Temporal trends in cardiovascular outcomes and costs among patients with type 2 diabetes.

BACKGROUND: Type 2 diabetes (T2D) is a strong risk factor for cardiovascular (CV) disease. CV outcomes in T2D have generally been improving over time but recent data from the US suggest attenuation of trends in older adults with reversal of trends in younger adults. However, published data are only reported through 2015. OBJECTIVES: To quantify trends over time in CV outcomes from 2001 to 2018, and describe changes over time in health care costs in T2D. METHODS: This retrospective cohort study incorporated data from a regional health insurance plan. Study outcomes included acute myocardial infarction (AMI), ischemic stroke, hemorrhagic stroke, heart failure hospitalization (HFH), percutaneous coronary intervention, coronary artery bypass surgery, and all-cause mortality. Poisson regression estimated rate ratios across the entire 17-year study period (RR17). RESULTS: Among 79,392 T2D members tracked on average 4.1 years, overall trends in AMI (RR17 = 0.69; 95% CI: 0.64, 0.74), HFH (RR17 = 0.82; 0.79, 0.86), and all-cause mortality (RR17 = 0.87; 0.84, 0.91) improved while ischemic stroke (RR17 = 2.36; 2.16, 2.57) worsened. For AMI, HFH, and all-cause mortality, trends in older age groups were significantly better than in younger age groups (interaction P-values < .001). Health care costs related to pharmaceuticals (+15%/year) and emergency department (ED) visits (>15%/year) increased at faster rates than other utilization metrics (+10%/year). CONCLUSIONS: In T2D, overall trends in most CV outcomes improved but smaller improvements or worsening trends were observed in younger patients. Health care costs accelerated at faster rates for medications and ED visits.

Evaluation of weight change and cardiometabolic risk factors in a real-world population of US adults with overweight or obesity.

Whether individuals in real-world settings are able to lose weight and improve cardiometabolic risk factors over time is unclear. We aimed to determine the management of and degree of body weight change over 2 years among individuals with overweight or obesity, and to assess associated changes in cardiometabolic risk factors and clinical outcomes. Using data from 11 large health systems within the Patient-Centered Outcomes Research Network in the U.S., we collected the following data on adults with a recorded BMI ≥25 kg/m2 between January 1, 2016 and December 31, 2016: body-mass index (BMI), systolic blood pressure (SBP), diastolic blood pressure (DBP), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDLC), triglycerides and glycated hemoglobin (HbA1c). We found that among 882,712 individuals with BMI ≥25 kg/m2 (median age 59 years; 56% female), 52% maintained stable weight over 2 years and 1.3% utilized weight loss pharmacotherapy. Weight loss of 10% was associated with small but significant lowering of mean SBP (-2.69 mmHg [95% CI -2.88, -2.50]), DBP (-1.26 mmHg [95% CI -1.35, -1.18]), LDL-C (-2.60 mg/dL [95% CI -3.14, -2.05]), and HbA1c (-0.27% [95% CI -0.35, -0.19]) in the same 12 months. However, these changes were not sustained over the following year. In this study of adults with BMI ≥25 kg/m2, the majority had stable weight over 2 years, pharmacotherapies for weight loss were under-used, and small changes in cardiometabolic risk factors with weight loss were not sustained, possibly due to failure to maintain weight loss.

Clinical and Cost Benefits of Anti-Obesity Medication for US Veterans Participating in the MOVE! Weight Management Program.

Abstract This study investigated the clinical and economic impact of anti-obesity medications (AOMs; orlistat, liraglutide, phentermine/topiramate extended-release [ER], naltrexone ER/bupropion ER) among United States Veterans with obesity participating in Motivating Overweight/Obese Veterans Everywhere! (MOVE!), a government-initiated weight management program. The study population was identified from electronic medical records of the Veterans Health Administration (2010-2020). Clinical indices of obesity and health care resource utilization and costs were evaluated at 6, 12, and 24 months after the initial dispensing of an AOM in the AOM+MOVE! cohort (N = 3732, mean age 57 years, 79% male) or on the corresponding date of an inpatient or outpatient encounter in the MOVE! cohort (N = 7883, mean age 58 years, 81% male). At 6 months postindex, the AOM+MOVE! cohort had better cardiometabolic indices (eg, systolic blood pressure, diastolic blood pressure, total cholesterol, low-density lipoprotein cholesterol, hemoglobin A1c) than the MOVE! cohort, with the trends persisting at 12 and 24 months. The AOM+MOVE! cohort was significantly more likely than the MOVE! cohort to have weight decreases of 5%-10%, 10%-15%, and >15% and lower body mass index at 6, 12, and 24 months. The AOM+MOVE! cohort also had fewer inpatient and emergency department visits than the MOVE! cohort, which was associated with lower mean total medical costs including inpatient costs. These results suggest that combining AOM treatment with the MOVE! program could yield long-term cost savings for the Veterans Affairs network and meaningful clinical improvements for Veterans with obesity.

Cost-effectiveness analysis of semaglutide 2.4 mg for the treatment of adult patients with overweight and obesity in the United States.

BACKGROUND: The rising prevalence and associated public health burden of obesity has led to advancements in pharmaceuticals for weight management. Semaglutide 2.4 mg, an anti-obesity medication (AOM) recently approved by the US Food and Drug Administration, has demonstrated clinically relevant weight loss in its phase 3 clinical trials. Economic evaluation comparing semaglutide 2.4 mg with other available weight management therapies is essential to inform payers for decision-making. OBJECTIVES: To assess the cost-effectiveness of semaglutide 2.4 mg in the treatment of adult patients with obesity (ie, body mass index [BMI] ≥ 30) and adult patients who are overweight (ie, BMI 27-29.9) with 1 or more weight-related comorbidities from a US third-party payer perspective. METHODS: A cohort Markov model was constructed to compare semaglutide 2.4 mg with the following comparators: no treatment, diet and exercise (D&E), and 3 branded AOMs (liraglutide 3 mg, phentermine-topiramate, and naltrexone-bupropion). All AOMs, including semaglutide 2.4 mg, were assumed to be taken in conjunction with D&E. Changes in BMI, blood pressure, cholesterol level, experience of acute and chronic obesity-related complications, costs, and quality-adjusted life years (QALYs) were simulated over 30 years based on pivotal trials of the AOMs and other relevant literature. Drug and health care prices reflect 2021 standardized values. Cost-effectiveness was examined with a willingness-to-pay (WTP) threshold of $150,000 per QALY gained. Sensitivity analyses were conducted to test the robustness of the cost-effectiveness results to plausible variation in model inputs. RESULTS: In the base-case analysis, treatment with semaglutide 2.4 mg was estimated to improve QALYs by 0.138 to 0.925 and incur higher costs by $3,254 to $25,086 over the 30-year time horizon vs comparators. Semaglutide 2.4 mg is cost-effective against all comparators at the prespecified WTP threshold, with the incremental cost per QALY gained ranging from $23,556 to $144,296 per QALY gained. In the sensitivity analysis, extended maximum treatment duration, types of subsequent treatment following therapy discontinuation, and weight-rebound rates were identified as key drivers for model results. The estimated probability of semaglutide 2.4 mg being cost-effective compared with comparators ranged from 67% to 100% when varying model parameters and assumptions. CONCLUSIONS: As a long-term weight management therapy, semaglutide 2.4 mg was estimated to be cost-effective compared with no treatment, D&E alone, and all other branded AOM comparators under a WTP threshold of $150,000 per QALY gained over a 30-year time horizon. DISCLOSURES: Financial support for this research was provided by Novo Nordisk Inc. The study sponsor was involved in several aspects of the research, including the study design, the interpretation of data, the writing of the manuscript, and the decision to submit the manuscript for publication. Dr Kim and Ms Ramasamy are employees of Novo Nordisk Inc. Ms Kumar and Dr Burudpakdee were employees of Novo Nordisk Inc at the time this study was conducted. Dr Sullivan received research support from Novo Nordisk Inc for this study. Drs Wang, Song, Wu, Ms Xie, and Ms Sun are employees of Analysis Group, Inc, who received consultancy fees from Novo Nordisk Inc in connection with this study.

Changes over time in the cardiovascular risk profile of type 2 diabetes from 2007 to 2020: A community-based study.

AIMS: To quantify changes over time in cardiovascular (CV) risk factor control and in the uptake of glucagon-like peptide-1 receptor agonists (GLP-1RAs) and sodium-glucose cotransporter-2 (SGLT2) inhibitors from 2007 to 2020 in a real-world community-based cohort of type 2 diabetes (T2D) patients. MATERIALS AND METHODS: This study identified 95 461 T2D patients, who were followed for an average of 6.4 years through a single healthcare organization's electronic health record. The primary outcome was global risk factor control according to four factors ("ABCS"): glycated haemoglobin (HbA1c [<8%]); Blood pressure (systolic/diastolic <140/90 mmHg); Cholesterol (non-HDL cholesterol <130 mg/dL); and Smoking (not). Concomitant presence of microvascular complications and commonly used medication classes were tracked. RESULTS: According to the ABCS metric, global risk factor control did not appreciably change over time; in 2020, 40.9% (95% confidence interval 40.2, 41.5) of patients had all four factors controlled. Among individual components, HbA1c control (<8%) worsened over time from 84% in 2007 to 78% in 2020, while lipid control (non-HDL cholesterol <130 mg/dL) improved from 59% to 72%. Coexisting microvascular complications were more prevalent over time; for example, neuropathy prevalence increased from 21% (2007) to 35% (2020). Use of thiazolidinediones and sulphonylureas decreased over time while metformin, insulin, dipeptidyl peptidase-4 inhibitor, GLP-1RA and SGLT2 inhibitor use increased. In 2020, GLP-1RAs and SGLT2 inhibitors were each used by 13% of T2D patients. CONCLUSIONS: In this community-based study, global CV risk factor control in T2D did not improve, although glycaemic control worsened and lipid control improved. Given increased uptake of GLP-1RAs and SGLT2 inhibitors, the collective effect of these changes on CV outcomes warrants evaluation.

Impact of Sustained Weight Loss on Cardiometabolic Outcomes.

Obesity increases the risk of developing type 2 diabetes, hypertension, and hyperlipidemia. We sought to determine the impact of obesity maintenance, weight regain, weight loss maintenance, and magnitudes of weight loss on future risk and time to developing these cardiometabolic conditions. This was a retrospective cohort study of adults receiving primary care at Geisinger Health System between 2001 and 2017. Using electronic health records, patients with ≥3-weight measurements over a 2-year index period were identified and categorized. Obesity maintainers (OM) had obesity (body mass index ≥30 kg/m²) and maintained their weight within ±3% from baseline (reference group). Both weight loss rebounders (WLR) and weight loss maintainers (WLM) had obesity at baseline and lost >5% body weight in year 1; WLR regained ≥20% of weight loss by end of year 2 and WLM maintained ≥80% of weight loss. Incident type 2 diabetes, hypertension, and hyperlipidemia, and time-to-outcome were determined for each study group and by weight loss category for WLM. Of the 63,567 patients included, 67% were OM, 19% were WLR, and 14% were WLM. The mean duration of follow-up was 6.6 years (SD, 3.9). Time until the development of electronic health record-documented type 2 diabetes, hypertension, and hyperlipidemia was longest for WLM and shortest for OM (log-rank test p <0.0001). WLM had the lowest incident type 2 diabetes (adjusted hazard ratio [HR] 0.676 [95% confidence interval [CI] 0.617 to 0.740]; p <0.0001), hypertension (adjusted HR 0.723 [95% CI 0.655 to 0.799]; p <0.0001), and hyperlipidemia (adjusted HR 0.864 [95% CI 0.803 to 0.929]; p <0.0001). WLM with the greatest weight loss (>15%) had a longer time to develop any of the outcomes compared with those with the least amount of weight loss (<7%) (p <0.0001). In an integrated delivery network population, sustained weight loss was associated with a delayed onset of cardiometabolic diseases, particularly with a greater magnitude of weight loss.

Retrospective descriptive analysis of a managed care population with obesity.

OBJECTIVES: To reveal the extent of obesity in a single healthcare system and provide a blueprint for other health systems to perform similar analyses, this study describes characteristics and weight change patterns of patients classified with overweight and obesity at a large integrated delivery network (IDN) in the South-Central United States. METHODS: A descriptive, observational, retrospective study was conducted using electronic medical records and claims data. Patients were ≥18 years old, body mass index (BMI) ≥27 kg/m2, and continuously enrolled in the IDN plan for ≥6 months before and ≥12 months after the index date. Demographics, comorbidities, BMI, and weight were collected. Weight changes were assessed annually, and anti-obesity medications (AOM) use was also captured. RESULTS: A total of 36,430 eligible patients were identified. A subset of 22,712 patients was continuously enrolled for the entire study period (mean age: 57.2) and were primarily white (83.3%) and commercially insured (54.3%). Most patients were categorized as overweight (40.1%) or obesity class I (32.5%) at baseline. At years 1 and 4 post-index, patients who maintained index weight (±3%) was 56.2% and 37.0%, respectively, whereas weight gain (≥3% increase) was 23.7% and 33.3%, respectively. AOM use (1.1%) primarily consisted of phentermine-hydrochloride (n = 114, 0.5%) and orlistat (n = 115, 0.5%). CONCLUSIONS: An increasing proportion of patients gained weight over time, combined with low AOM use, emphasizing the need for weight-loss interventions in this population. Findings from this study provide a foundation for health systems to perform similar analyses.

Effects of sustained weight loss on outcomes associated with obesity comorbidities and healthcare resource utilization.

OBJECTIVE: Determine the impact of long-term non-surgical weight loss maintenance on clinical relevance for osteoarthritis, cancer, opioid use, and depression/anxiety and healthcare resource utilization. METHODS: A cohort of adults receiving primary care within Geisinger Health System between 2001-2017 was retrospectively studied. Patients with ≥3 weight measurements in the two-year index period and obesity at baseline (BMI ≥30 kg/m2) were categorized: Obesity Maintainers (reference group) maintained weight within +/-3%; Weight Loss Rebounders lost ≥5% body weight in year one, regaining ≥20% of weight loss in year two; Weight Loss Maintainers lost ≥5% body weight in year one, maintaining ≥80% of weight loss. Association with development of osteoarthritis, cancer, opioid use, and depression/anxiety, was assessed; healthcare resource utilization was quantified. Magnitude of weight loss among maintainers was evaluated for impact on health outcomes. RESULTS: In total, 63,567 patients were analyzed including 67% Obesity Maintainers, 19% Weight Loss Rebounders, and 14% Weight Loss Maintainers; median follow-up was 9.7 years. Time until osteoarthritis onset was delayed for Weight Loss Maintainers compared to Obesity Maintainers (Logrank test p <0.0001). Female Weight Loss Maintainers had a 19% and 24% lower risk of developing any cancer (p = 0.0022) or obesity-related cancer (p = 0.0021), respectively. No significant trends were observed for opioid use. Weight loss Rebounders and Maintainers had increased risk (14% and 25%) of future treatment for anxiety/depression (both <0.0001). Weight loss maintenance of >15% weight loss was associated with the greatest decrease in incident osteoarthritis. Healthcare resource utilization was significantly higher for Weight Loss Rebounders and Maintainers compared to Obesity Maintainers. Increased weight loss among Weight Loss Maintainers trended with lower overall healthcare resource utilization, except for hospitalizations. CONCLUSIONS: In people with obesity, sustained weight loss was associated with greater clinical benefits than regained short-term weight loss and obesity maintenance. Higher weight loss magnitudes were associated with delayed onset of osteoarthritis and led to decreased healthcare utilization.

The Association Between Structural, Performance, and Community Factors and the Likelihood of Receiving a Penalty Under the Hospital Readmissions Reduction Program (Fiscal Year 2013-2019).

Purpose: Little is known about the role of structural, performance, and community factors that impact the likelihood of receiving a penalty under the Hospital Readmission Reduction Program. This study examined the association between structural, performance, and community factors and the likelihood of receiving a penalty as well as investigated the likelihood of hospitals serving vulnerable populations of receiving a penalty. Methods: Centers for Medicare and Medicaid Services and United States Census Bureau data were used in this analysis. Ordered logistic regressions in a cross-sectional analysis were employed to estimate the probability of receiving a high or low penalty in the fiscal year 2013 through 2019. Results: On average, medium-sized, major teaching, and safety-net hospitals had the highest proportion of hospitals with a high penalty. After controlling for performance and community factors, structural factor variables such as safety-net status, rural status, and teaching status either were no longer significant or the likelihood magnitude changed. However, after controlling for performance and community factors, the statistical significance of hospital size variables and geographic location persisted across the years. Length of stay and occupancy rate variables were also statistically significant across the 7 years under review. Conclusion: Taken together, structural, performance, and community factors are important in explaining variation in the likelihood of receiving a penalty. There is no evidence that safety-net, rural, and public hospitals are more likely to receive a penalty. The results also suggest that there is room for providers to reduce avoidable readmissions and policymakers to mitigate unintended consequences.

Identifying and mapping TB hot spots in an urban slum by integratingGeographic positioning system and the local postman - A pilot study.

SETTING: Mahavir DOT Centre, Hyderabad, Telangana, India INTRODUCTION: Urban slums are characterized by crowding, poverty. In such setting due to lack of infection control the transmission of tuberculosis is known to rise, thereby creating a "Hot" spot. Distribution of residences in such areas does not necessarily follow postal codes, making it difficult for health workers to locate TB patients unless accompanied by the STLS. OBJECTIVE: To investigate the utility of integrating the help of local postman and geographic positioning system (GPS) to identify and create map of hot spots in an area under a regional DOT centre. MATERIALS & METHODS: Retrospective and prospective demographic data of TB patients enrolled during 12 years (1999-2011) was analysed from the TB register at a ward where number of cases continued to increase despite active implementation of DOTS strategy. Non-Spatial data was generated with the local postman identifying individual house addresses. The corresponding co-ordinates were recorded with GPS and uploaded in Google Earth to identify the locations. Area map was created by software (AutoCAD, Map R3, MapInfo Pro 7.5 Trial Version and MS office Tools). Residences of Index patients were marked in different colours year wise on the map. RESULTS: Maps displayed in the DOT centre area helped in identifying HOT SPOT and visualization of the clustering of TB cases in the area. Time interval between subsequent infections (3 months-5 years) could be calculated in the locality, within household, neighbourhood and random contacts. Average distances (<1 m) between houses indicated the probable source of infection. Risk factors included crowding, poor ventilation and sanitation contributed to TB transmission in HOT spot area. CONCLUSION: Integrating local postman and information technology to identify HOT SPOT in RNTCP, will help in early intervention by health personnel to arrest TB transmission.

External validation of a claims-based and clinical approach for predicting post-pulmonary embolism outcomes among United States veterans.

The In-hospital Mortality for PulmonAry embolism using Claims daTa (IMPACT) rule can accurately identify pulmonary embolism (PE) patients at low risk of early complications using claims data. We sought to externally validate the IMPACT and simplified Pulmonary Embolism Severity Index (sPESI) tools for predicting all-cause mortality and readmission. We used Veteran Health Administration data (10/1/2010-9/30/2015) to identify adults with ≥1 inpatient diagnosis code for acute PE, ≥12 months continuous medical and pharmacy benefits prior to the index PE, ≥90 days of post-event follow-up (unless death occurred) and ≥1 claim for an anticoagulant during the index PE stay. Prognostic accuracies of IMPACT and sPESI for 30- and 90-day all-cause mortality and 90-day readmission were estimated. Of 6,746 PE patients, 7.5 and 12.6% died at 30 and 90 days. Within 90 days, 20.1% were readmitted for any reason. Hospitalization for recurrent VTE and major bleeding occurred in 5.6 and 1.7% of patients. IMPACT classified 15.2% as low risk, while 28.4% were low risk per sPESI. Both tools displayed sensitivity >90% and negative predictive values (NPVs) >97% for 30-day mortality, but low specificity (range 16.2-30.0) and positive predictive values (PPVs) (range 8.7-9.5); with similar results observed for 90-day mortality. IMPACT's sensitivity for all-cause readmission was numerically higher than sPESI (88.2 vs. 79.0%), but both had comparable NPVs (85.1 vs. 84.2%). Similar trends were observed for VTE or major bleeding readmissions. IMPACT classified patients for post-PE outcomes with similar accuracy as sPESI. IMPACT appears useful for identifying PE patients at low risk for early mortality or readmission in claims-based studies.

IL-10 high producing genotype predisposes HIV infected individuals to TB infection.

Interleukin (IL-10), an anti-inflammatory cytokine, is known to have dual effect on the host immune system. One of these roles is that it provides an effective autoregulatory mechanism which protects the host from excessive inflammation and tissue damage which is in part initiated by the Th1 driven pro-inflammatory immune responses during infections (such as TB, HIV and malaria). However, though beneficial, this autoregulatory mechanism is at times exploited by pathogens which evade elimination by Th1 driven immune response leading to chronic infections. The main aim of this study therefore was to study the influence of IL-10 polymorphism in relation to its levels with respect to HIV-TB co-infection. A total of 452 participants were categorized into HIV (121), active tuberculosis (TB) (118), HIV-TB (HT) (106) groups and healthy control group (107). Polymorphism for IL-10 gene (positions -1082, -819, -592) was studied using ARMS-PCR, RFLP. IL-10 and IFN-γ levels in antigen stimulated cultures were measured using ELISA. Statistical analysis was performed using Chi-Square (χ(2)) test, One-way ANOVA and t-tests. IL-10 (-1082) GG genotype was positively associated with HIV-TB, whereas AG with HIV and AA with TB. The cohort with GG genotype also had significantly high stimulated levels of IL-10 compared to AG and AA. AC genotype was significantly frequent in HIV-TB group at IL-10 (-592) position when compared with controls. HIV positive individuals with GG genotype at IL-10 (-1082) position and high IL-10 levels may have a high risk of developing TB co-infection.

Plastid movement in statocytes of the arg1 (altered response to gravity) mutant.

The ability of a plant to respond to gravity is crucial for growth and development throughout the life cycle. A key player in the cellular mechanisms of gravitropism is ARG1 (altered response to gravity), a DnaJ-like protein that associates with components of the vesicular trafficking pathway and carries a C-terminal domain with similarities to cytoskeleton-associated proteins. The arg1-2 mutant of Arabidopsis thaliana has reduced and delayed gravitropism in roots, shoots, and inflorescence stems when grown in the light or dark. We performed light microscopic studies of plastid movement in the gravity-perceiving statocytes (endodermal cells) of hypocotyls of arg1-2 and WT light-grown seedlings following reorientation to better characterize the role of ARG1 in gravitropism. Cryofixation/freeze substitution procedures were used because they provide a reliable indication of rapid cellular events within the statocytes. Our results suggest that ARG1 affects gravitropism by reducing plastid movement/sedimentation, a process known to be essential for early phases of signaling cascades in the statocytes.