risk mitigation, and the medication order embedded the morphine equivalent daily dose (MEDD) calculator and a hyperlink to the Louisiana pharmacy drug monitoring program. Outcome measures included change in the average MEDD and rates of opioid risk mitigation, hospitalization, and emergency department use.Among 14 221 patients, 9% had prescriptions with an average MEDD ≥90 mg. There were no significant changes in MEDD after EMR CDS implementation. Increasing age, Charlson Comorbidity Index score, female sex, black non-Hispanic race, non-opioid pain medication co-prescriptions, and specialty referrals were associated with a lower odds of MEDD ≥90 (high-dose threshold). Medicare or self-pay, substance abuse history, and pain agreements were associated with increased odds of prescribing above this high-dose threshold. After incorporation of EMR CDS, patients had higher rates of urine drug screens (17% vs 7%) and naloxone prescriptions (3% vs 1%, all P.001). In addition, specialty referrals to physical or occupational therapy, orthopedics, neurology, and psychiatry or psychology increased in the postintervention period. Although emergency department use decreased (rate ratio 0.92; 95% confidence interval 0.89-0.95), hospitalization rates did not change.EMR CDS improved adherence to opioid risk mitigation strategies. Further research examining which practice redesign interventions effectively reduce high-dose opioid prescribing is needed.

Context Very few studies focused on the association between body mass index (BMI) and stroke risk among patients with diabetes. Objective We aimed to investigate the association between BMI and stroke risk in patients with type 2 diabetes. Design Demographic, anthropometric, laboratory, and medication information were extracted from the National Patient-Centered Clinical Research Network common data model. Participants We performed a retrospective cohort study of 67 086 patients with type 2 diabetes. Main Outcome Measures Incident stroke including both ischemic and hemorrhagic stroke were defined. Results During a mean follow up of 3.74 years. 8918 incident stroke events occurred. Multivariable-adjusted hazard ratios across different categories of BMI at baseline (18.5–24.9 [reference group], 25.0–29.9, 30.0–34.9, 35.0–39.9, and ≥40 kg/m2) were 1.00, 0.92, 0.85, 0.74, and 0.63 (Ptrend Conclusion The present study found an inverse association between BMI and the risk of total, ischemic, and hemorrhagic stroke among patients with type 2 diabetes. More clinical and molecular insights are still needed in explaining these findings.

Background and Purpose The association between hemoglobin A1c (HbA1c) and stroke risk along with its subtypes is rarely reported. We aimed to investigate the association between HbA1c and the risk of incident stroke in patients with type 2 diabetes based on real world data from three healthcare systems.Methods We performed a retrospective cohort study of 27,113 African Americans and 40,431 whites with type 2 diabetes. Demographic, anthropometric, laboratory, and medication information were abstracted from the National Patient-Centered Clinical Research Network common data model. Incident stroke events including both ischemic and hemorrhagic stroke were defined.Results During a mean follow-up period of 3.79±1.68 years, 7,735 patients developed stroke (6,862 ischemic and 873 hemorrhagic). Multivariable-adjusted hazard ratios across levels of HbA1c at baseline (Ptrend Ptrend Ptrend=0.002) for hemorrhagic stroke. When we used an updated mean value of HbA1c, the U-shaped association of HbA1c with stroke risk did not change. This U-shaped association was consistent among patients of different subgroups. The U-shaped association was more pronounced among patients taking antidiabetic, lipid-lowering, and antihypertensive medications compared with those without these medications.Conclusions These data suggest that diabetes management may have to be individualized according to the guideline recommendations rather than intensively attempting to lower HbA1c.

This study investigated associations between cardiovascular health (CVH), adiposity, and food insecurity by race, sex, and health literacy in a sample of 800 underserved patients with obesity (body mass index [BMI] &ge, 30 kg/m2). CVH was assessed using American Heart Association Life&rsquo, s Simple 7 (LS7) and adiposity was estimated using BMI and waist circumference (WC). Mixed models including interaction terms between food insecurity and sex, race, and health literacy were analyzed for LS7, BMI, and WC. Stratified models were analyzed as indicated by significant interactions. Mean BMI and WC were 37.3 kg/m2 (4.6 SD) and 113.5 cm (12.4 SD), respectively. Among patients, 31% were food insecure and 31% had low health literacy. There were significant positive associations between food insecurity and BMI (p = 0.03) and WC (p = 0.03) in the overall sample. In sex-stratified models, women who were food insecure had higher BMI (p = 0.02) and WC (p = 0.007) than their food secure counterparts. Further, food insecure patients with better health literacy had greater BMI (p = 0.004) and WC (p = 0.007) than their food secure counterparts. Results suggest that adiposity is a greater burden in food insecure patients, which may be an important consideration for obesity treatment in underserved populations.

OBJECTIVES: Investigate differences in the associations between adiposity, cardiovascular health (CVH), and food insecurity by key social determinants (sex, race, and health literacy) in a sample of underserved patients. METHODS: The sample included 800 patients (21–74 years old; 67% African American; 84% female) with obesity (body mass index [BMI] ≥ 30). Adiposity was assessed using BMI and waist circumference (WC). CVH was assessed using the American Heart Association Life's Simple 7. Food insecurity was determined by the 6-Item Food Security Survey. Health literacy was measured using the REALM-SF. Mixed models with interaction terms between food insecurity and sex, race, and health literacy were analyzed for BMI, WC, and CVH. Stratified models were then analyzed as indicated by significant interaction terms. RESULTS: Mean BMI, WC, and CVH were 37.3 kg/m(2) (±4.6), 113.5 cm (±12.4), 6.7 (±1.9), respectively. Thirty-one % of patients were food insecure and 31% had low health literacy. Significant food insecurity by sex interactions were seen for adiposity. Sex-stratified models showed women who were food insecure had greater BMI (38.2 vs. 37.2 kg/m(2); P = 0.02) and WC (114.0 vs 111.2 cm; P = 0.007) than food secure counterparts, but associations were not significant in men. Significant food insecurity by health literacy interactions were also seen for adiposity. Health literacy-stratified models showed food insecure participants with better health literacy had greater BMI (39.1 vs. 37.7 kg/m(2); P = 0.004) and WC (121.7 vs. 118.2 cm; P = 0.007) than food secure counterparts, but associations were not significant in those with low health literacy. No significant interactions were observed for race. CONCLUSIONS: Significant differences in adiposity were seen in food insecure vs. food secure women, as well as in food insecure vs. food secure patients with better health literacy. These data suggest that adiposity is a greater burden in food insecure patients and may pose challenges for obesity treatment in underserved populations. FUNDING SOURCES: This research was supported by the PCORI (#OB-1402–10,977), the NIGMS of the NIH that funds the Louisiana Clinical and Translational Science Center (1 U54 GM104940), and NORC Center Grant “Nutrition and Metabolic Health Through the Lifespan” sponsored by NIDDK (#P30DK072476).

Clinical findings regarding the association between hemoglobin A1c (HbA1c) and stroke risk remain inconclusive, especially among patients with diabetes. We aimed to investigate the association between HbA1c and the risk of incident stroke in patients with type 2 diabetes using electronic medical record data from three large healthcare systems in Louisiana. We performed a retrospective cohort study of 27,113 African Americans and 40,431 whites with type 2 diabetes. Cox proportional hazards regression models were used to estimate the association of different levels of HbA1c with stroke risk. During a mean follow-up period of 3.74 years, 8986 patients developed stroke (8438 ischemic and 548 hemorrhagic). Multivariable-adjusted hazard ratios across levels of HbA1c at baseline ( Disclosure Y. Shen: None. L. Shi: None. E. Nauman: None. P. Katzmarzyk: None. E.G. Price-Haywood: None. A.N. Bazzano: None. S. Nigam: None. G. Hu: None. Funding Patient-Centered Outcomes Research Institute (NEN-1508-32257); National Institute of General Medical Sciences (U54GM104940 to G.H., P.K.)

This real-world retrospective observational analysis was conducted using data from REACHnet, a U.S. regional electronic medical records (EMR) database. Glycemic outcomes after simultaneous or sequential initiation of basal insulin (BI) and a glucagon-like peptide-1 receptor agonist (GLP-1 RA) were evaluated in patients with T2D uncontrolled (A1C ≥7.0%) on oral antidiabetes drugs (OADs). Three patient cohorts were defined: simultaneous BI and GLP-1 RA initiation (Cohort 1; n=109); initiation of BI followed by a GLP-1 RA with a gap of ≤90 days (Cohort 2; n=301); and initiation of BI followed by a GLP-1 RA with a gap of >90 days (Cohort 3; n=459). Baseline mean A1C was very similar across the cohorts (10.3%, 10.3%, and 10.2% in Cohorts 1, 2, and 3, respectively), as were comorbidities including dyslipidemia, hypertension, and obesity. Mean A1C decreased in all 3 cohorts in the 12 months from the date of first BI injection. The greatest mean A1C reductions occurred within 6 months of simultaneous administration (Cohort 1: -2.18%), followed by addition of a GLP-1 RA within 90 days (Cohort 2: -1.77%) and after 90 days (Cohort 3: -1.24%). Results at 12 months were Cohort 1: -1.66%; Cohort 2: -1.46%; and Cohort 3: -1.32%. Persistence (i.e., non-discontinuation of index treatments) at 12 months was 74.3%, 73.8%, and 80.0% in Cohorts 1, 2, and 3, respectively. Simultaneous initiation resulted in more patients achieving A1C In conclusion, this retrospective analysis of real-world EMR data in patients with T2D uncontrolled on OADs suggests that simultaneous initiation of BI and a GLP-1 RA resulted in significantly better glycemic control than sequential initiation with a gap of >90 days. Disclosure X.V. Peng: Employee; Self; Sanofi. Stock/Shareholder; Spouse/Partner; AbbVie Inc. Stock/Shareholder; Self; AbbVie Inc., Sanofi. R. Ayyagari: Consultant; Self; Sanofi US. Other Relationship; Self; Various pharmaceutical companies. R. Lubwama: Employee; Self; Merck & Co., Inc., Sanofi. M.J. Van Vleet: Employee; Self; Sanofi US. L. Shi: None. E.G. Price-Haywood: None. P. Hollander: Advisory Panel; Self; Novo Nordisk Inc. V. Fonseca: Board Member; Self; American Association of Clinical Endocrinologists. Consultant; Self; Abbott, Asahi Kasei Corporation, Novo Nordisk Inc., Sanofi US, Takeda Pharmaceutical Company Limited. Research Support; Self; Bayer US. Stock/Shareholder; Self; Amgen Inc., BRAVO4HEALTH, Mellitus Health. Funding Sanofi U.S.

Background PCSK9 (proprotein convertase subtilisin/kexin type 9) inhibitors effectively lower LDL (low‐density lipoprotein) cholesterol and have been shown to reduce cardiovascular outcomes in high‐risk patients. We used real‐world electronic health record data to characterize use of PCSK9 inhibitors, in addition to standard therapies, according to cardiovascular risk status. Methods and Results Data were obtained from 18 health systems with data marts within the National Patient‐Centered Clinical Research Network (PCORnet) using a common data model. Participating sites identified >17.5 million adults, of whom 3.6 million met study criteria. Patients were categorized into 3 groups: (1) dyslipidemia, (2) untreated LDL ≥130 mg/dL, and (3) coronary artery disease or coronary heart disease. Demographics, comorbidities, estimated 10‐year atherosclerotic cardiovascular disease risk, and lipid‐lowering pharmacotherapies were summarized for each group. Participants’ average age was 62 years, 50% were female, and 11% were black. LDL cholesterol ranged from 85 to 151 mg/dL. Among patients in groups 1 and 3, 54% received standard lipid‐lowering therapies and a PCSK9 inhibitor was prescribed in Conclusions We successfully used electronic health record data from 18 PCORnet data marts to identify >3.6 million patients meeting criteria for 3 patient groups. Approximately half of patients had been prescribed lipid‐lowering medication, but