DCRM 2.0: Multispecialty practice recommendations for the management of diabetes, cardiorenal, and metabolic diseases.

The spectrum of cardiorenal and metabolic diseases comprises many disorders, including obesity, type 2 diabetes (T2D), chronic kidney disease (CKD), atherosclerotic cardiovascular disease (ASCVD), heart failure (HF), dyslipidemias, hypertension, and associated comorbidities such as pulmonary diseases and metabolism dysfunction-associated steatotic liver disease and metabolism dysfunction-associated steatohepatitis (MASLD and MASH, respectively, formerly known as nonalcoholic fatty liver disease and nonalcoholic steatohepatitis [NAFLD and NASH]). Because cardiorenal and metabolic diseases share pathophysiologic pathways, two or more are often present in the same individual. Findings from recent outcome trials have demonstrated benefits of various treatments across a range of conditions, suggesting a need for practice recommendations that will guide clinicians to better manage complex conditions involving diabetes, cardiorenal, and/or metabolic (DCRM) diseases. To meet this need, we formed an international volunteer task force comprising leading cardiologists, nephrologists, endocrinologists, and primary care physicians to develop the DCRM 2.0 Practice Recommendations, an updated and expanded revision of a previously published multispecialty consensus on the comprehensive management of persons living with DCRM. The recommendations are presented as 22 separate graphics covering the essentials of management to improve general health, control cardiorenal risk factors, and manage cardiorenal and metabolic comorbidities, leading to improved patient outcomes.

Association Between Age at Diabetes Diagnosis and Subsequent Incidence of Cancer: A Longitudinal Population-Based Cohort.

OBJECTIVE: Diabetes presenting at a younger age has a more aggressive nature. We aimed to explore the association of age at type 2 diabetes mellitus (T2DM) diagnosis with subsequent cancer incidence in a large Chinese population. RESEARCH DESIGN AND METHODS: The prospective population-based longitudinal cohort included 428,568 newly diagnosed T2DM patients from 2011 to 2018. Participants were divided into six groups according to their age at diagnosis: 20-54, 55-59, 60-64, 65-69, 70-74, and ≥75 years. The incidence of overall and 14 site-specific cancers was compared with the Shanghai general population including 100,649,346 person-years. RESULTS: A total of 18,853 and 582,643 overall cancer cases were recorded in the T2DM cohort and the general population. The age-standardized rate of overall cancer in T2DM patients was 501 (95% CI: 491, 511) per 100,000 person-years, and the standardized incidence ratio (SIR) was 1.10 (1.09, 1.12). Younger age at T2DM diagnosis was associated with higher incidence of overall and site-specific cancers. SIRs for overall cancer with T2DM diagnosis at ages 20-54, 55-59, 60-64, 65-69, 70-74, and ≥75 years were 1.48 (1.41, 1.54), 1.30 (1.25, 1.35), 1.19 (1.15, 1.23), 1.16 (1.12, 1.20), 1.06 (1.02, 1.10), and 0.86 (0.84, 0.89), respectively. Similar trends were observed for site-specific cancers, including respiratory, colorectum, stomach, liver, pancreatic, bladder, central nervous system, kidney, and gallbladder cancer and lymphoma among both males and females. CONCLUSIONS: Our findings highlight the necessity of stratifying management for T2DM according to age of diagnosis. As with a range of vascular outcomes, age-standardized cancer risks are greater in earlier compared with later onset T2DM.

Association between age at diabetes onset or diabetes duration and subsequent risk of pancreatic cancer: Results from a longitudinal cohort and mendelian randomization study.

Background: The aim of the study is to estimate the incidence of pancreatic cancer among individuals with new-onset type 2 Diabetes (T2DM) and evaluate the relationship of pancreatic cancer risk with age at diabetes onset and diabetes duration. Methods: This longitudinal cohort study included 428,362 new-onset T2DM patients in Shanghai and Mendelian randomization (MR) in the east-Asian population were used to investigate the association. Incidence rates of pancreatic cancer in all patients and by subgroups were calculated and compared to the general population. Findings: A total of 1056 incident pancreatic cancer cases were identified during eight consecutive years of follow-up. The overall pancreatic cancer annual incidence rate was 55·28/100,000 person years in T2DM patients, higher than that in the general population, with a standardized incidence ratio (SIR) of 1·54 (95% confidence interval [CI], 1·45-1·64). The incidence of pancreatic cancer increased with age and a significantly higher incidence was observed in the older groups with T2DM. However, the relative pancreatic cancer risk was inversely related to age of T2DM onset, and a higher SIR of 5·73 (95%CI, 4·49-7·22) was observed in the 20-54 years old group. The risk of pancreatic cancer was elevated at any diabetes duration. Fasting blood glucose ≥10·0 mmol/L was associated with increased risk of pancreatic cancer. MR analysis indicated a positive association between T2DM and pancreatic cancer risk. Interpretation: Efforts toward early and close follow-up programs, especially in individuals with young-onset T2DM, and the improvement of glucose control might represent effective strategies for improving the detection and results of treatment of pancreatic cancer. Funding: Chinese National Natural Science Foundation.

CVD risk in non-albuminuric chronic kidney disease in hypertensive, non-diabetic subjects: A post-hoc analysis from SPRINT.

Introduction: The risks associated with non-albuminuric chronic kidney disease (CKD) have been investigated in diabetes mellitus but not in hypertensive patients. The objective of this study was to investigate the risks associated with non-albuminuric CKD in treated hypertensive patients in the Systolic Blood Pressure Intervention Trial (SPRINT) population. Methods: Based on baseline albuminuria status (urine albumin/creatinine ratio [UACR], ≥30 or <30 mg/g) and the levels of estimated glomerular filtration rate ([eGFR], ≥60, 45-59, or <45 mL/min/1.73 m2), participants were classified into six subgroups to assess the risks associated with the primary outcome and mortality. The primary composite outcome was myocardial infarction, other acute coronary syndromes, stroke, heart failure, or mortality from cardiovascular causes. Results: During a median follow-up of 3.26 years in 8,866 hypertensive patients, there were 352 deaths and 547 participants with the primary outcome. In adjusted Cox regression analysis using non-CKD and non-albuminuria (eGFR ≥60 mL/min/1.73 m2 combined with UACR <30 mg/g) as reference, albuminuria whether combined with CKD or not, showed significantly higher risk of both primary outcome and all-cause mortality in the total population. Whereas, non-albuminuria only combined with eGFR <45 mL/min/1.73 m2 showed significantly higher risk of both primary outcome and all-cause mortality in the intensive-therapy group. Discussion: Non-albuminuric CKD did have higher risk of all-cause and CVD mortality only if the eGFR <45 mL/min/1.73 m2. Increased albuminuria conferred higher risk of primary outcome and all-cause mortality irrespective the levels of eGFR. Clinical trial registration: ClinicalTrials.gov, number: NCT01206062.

Comparative Safety of Dipeptidyl Peptidase-4 Inhibitors and Sudden Cardiac Arrest and Ventricular Arrhythmia: Population-Based Cohort Studies.

In vivo studies suggest that arrhythmia risk may be greater with less selective dipeptidyl peptidase-4 inhibitors, but evidence from population-based studies is missing. We aimed to compare saxagliptin, sitagliptin, and linagliptin with regard to risk of sudden cardiac arrest (SCA)/ventricular arrhythmia (VA). We conducted high-dimensional propensity score (hdPS) matched, new-user cohort studies. We analyzed Medicaid and Optum Clinformatics separately. We identified new users of saxagliptin, sitagliptin (both databases), and linagliptin (Optum only). We defined SCA/VA outcomes using emergency department and inpatient diagnoses. We identified and then controlled for confounders via a data-adaptive, hdPS approach. We generated marginal hazard ratios (HRs) via Cox proportional hazards regression using a robust variance estimator while adjusting for calendar year. We identified the following matched comparisons: saxagliptin vs. sitagliptin (23,895 vs. 96,972) in Medicaid, saxagliptin vs. sitagliptin (48,388 vs. 117,383) in Optum, and linagliptin vs. sitagliptin (36,820 vs. 78,701) in Optum. In Medicaid, use of saxagliptin (vs. sitagliptin) was associated with an increased rate of SCA/VA (adjusted HR (aHR), 2.01, 95% confidence interval (CI) 1.24-3.25). However, in Optum data, this finding was not present (aHR, 0.79, 95% CI 0.41-1.51). Further, we found no association between linagliptin (vs. sitagliptin) and SCA/VA (aHR, 0.65, 95% CI 0.36-1.17). We found discordant results regarding the association between SCA/VA with saxagliptin compared with sitagliptin in two independent datasets. It remains unclear whether these findings are due to heterogeneity of treatment effect in the different populations, chance, or unmeasured confounding.

DCRM Multispecialty Practice Recommendations for the management of diabetes, cardiorenal, and metabolic diseases.

Type 2 diabetes (T2D), chronic kidney disease (CKD), atherosclerotic cardiovascular disease (ASCVD), and heart failure (HF)-along with their associated risk factors-have overlapping etiologies, and two or more of these conditions frequently occur in the same patient. Many recent cardiovascular outcome trials (CVOTs) have demonstrated the benefits of agents originally developed to control T2D, ASCVD, or CKD risk factors, and these agents have transcended their primary indications to confer benefits across a range of conditions. This evolution in CVOT evidence calls for practice recommendations that are not constrained by a single discipline to help clinicians manage patients with complex conditions involving diabetes, cardiorenal, and/or metabolic (DCRM) diseases. The ultimate goal for these recommendations is to be comprehensive yet succinct and easy to follow by the nonexpert-whether a specialist or a primary care clinician. To meet this need, we formed a volunteer task force comprising leading cardiologists, nephrologists, endocrinologists, and primary care physicians to develop the DCRM Practice Recommendations, a multispecialty consensus on the comprehensive management of the patient with complicated metabolic disease. The task force recommendations are based on strong evidence and incorporate practical guidance that is clinically relevant and simple to implement, with the aim of improving outcomes in patients with DCRM. The recommendations are presented as 18 separate graphics covering lifestyle therapy, patient self-management education, technology for DCRM management, prediabetes, cognitive dysfunction, vaccinations, clinical tests, lipids, hypertension, anticoagulation and antiplatelet therapy, antihyperglycemic therapy, hypoglycemia, nonalcoholic fatty liver disease (NAFLD) and nonalcoholic steatohepatitis (NASH), ASCVD, HF, CKD, and comorbid HF and CKD, as well as a graphical summary of medications used for DCRM.

Early Life Famine Exposure, Ideal Cardiovascular Health Metrics, and Risk of Incident Diabetes: Findings From the 4C Study.

OBJECTIVE: We aim to investigate the impact of ideal cardiovascular health metrics (ICVHMs) on the association between famine exposure and adulthood diabetes risk. RESEARCH DESIGN AND METHODS: This study included 77,925 participants from the China Cardiometabolic Disease and Cancer Cohort (4C) Study who were born around the time of the Chinese Great Famine and free of diabetes at baseline. They were divided into three famine exposure groups according to the birth year, including nonexposed (1963-1974), fetal exposed (1959-1962), and childhood exposed (1949-1958). Relative risk regression was used to examine the associations between famine exposure and ICVHMs on diabetes. RESULTS: During a mean follow-up of 3.6 years, the cumulative incidence of diabetes was 4.2%, 6.0%, and 7.5% in nonexposed, fetal-exposed, and childhood-exposed participants, respectively. Compared with nonexposed participants, fetal-exposed but not childhood-exposed participants had increased risks of diabetes, with multivariable-adjusted risk ratios (RRs) (95% CIs) of 1.17 (1.05-1.31) and 1.12 (0.96-1.30), respectively. Increased diabetes risks were observed in fetal-exposed individuals with nonideal dietary habits, nonideal physical activity, BMI ≥24.0 kg/m2, or blood pressure ≥120/80 mmHg, whereas significant interaction was detected only in BMI strata (P for interaction = 0.0018). Significant interactions have been detected between number of ICVHMs and famine exposure on the risk of diabetes (P for interaction = 0.0005). The increased risk was observed in fetal-exposed participants with one or fewer ICVHMs (RR 1.59 [95% CI 1.24-2.04]), but not in those with two or more ICVHMs. CONCLUSIONS: The increased risk of diabetes associated with famine exposure appears to be modified by the presence of ICVHMs.

Prognostic Significance of Long-term HbA1c Variability for All-Cause Mortality in the ACCORD Trial.

OBJECTIVE: The association between high glycemic variability and all-cause mortality has been widely investigated in epidemiological studies but rarely validated in glucose-lowering clinical trials. We aimed to identify the prognostic significance of visit-to-visit HbA1c variability in treated patients in the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial population. RESEARCH DESIGN AND METHODS: We studied the risk of all-cause mortality in relation to long-term visit-to-visit HbA1c variability, expressed as coefficient of variation (CV), variability independent of the mean (VIM), and average real variability (ARV), from the 8th month to the transition from intensive to standard glycemic therapy. Multivariable Cox proportional hazards models were used to estimate adjusted hazard ratio (HR) and 95% CI. RESULTS: Compared with the standard therapy group (n = 4,728), the intensive therapy group (n = 4,755) had significantly lower mean HbA1c (6.6% [49 mmol/mol] vs. 7.7% [61 mmol/mol], P < 0.0001) and lower CV, VIM, and ARV (P < 0.0001). In multivariate adjusted analysis, all three HbA1c variability indices were significantly associated with total mortality in all patients as well as in the standard- and intensive-therapy groups analyzed separately. The hazard ratios for a 1-SD increase in HbA1c variability indices for all-cause mortality were 1.19 and 1.23 in intensive and standard therapy, respectively. Cross-tabulation analysis showed the third tertile of HbA1c mean and VIM had significantly higher all-cause mortality (HR 2.05; 95% CI 1.17-3.61; P < 0.01) only in the intensive-therapy group. CONCLUSIONS: Long-term visit-to-visit HbA1c variability was a strong predictor of all-cause mortality. HbA1c VIM combined with HbA1c mean conferred an increased risk for all-cause mortality in the intensive-therapy group.

The risk of sudden cardiac arrest and ventricular arrhythmia with rosiglitazone versus pioglitazone: real-world evidence on thiazolidinedione safety.

BACKGROUND: The low cost of thiazolidinediones makes them a potentially valuable therapeutic option for the > 300 million economically disadvantaged persons worldwide with type 2 diabetes mellitus. Differential selectivity of thiazolidinediones for peroxisome proliferator-activated receptors in the myocardium may lead to disparate arrhythmogenic effects. We examined real-world effects of thiazolidinediones on outpatient-originating sudden cardiac arrest (SCA) and ventricular arrhythmia (VA). METHODS: We conducted population-based high-dimensional propensity score-matched cohort studies in five Medicaid programs (California, Florida, New York, Ohio, Pennsylvania | 1999-2012) and a commercial health insurance plan (Optum Clinformatics | 2000-2016). We defined exposure based on incident rosiglitazone or pioglitazone dispensings; the latter served as an active comparator. We controlled for confounding by matching exposure groups on propensity score, informed by baseline covariates identified via a data adaptive approach. We ascertained SCA/VA outcomes precipitating hospital presentation using a validated, diagnosis-based algorithm. We generated marginal hazard ratios (HRs) via Cox proportional hazards regression that accounted for clustering within matched pairs. We prespecified Medicaid and Optum findings as primary and secondary, respectively; the latter served as a conceptual replication dataset. RESULTS: The adjusted HR for SCA/VA among rosiglitazone (vs. pioglitazone) users was 0.91 (0.75-1.10) in Medicaid and 0.88 (0.61-1.28) in Optum. Among Medicaid but not Optum enrollees, we found treatment effect heterogeneity by sex (adjusted HRs = 0.71 [0.54-0.93] and 1.16 [0.89-1.52] in men and women respectively, interaction term p-value = 0.01). CONCLUSIONS: Rosiglitazone and pioglitazone appear to be associated with similar risks of SCA/VA.