Emerging racial disparities among Medicare beneficiaries and Veterans with metastatic castration-sensitive prostate cancer.

BACKGROUND: Previous studies have shown that Black men receive worse prostate cancer care than White men. This has not been explored in metastatic castration-sensitive prostate cancer (mCSPC) in the current treatment era. METHODS: We evaluated treatment intensification (TI) and overall survival (OS) in Medicare (2015-2018) and Veterans Health Administration (VHA; 2015-2019) patients with mCSPC, classifying first-line mCSPC treatment as androgen deprivation therapy (ADT) + novel hormonal therapy; ADT + docetaxel; ADT + first-generation nonsteroidal antiandrogen; or ADT alone. RESULTS: We analyzed 2226 Black and 16,071 White Medicare, and 1020 Black and 2364 White VHA patients. TI was significantly lower for Black vs White Medicare patients overall (adjusted odds ratio [OR] 0.68; 95% confidence interval [CI] 0.58-0.81) and without Medicaid (adjusted OR 0.70; 95% CI 0.57-0.87). Medicaid patients had less TI irrespective of race. OS was worse for Black vs White Medicare patients overall (adjusted hazard ratio [HR] 1.20; 95% CI 1.09-1.31) and without Medicaid (adjusted HR 1.13; 95% CI 1.01-1.27). OS was worse in Medicaid vs without Medicaid, with no significant OS difference between races. TI was significantly lower for Black vs White VHA patients (adjusted OR 0.75; 95% CI 0.61-0.92), with no significant OS difference between races. CONCLUSIONS: Guideline-recommended TI was low for all patients with mCSPC, with less TI in Black patients in both Medicare and the VHA. Black race was associated with worse OS in Medicare but not the VHA. Medicaid patients had less TI and worse OS than those without Medicaid, suggesting poverty and race are associated with care and outcomes.

Some patients with type 2 diabetes may benefit from intensive glycaemic and blood pressure control: A post-hoc machine learning analysis of ACCORD trial data.

AIM: The action to control cardiovascular risk in diabetes (ACCORD) trial showed a neutral average treatment effect of intensive blood glucose and blood pressure (BP) controls in preventing major adverse cardiovascular events (MACE) in individuals with type 2 diabetes. Yet, treatment effects across patient subgroups have not been well understood. We aimed to identify patient subgroups that might benefit from intensive glucose or BP controls for preventing MACE. MATERIALS AND METHODS: As a post-hoc analysis of the ACCORD trial, we included 10 251 individuals with type 2 diabetes. We applied causal forest and causal tree models to identify participant characteristics that modify the efficacy of intensive glucose or BP controls from 68 candidate variables (demographics, comorbidities, medications and biomarkers) at the baseline. The exposure was (a) intensive versus standard glucose control [glycated haemoglobin (HbA1c) <6.0% vs. 7.0%-7.9%], and (b) intensive versus standard BP control (systolic BP <120 vs. <140 mmHg). The primary outcome was MACE. RESULTS: Compared with standard glucose control, intensive one reduced MACE in those with baseline HbA1c <8.5% [relative risk (RR): 0.79, 95% confidence interval (CI): 0.67-0.93] and those with estimated glomerular filtration rate ≥106 ml/min/1.73 m2 (RR: 0.74, 95% CI: 0.55-0.99). Intensive BP control reduced MACE in those with normal high-density lipoprotein levels (women >55 mg/dl, men >45 mg/dl; RR: 0.51, 95% CI: 0.34-0.74). Risk reductions were not significant in other patient subgroups. CONCLUSIONS: Our findings suggest heterogeneous treatment effects of intensive glucose and BP control and could provide biomarkers for future clinical trials to identify more precise HbA1c and BP treatment goals for individualized medicine.

Compassionate use of contezolid in a toddler with severe community-acquired pneumonia induced by staphylococcus aureus: a case report and follow-up.

Background: Initial choices of antimicrobial therapy for most cases of community-acquired pneumonia (CAP) in children under 5 years of age are typically based on local epidemiology, risk factors assessment, and subsequent clinical parameters and positive cultures, which can lead to the underdiagnosis and underestimation of lung infections caused by uncommon pathogens. Contezolid, an orally administered oxazolidinone antibiotic, gained approval from the National Medical Products Administration (NMPA) of China in June 2021 for managing complicated skin and soft tissue infections (cSSTI) caused by staphylococcus aureus (SA), streptococcus pyogenes, or streptococcus agalactis. Owing to its enhanced safety profile and ongoing clinical progress, the scope of contezolid's clinical application continues to expand, benefiting a growing number of patients with Gram-positive bacterial infections. Case summary: In this report, we present the first use of contezolid in a toddler with severe CAP caused by SA, aiming to avoid potential adverse drug reactions (ADRs) associated with vancomycin and linezolid. Conclusion: Although contezolid has not been officially indicated for CAP, it has been shown to be effective and safe in the management of SA-induced severe CAP in this toddler, suggesting its potential as an alternative option in the dilemma, especially for patients who are susceptible or intolerant to ADRs associated with first-line anti-methicillin-resistant staphylococcus aureus (MRSA) antimicrobial agents.

A prediction model on incident chronic kidney disease among individuals with type 2 diabetes in the United States.

AIM: Early identification of incident chronic kidney disease (CKD) in individuals with diabetes may help improve patients' clinical outcomes. This study aimed to develop a prediction equation for incident CKD among people with type 2 diabetes (T2D). MATERIALS AND METHODS: A time-varying Cox model was applied to data from the ACCORD trial to predict the risk of incident CKD. A list of candidate variables was chosen based on literature reviews and experts' consultations, including demographic characteristics, vitals, laboratory results, medical history, drug use and health care utilization. Model performance was evaluated. Decomposition analysis was conducted, and external validation was performed. RESULTS: In total, 6006 patients with diabetes free of CKD were included, with a median follow-up of 3 years and 2257 events. The risk model included age at T2D diagnosed, smoking status, body mass index, high-density lipoprotein, very-low-density lipoprotein, alanine aminotransferase, estimated glomerular filtration rate, urine albumin-creatinine ratio, hypoglycaemia, retinopathy, congestive heart failure, coronary heart disease history, antihyperlipidaemic drug use, antihypertensive drug use and hospitalization. The urine albumin-creatinine ratio, estimated glomerular filtration rate and congestive heart failure were the top three factors that contributed most to the incident CKD prediction. The model showed acceptable discrimination [C-statistic: 0.772 (95% CI 0.767-0.805)] and calibration [Brier Score: 0.0504 (95% CI 0.0477-0.0531)] in the Harmony Outcomes Trial. CONCLUSION: Incident CKD prediction among individuals with T2D was developed and validated for use in decision support of CKD prevention.

A prediction model on incident ESKD among individuals with T2D and CKD.

BACKGROUND: Diabetes is the leading cause of end-stage kidney disease (ESKD). This study aimed to predict incident ESKD among individuals with T2D and CKD. METHOD: The Action to Control Cardiovascular Risk in Diabetes (ACCORD) clinical trial data were split into a training set and a validation set by a ratio of 7:3. A dynamic time-varying Cox model was fit to predict the development of incident ESKD. Significant predictors were identified from a list of candidate variables, including demographic characteristics, physical exam results, laboratory results, medical history, drug information, and healthcare utilization. Model performance was evaluated by Brier score and C statistics. Decomposition analysis was conducted to assess the variable importance. Patient-level data from Harmony Outcome clinical trial and CRIC study were used for external validation. RESULTS: A total of 6982 diabetes patients with CKD were used for model development, with a median follow-up of four years and 312 ESKD events. The significant predictors for the final model were female sex, race, smoking status, age at T2D diagnosis, SBP, HR, HbA1c, estimated glomerular filtration rate (eGFR), urine albumin-creatinine ratio (UACR), retinopathy event occurring in last year, antihypertensive drug use, and an interaction term between SBP and female. The model demonstrated good performance in discrimination (C-statistic 0.764 [95 % CI 0.763-0.811]) and calibration (Brier Score 0.0083 [95 % CI 0.0063-0.0108]). The top 3 most important predictors in the prediction model were eGFR, retinopathy event, and UACR. Acceptable discrimination (C-statistic: 0.701 [95 % CI 0.665-0.716]; 0.86 [95 % CI 0.847-0.872]) and calibration (Brier Score: 0.0794 [95 % CI 0.0733-0.1022]; 0.0476 [95 % CI 0.0440, 0.0506]) were demonstrated in the Harmony Outcome and CRIC data, respectively. CONCLUSION: The dynamic risk prediction of incident ESKD among individuals with T2D can be a useful tool to support better disease management to lower the risk of developing ESKD.

Exacerbation of financial burden of insulin and overall glucose-lowing medications among uninsured population with diabetes.

BACKGROUND: Approximately 7.4 million Americans with diabetes used insulin. This study aimed to document the 10-year trend of insulin and other glucose-lowering medications expenditure among insured and uninsured populations and to examine the impact of insulin out-of-pocket (OOP) payment and insurance status on glucose-lowering medication OOP expenditure. METHODS: We extracted data from the Medical Expenditure Panel Survey (2009-2018) to document trends in the expenditure of insulin among people with diabetes. Total expenditures and OOP spending per person were documented on insulin and noninsulin glucose-lowering medications among insured and uninsured populations. Multivariable regression was applied to assess the association of insulin OOP payment and insurance status on glucose-lowering medication OOP expenditure. RESULTS: Although insulin usage was stable over the decades, total insulin expenditure almost doubled per person per year after the Affordable Care Act (ACA) regardless of the insurance status. The OOP cost of insulin by the uninsured population increased from $1678 per person per year in the pre-ACA period to $2800 per person per year in the post-ACA period. After the ACA was enacted, the uninsured population had $403.96 and $143.64 more on OOP costs than the people with public and private insurance, respectively. CONCLUSION: For insured people, the rising financial burden of insulin was borne mainly by insurance. The uninsured population is bearing a heavy burden due to the high price of insulin. Policymakers should take action to reduce the insulin price and improve the transparency of the insulin pricing process.

A prediction model of CKD progression among individuals with type 2 diabetes in the United States.

BACKGROUND: CKD progression among individuals with T2D is associated with poor health outcomes and high healthcare costs, which have not been fully studied. This study aimed to predict CKD progression among individuals with diabetes. METHOD: Using ACCORD trial data, a time-varying Cox model was developed to predict the risk of CKD progression among patients with CKD and T2D. CKD progression was defined as a 50 % decline, or 25 mL/min/1.73 m2 decline in eGFR from baseline, doubling of the serum creatinine, or onset of ESKD. A list of candidate variables included demographic characteristics, physical exam results, laboratory results, medical history, drug use, and healthcare utilization. A stepwise algorithm was used for variable selection. Model performance was evaluated by Brier score and C-statistics. Confidence intervals (CI) were calculated using a bootstrap method. Decomposition analysis was conducted to assess the predictor contribution. Generalizability was assessed on patient-level data of the Harmony Outcome trial and CRIC study. RESULTS: A total of 6982 diabetes patients with CKD were used for model development, with a median follow-up of 4 years and 3346 events. The predictors for CKD progression included female sex, age at T2D diagnosis, smoking status, SBP, DBP, HR, HbA1c, alanine aminotransferase (ALT), eGFR, UACR, retinopathy event, hospitalization. The model demonstrated good discrimination (C-statistics 0.745 [95 % CI 0.723-0.763]) and calibration (Brier Score 0.0923 [95 % CI 0.0873-0.0965]) performance in the ACCORD data. The most contributing predictors for CKD progression were eGFR, HbA1c, and SBP. The model demonstrated acceptable discrimination and calibration performance in the two external data. CONCLUSION: For high-risk patients with both diabetes and CKD, the tool as a dynamic risk prediction of CKD progression may help develop novel strategies to lower the risk of CKD progression.

Prevalence and Disability-Adjusted Life Year Rates of Asthma in China: Findings from the GBD Study 2019 of the G20.

BACKGROUND: The credible materials about the burden of asthma in China when compared to other countries in the group of twenty (G20) remain unavailable. OBJECTIVES AND DESIGN: Following the popular analysis strategy used in the Global Burden of Disease Study, the age-, sex-, country-specific prevalence, and disability-adjusted life years (DALYs) of asthma in China were analyzed. Meanwhile, the comparison in trends between China and other countries in the G20 was also evaluated. RESULTS: In 2019, asthma was the 8th leading cause of the DALYs' burden of 369 diseases in China. From 1990 to 2019, the age-standardized prevalence and DALY rates of asthma in China decreased by 14% and 51%, respectively; further, the decline rate of DALYs was much higher than the global average (-51%: -43%). It is worth noting that the overall population age-standardized DALYs rate of asthma in China was the lowest in the G20 during 2019 (102.81, 95% UI: (72.30,147.42)/100,000). Moreover, the age-standardized asthma prevalence rate peaks in both childhood (178.14, 95% UI: (90.50, 329.01)/100,000) and the elderly (541.80, 95% UI: (397.79, 679.92)/100,000). Moreover, throughout the study, subjects in the 5 to 9 years old interval were a constant focus of our attention. CONCLUSIONS: The disease burden of asthma has varied greatly by gender and age over the past 30 years. In contrast to the increasing burden in most other G20 countries, the age-standardized prevalence rate of asthma shows a significant decreasing trend in China, however, the age-standardized DALYs rate shows a fluctuating change, and has even shown a rebound trend in recent years.

Using modern risk engines and machine learning/artificial intelligence to predict diabetes complications: A focus on the BRAVO model.

Management of diabetes requires a multifaceted approach of risk factor reduction; through management of risk factors such as glucose, blood pressure and cholesterol. Goals for these risk factors often vary and guidelines suggest that this is based on patient characteristics and need to be individualized. Evaluating risk is therefore critically important to determine goals and choose appropriate treatments. A risk engine is an analytic tool that collects a large amount of population data allowing the simulation of the progression of diabetes with set equations over a period of time. Recently, a number of data cohorts have become available, leading to the development of newer risk engines that are more dynamic and generalizable. An example is the Building, Relating, Assessing, and Validating Outcomes in (BRAVO) diabetes model which was built on the ACCORD trial database. It is capable of accurately predicting diabetes comorbidities in an international population based on calibration with international clinical trial data. It has potential uses in risk stratification of patients, evaluation of interventions and calculation of their long term cost effectiveness. Recently, it has been used to simulate long term outcomes based on short term data, using difference modelling scenarios.

Effect of continuity of care on emergency department and hospital visits for obesity-associated chronic conditions: A federated cohort meta-analysis.

BACKGROUND: Obesity-associated chronic conditions (OCC) are prevalent in medically underserved areas of the Southern US. Continuity of care with a primary care provider is associated with reduced preventable healthcare utilization, yet little is known regarding the impact of continuity of care among populations with OCC. This study aimed to examine whether continuity of care protects patients living with OCC and the subgroup with type 2 diabetes (OCC+T2D) from emergency department (ED) and hospitalizations, and whether these effects are modified by race and patient residence in health professional shortage areas (HPSA) METHODS: We conducted a retrospective federated cohort meta-analysis of 2015-2018 data from four large practice-based research networks in the Southern U.S. among adult patients with obesity and one more more additional diagnosed OCC. The outcomes included overall and preventable ED visits and hospitalizations. Continuity of care was assessed at the clinic-level using the Bice-Boxerman Continuity of Care Index RESULTS: A total of 111,437 patients with OCC and 47,071 patients with OCC+T2D from the four large practice-based research networks in the South were included in the meta-analysis. Continuity of Care index varied among sites from a mean (SD) of 0.6 (0.4) to 0.9 (0.2). Meta-analysis demonstrated that, regardless of race or residence in HPSA, continuity of care significantly protected OCC patients from preventable ED visits (IRR:0.95; CI:0.92-0.98) and protected OCC+T2D patients from overall ED visits (IRR:0.92; CI:0.85-0.99), preventable ED visits (IRR:0.95; CI:0.91-0.99), and overall hospitalizations (IRR:0.96; CI:0.93-0.98) CONCLUSION: Improving continuity of care may reduce ED and hospital use for patients with OCC and particularly those with OCC+T2D.

A machine learning approach identifies modulators of heart failure hospitalization prevention among patients with type 2 diabetes: A revisit to the ACCORD trial.

BACKGROUND: To examine patient characteristics that may modulate the heterogeneous treatment effect of intensive systolic blood pressure control (SBP) and intensive glycemic control on incident heart failure (HF) risk in people with type 2 diabetes. METHODS: We analyzed 10,251 participants from the ACCORD glucose trial, and 4733 from the SBP sub-trial separately. We applied a robust machine-learning (ML) algorithm, namely the causal forest/causal tree analysis, to each trial to identify participants' characteristics that modulate the effectiveness of each trial intervention. RESULTS: Diastolic blood pressure (DBP) was found to interact with intensive glycemic control and impact outcomes. An increased HF risk associated with intensive glycemic control (absolute risk change (ARC): 2.28 %, 95 % confidence interval (CI): 0.69 % to 3.90 %; relative risk (RR):1.57, 95 % CI: 1.15 to 2.20; P < 0.05) was observed in individuals with baseline DBP at the lowest tertile (45-69 mmHg), while no changes in HF risk associated with intensive glycemic control were observed in individuals with baseline DBP at the middle (70-79 mmHg) and the highest tertiles (80-100 mmHg). Liver function was identified as a modulator of intensive BP control, and baseline Alanine transaminase (ALT) level was a sensitive marker for the modulating effect. Only individuals with baseline ALT at the lowest tertile (8-19 mg/dl) benefited from the intensive BP control for HF prevention (ARC: -1.95 %, 95 % CI: -4.06 % to 0.11 %; RR:0.62. 95 % CI: 0.27 to 0.94; P < 0.05). CONCLUSIONS: Our study is the first to observe and quantify the potential synergistic harmful effect when low DBP was combined with an intensive blood glucose intervention. Recognizing these may help clinicians develop a more precise approach to such treatments, thus increasing the efficiency and outcomes of diabetes treatments.

Predicting incident heart failure among patients with type 2 diabetes mellitus: The DM-CURE risk score.

AIM: Early identification and prediction of incident heart failure (HF) is important because of severe morbidity and mortality. This study aimed to predict onset of HF among patients with diabetes. METHODS: A time-varying Cox model was derived from ACCORD clinical trial to predict the risk of incident HF, defined by hospitalization for HF (HHF). External validation was performed on patient-level data from the Harmony Outcome trial and Chronic Renal Insufficiency Cohort (CRIC) study. The model was transformed into an integer-based scoring algorithm for 10-year risk evaluation. A stepwise algorithm identified and selected predictors from demographic characteristics, physical examination, laboratory results, medical history, medication and health care utilization, to develop a risk prediction model. The main outcome was incident HF, defined by HHF. The C statistic and Brier score were used to assess model performance. RESULTS: In total, 9649 patients with diabetes free of HF were used, with median follow-up of 4 years and 299 incident hospitalization of HF events. The model identified several predictors for the 10-year HF incidence risk score 'DM-CURE': socio-Demographic [education, age at type 2 diabetes (T2DM) diagnosis], Metabolic (glycated haemoglobin, systolic blood pressure, body mass index, high-density lipoproteins), diabetes-related Complications (myocardial infarction, revascularization, cardiovascular medications, neuropathy, hypertension duration, albuminuria, urine albumin-to-creatinine ratio, End Stage Kidney Disease), and health care Utilization (all-cause hospitalization, emergency room visits) for Risk Evaluation. Among them, the strongest impact factors for future HF were age at T2DM diagnosis, health care utilization and cardiovascular disease-related variables. The model showed good discrimination (C statistic: 0.838, 95% CI: 0.821-0.855) and calibration (Brier score: 0.006, 95% CI: 0.006-0.007) in the ACCORD data and good performance in the validation data (Harmony: C statistic: 0.881, 95% CI: 0.863-0.899; CRIC: C statistic: 0.813, 95% CI: 0.794-0.833). The 10-year risk of incident HF increased in a graded fashion, from ≤1% in quintile 1 (score ≤14), 1%-5% in quintile 2 (score 15-23), 5%-10% in quintile 3 (score 24-27), 10%-20% in quintile 4 (score 28-33) and ≥20% in quintile 5 (score >33). CONCLUSIONS: The DM-CURE model and score were useful for population risk stratification of incident HHF among patients with T2DM and can be easily applied in clinical practice.

Optimizing treatment goals for long-term health outcomes among patients with type 2 diabetes mellitus.

INTRODUCTION: Considerable confusions on treatment target have resulted from recent changes in guidelines. Evidence in medical guidelines came from clinical trials with highly selected patients, whereas treatment goals may differ in some subgroups. This study aimed to assess optimal treatment goals (A1C, blood pressure, low-density lipoprotein cholesterol (LDL-C)) for patients with type 2 diabetes mellitus (T2DM), which lead to optimal health outcomes by different treatment strategies. RESEARCH DESIGN AND METHODS: A retrospective longitudinal study was conducted for veterans with T2DM by using US Veterans Affairs Administrative Database (2005-2015). Medical records were prepared for repeated evaluation performed at 6-month intervals and multivariate longitudinal regression was used to estimate the risk of microvascular and macrovascular complication events. Second-degree polynomial and splines were applied to identify the optimal goals in their associations with lowest risk of clinical outcomes, controlling for demographic characteristics, medical history, and medications. RESULTS: A total of 124 651 patients with T2DM were selected, with mean of 6.72 follow-up years. In the general population, to achieve the lowest risk of microvascular and macrovascular complication, the optimal goals were A1C=6.81%, LDL-C=109.10 mg/dL; and A1C=6.76%, LDL-C=111.65 mg/dL, systolic blood pressure (SBP)=130.60 mmHg, respectively. The optimal goals differed between age and racial subgroups. Lower SBP for younger patients and lower LDL-C for black patients were associated with better health outcomes. CONCLUSIONS: Optimal treatment goals were identified and multi-faceted treatment strategies targeting hyperglycemia and hyperlipidemia and hypertension may improve health outcome in veterans with T2DM. In addition to guidelines' recommended goals, health systems may examine their own large diverse patients with T2DM for better quality of care.

Effects of medicaid expansion on poverty disparities in health insurance coverage.

BACKGROUND: More than 30 states have either expanded Medicaid or are actively considering expansion. The coverage gains from this policy are well documented, however, the impacts of its increasing coverage on poverty disparity are unclear at the national level. METHOD: American Community Survey (2012-2018) was used to examine the effects of Medicaid expansion on poverty disparity in insurance coverage for nonelderly adults in the United States. Differences-in-differences-in-differences design was used to analyze trends in uninsured rates by poverty levels: (1) < 138 %, (2) 138-400 % and (3) > 400 % federal poverty level (FPL). RESULTS: Compared with uninsured rates in 2012, uninsured rates in 2018 decreased by 10.75 %, 6.42 %, and 1.11 % for < 138 %, 138-400 %, and > 400 % FPL, respectively. From 2012 to 2018, > 400 % FPL group continuously had the lowest uninsured rate and < 138 % FPL group had the highest uninsured rate. Compared with ≥ 138 % FPL groups, there was a 2.54 % reduction in uninsured risk after Medicaid expansion among < 138 % FPL group in Medicaid expansion states versus control states. After eliminating the impact of the ACA market exchange premium subsidy, 3.18 % decrease was estimated. CONCLUSION: Poverty disparity in uninsured rates improved with Medicaid expansion. However, < 138 % FPL population are still at a higher risk for being uninsured.

The Effect of Proton Pump Inhibitor Use on the Course of Kidney Function in Patients with Chronic Kidney Disease Stages G3a to G4.

BACKGROUND: Proton pump inhibitors (PPI) are widely used and implicated in the progression of chronic kidney disease (CKD). We evaluated the relation between chronic PPI use in veterans with CKD G3a to G4 and the rate of decline in renal function. METHODS: We accessed the Veteran Affairs Informatics and Computing Infrastructure national database to evaluate the relation between chronic PPI use and rate of decline in renal function in veterans with CKD (eGFR <60 ml/min1.73 m2). We applied Propensity Score Matching to match the PPI group and the no-PPI control group on age, sex, race, and Charlson Comorbidity Index. The final sample included 1406 patients (age: 62.07±7.82, 62.02% Caucasian) in the PPI cohort with a median 4.7 years follow-up and 1425 patients (age: 65.45±6.58, 71.16% Caucasian) in the control cohort with a median 3.9 years follow-up. Kaplan-Meier curve and Cox regression were performed to analyze the associations of PPI use with dialysis, all-cause mortality, metabolic acidosis, and CKD progression. RESULTS: The PPI group had a significantly increased risk of CKD progression, dialysis and all-cause mortality (aHR, 1.83; 95% CI, 1.53 to 2.19; aHR, 1.84; 95% CI, 1.26 to 2.67; and aHR, 1.34; 95% CI, 1.08 to 1.65, respectively). The PPI cohort also had a trend for development of metabolic acidosis (aHR, 1.34; 95% CI, 0.998 to 1.80), although the difference was not statistically significant. CONCLUSIONS: The data suggest that chronic PPI use accelerates progression of kidney disease and is associated with increased mortality in CKD patients.

Continuity of Care for Patients with Obesity-Associated Chronic Conditions: Protocol for a Multisite Retrospective Cohort Study.

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.

Second-line rituximab-bendamustine versus rituximab-gemcitabine-oxaliplatin in diffuse large B-cell lymphoma in the real world.

Aim: Despite long-term responses to first-line immunochemotherapy, many patients with diffuse large B-cell lymphoma (DLBCL) have relapsed/refractory disease. Second-line treatment options are available. However, a large proportion of patients are ineligible for transplantation/intensive therapy. Patients & methods: This observational study of 702 patients in the USA, who used second-line therapies for relapsed/refractory DLBCL, evaluated treatment patterns and overall survival (OS). The study focused on the OS outcome of patients receiving second-line rituximab-bendamustine or rituximab-gemcitabine-oxaliplatin. Results & conclusion: Rituximab-bendamustine and rituximab-gemcitabine-oxaliplatin were received by 4.6 and 1.4% of patients, respectively (N = 42/702). Median and 1-year OS rates were similar between regimens. Many of the 200 different treatment regimens observed in second line were modified versions of National Comprehensive Cancer Network regimens.

Analysis on geographic variations in hospital deaths and endovascular therapy in ischaemic stroke patients: an observational cross-sectional study in China.

OBJECTIVES: Stroke is the leading cause of death and adult disability in China, following a rise in incidence over the last few decades. We aimed to explore the geographic variations in hospital mortality and endovascular therapy (EVT) use among ischaemic stroke (IS) patients in China, and investigate the associated potential risk factors. DESIGN: Observational cross-sectional study of patients hospitalised for stroke. SETTING: Hospital discharge data for 1267 tertiary hospitals between 1 January 2015 and 31 December 2015 were derived from the Nationwide Hospital Discharge Database operated by the National Health Commission of China. PARTICIPANTS: 1 826 332 patients aged ≥18 years, hospitalised following stroke. OUTCOME MEASURES: In-hospital mortality and EVT use. RESULTS: The nationwide hospital mortality rate of IS patients was 0.88% (95% CI 0.86% to 0.90%); there was a significantly greater risk of mortality in the Northeast (OR 2.37; 95% CI 2.23 to 2.52), West (1.65; 1.54 to 1.78), South (1.25; 1.17 to 1.33) and North (1.29; 1.20 to 1.39) than in the East. Tertiary B hospitals (OR 1.05; 95% CI 1.00 to 1.09), patients admitted from emergency departments and older patients were associated with higher hospital mortality. The national EVT use rate was 0.45% (95% CI 0.44% to 0.46%). Compared with in East China, EVT use was significantly lower in the Northeast (OR 0.22; 95% CI 0.20 to 0.24) and West (0.64; 0.58 to 0.71), though not the North (1.23; 1.14 to 1.33). Tertiary A hospitals (OR 2.62; 95% CI 2.43 to 2.83), male patients and patients admitted from emergency departments were also associated with higher EVT use rates. CONCLUSIONS: There were substantial disparities in mortality and EVT use for hospitalised patients with IS among China's tertiary hospitals, linked with both geographic and hospital characteristics. More targeted intervention at regional and hospital levels is needed for providing effective health technologies and eventually improving post-stroke outcomes.

Spatiotemporal dynamics of the biological interface between cancer and the microenvironment: a fractal anomalous diffusion model with microenvironment plasticity.

BACKGROUND: The invasion-metastasis cascade of cancer involves a process of parallel progression. A biological interface (module) in which cells is linked with ECM (extracellular matrix) by CAMs (cell adhesion molecules) has been proposed as a tool for tracing cancer spatiotemporal dynamics. METHODS: A mathematical model was established to simulate cancer cell migration. Human uterine leiomyoma specimens, in vitro cell migration assay, quantitative real-time PCR, western blotting, dynamic viscosity, and an in vivo C57BL6 mouse model were used to verify the predictive findings of our model. RESULTS: The return to origin probability (RTOP) and its related CAM expression ratio in tumors, so-called "tumor self-seeding", gradually decreased with increased tumor size, and approached the 3D Pólya random walk constant (0.340537) in a periodic structure. The biphasic pattern of cancer cell migration revealed that cancer cells initially grew together and subsequently began spreading. A higher viscosity of fillers applied to the cancer surface was associated with a significantly greater inhibitory effect on cancer migration, in accordance with the Stokes-Einstein equation. CONCLUSION: The positional probability and cell-CAM-ECM interface (module) in the fractal framework helped us decipher cancer spatiotemporal dynamics; in addition we modeled the methods of cancer control by manipulating the microenvironment plasticity or inhibiting the CAM expression to the Pólya random walk, Pólya constant.