Project description:BackgroundEstimated 10-year atherosclerotic cardiovascular disease (ASCVD) risk in diabetes mellitus patients is used to guide primary prevention, but the performance of risk estimators (2013 Pooled Cohort Equations [PCE] and Risk Equations for Complications of Diabetes [RECODe]) varies across populations. Data from electronic health records could be used to improve risk estimation for a health system's patients. We aimed to evaluate risk equations for initial ASCVD events in US veterans with diabetes mellitus and improve model performance in this population.Methods and resultsWe studied 183 096 adults with diabetes mellitus and without prior ASCVD who received care in the Veterans Affairs Healthcare System (VA) from 2002 to 2016 with mean follow-up of 4.6 years. We evaluated model discrimination, using Harrell's C statistic, and calibration, using the reclassification χ2 test, of the PCE and RECODe equations to predict fatal or nonfatal myocardial infarction or stroke and cardiovascular mortality. We then tested whether model performance was affected by deriving VA-specific β-coefficients. Discrimination of ASCVD events by the PCE was improved by deriving VA-specific β-coefficients (C statistic increased from 0.560 to 0.597) and improved further by including measures of glycemia, renal function, and diabetes mellitus treatment (C statistic, 0.632). Discrimination by the RECODe equations was improved by substituting VA-specific coefficients (C statistic increased from 0.604 to 0.621). Absolute risk estimation by PCE and RECODe equations also improved with VA-specific coefficients; the calibration P increased from <0.001 to 0.08 for PCE and from <0.001 to 0.005 for RECODe, where higher P indicates better calibration. Approximately two-thirds of veterans would meet a guideline indication for high-intensity statin therapy based on the PCE versus only 10% to 15% using VA-fitted models.ConclusionsExisting ASCVD risk equations overestimate risk in veterans with diabetes mellitus, potentially impacting guideline-indicated statin therapy. Prediction model performance can be improved for a health system's patients using readily available electronic health record data.
Project description:AimsThe 10-year risk of recurrent atherosclerotic cardiovascular disease (ASCVD) events in patients with established ASCVD can be estimated with the Secondary Manifestations of ARTerial disease (SMART) risk score, and may help refine clinical management. To broaden generalizability across regions, we updated the existing tool (SMART2 risk score) and recalibrated it with regional incidence rates and assessed its performance in external populations.Methods and resultsIndividuals with coronary artery disease, cerebrovascular disease, peripheral artery disease, or abdominal aortic aneurysms were included from the Utrecht Cardiovascular Cohort-SMART cohort [n = 8355; 1706 ASCVD events during a median follow-up of 8.2 years (interquartile range 4.2-12.5)] to derive a 10-year risk prediction model for recurrent ASCVD events (non-fatal myocardial infarction, non-fatal stroke, or cardiovascular mortality) using a Fine and Gray competing risk-adjusted model. The model was recalibrated to four regions across Europe, and to Asia (excluding Japan), Japan, Australia, North America, and Latin America using contemporary cohort data from each target region. External validation used data from seven cohorts [Clinical Practice Research Datalink, SWEDEHEART, the international REduction of Atherothrombosis for Continued Health (REACH) Registry, Estonian Biobank, Spanish Biomarkers in Acute Coronary Syndrome and Biomarkers in Acute Myocardial Infarction (BACS/BAMI), the Norwegian COgnitive Impairment After STroke, and Bialystok PLUS/Polaspire] and included 369 044 individuals with established ASCVD of whom 62 807 experienced an ASCVD event. C-statistics ranged from 0.605 [95% confidence interval (CI) 0.547-0.664] in BACS/BAMI to 0.772 (95% CI 0.659-0.886) in REACH Europe high-risk region. The clinical utility of the model was demonstrated across a range of clinically relevant treatment thresholds for intensified treatment options.ConclusionThe SMART2 risk score provides an updated, validated tool for the prediction of recurrent ASCVD events in patients with established ASCVD across European and non-European populations. The use of this tool could allow for a more personalized approach to secondary prevention based upon quantitative rather than qualitative estimates of residual risk.
Project description:ImportanceCurrent guidelines recommend statin therapy for millions of US residents for the primary prevention of atherosclerotic cardiovascular disease (ASCVD). It is unclear whether traditional prediction models that do not account for current widespread statin use are sufficient for risk assessment.ObjectivesTo examine the performance of the Pooled Cohort Equations (PCE) for 5-year ASCVD risk estimation in a contemporary cohort and to test the hypothesis that inclusion of statin therapy improves model performance.Design, setting, and participantsThis cohort study included adult patients in the Veterans Affairs health care system without baseline ASCVD. Using national electronic health record data, 3 Cox proportional hazards models were developed to estimate 5-year ASCVD risk, as follows: the variables and published β coefficients from the PCE (model 1), the PCE variables with cohort-derived β coefficients (model 2), and model 2 plus baseline statin use (model 3). Data were collected from January 2002 to December 2012 and analyzed from June 2016 to March 2020.ExposuresTraditional ASCVD risk factors from the PCE plus baseline statin use.Main outcomes and measuresIncident ASCVD and ASCVD mortality.ResultsOf 1 672 336 patients in the cohort (mean [SD] baseline age 58.0 [13.8] years, 1 575 163 [94.2%] men, 1 383 993 [82.8%] white), 312 155 (18.7%) were receiving statin therapy at baseline. During 5 years of follow-up, 66 605 (4.0%) experienced an ASCVD event, and 31 878 (1.9%) experienced ASCVD death. Compared with the original PCE, the cohort-derived model did not improve model discrimination in any of the 4 age-sex strata but did improve model calibration. The PCE overestimated ASCVD risk compared with the cohort-derived model; 211 237 of 1 136 161 white men (18.6%), 29 634 of 218 463 black men (13.6%), 1741 of 44 399 white women (3.9%), and 836 of 16 034 black women (5.2%) would be potentially eligible for statin therapy under the PCE but not the cohort-derived model. When added to the cohort-derived model, baseline statin therapy was associated with a 7% (95% CI, 5%-9%) lower relative risk of ASCVD and a 25% (95% CI, 23%-28%) lower relative risk for ASCVD death.Conclusions and relevanceIn this study, lower than expected rates of incident ASCVD events in a contemporary national cohort were observed. The PCE overestimated ASCVD risk, and more than 15% of patients would be potentially eligible for statin therapy based on the PCE but not on a cohort-derived model. In the statin era, health care professionals and systems should base ASCVD risk assessment on models calibrated to their patient populations.
Project description:AimsFinerenone, a selective, non-steroidal mineralocorticoid receptor antagonist, improves cardiovascular (CV) and kidney outcomes in patients with type 2 diabetes (T2D) and chronic kidney disease (CKD). This subgroup analysis of FIDELITY, a pre-specified, pooled, individual patient-data analysis of FIDELIO-DKD (NCT02540993) and FIGARO-DKD (NCT02545049), compared finerenone vs. placebo in patients with and without baseline history of atherosclerotic CV disease (ASCVD).Methods and resultsOutcomes included a composite CV outcome [CV death, non-fatal myocardial infarction, non-fatal stroke, or hospitalization for heart failure (HHF)]; CV death or HHF; a composite kidney outcome (kidney failure, sustained estimated glomerular filtration rate decrease ≥57%, or kidney-related death); all-cause mortality; and safety by baseline history of ASCVD.Of 13 026 patients, 5935 (45.6%) had a history of ASCVD. The incidence of the composite CV outcome, CV death or HHF, and all-cause mortality was higher in patients with ASCVD vs. those without, with no difference between groups in the composite kidney outcome. Finerenone consistently reduced outcomes vs. placebo in patients with and without ASCVD (P-interaction for the composite CV outcome, CV death or HHF, the composite kidney outcome, and all-cause mortality 0.38, 0.68, 0.33, and 0.38, respectively). Investigator-reported treatment-emergent adverse events were consistent between treatment arms across ASCVD subgroups.ConclusionFinerenone reduced the risk of CV and kidney outcomes consistently across the spectrum of CKD in patients with T2D, irrespective of prevalent ASCVD.
Project description:Cardiovascular disease remains the principal cause of death and disability among patients with diabetes mellitus. Diabetes mellitus exacerbates mechanisms underlying atherosclerosis and heart failure. Unfortunately, these mechanisms are not adequately modulated by therapeutic strategies focusing solely on optimal glycemic control with currently available drugs or approaches. In the setting of multifactorial risk reduction with statins and other lipid-lowering agents, antihypertensive therapies, and antihyperglycemic treatment strategies, cardiovascular complication rates are falling, yet remain higher for patients with diabetes mellitus than for those without. This review considers the mechanisms, history, controversies, new pharmacological agents, and recent evidence for current guidelines for cardiovascular management in the patient with diabetes mellitus to support evidence-based care in the patient with diabetes mellitus and heart disease outside of the acute care setting.
Project description:Risk factors for cardiovascular disease (CVD) are well-established in type 2 but not type 1 diabetes (T1DM). We assessed risk factors in the long-term (mean 27 years) follow-up of the Diabetes Control and Complications Trial (DCCT) cohort with T1DM. Cox proportional hazards multivariate models assessed the association of traditional and novel risk factors, including HbA1c, with major atherosclerotic cardiovascular events (MACE) (fatal or nonfatal myocardial infarction [MI] or stroke) and any-CVD (MACE plus confirmed angina, silent MI, revascularization, or congestive heart failure). Age and mean HbA1c were strongly associated with any-CVD and with MACE. For each percentage point increase in mean HbA1c, the risk for any-CVD and for MACE increased by 31 and 42%, respectively. CVD and MACE were associated with seven other conventional factors, such as blood pressure, lipids, and lack of ACE inhibitor use, but not with sex. The areas under the receiver operating characteristics curves for the association of age and HbA1c, taken together with any-CVD and for MACE, were 0.70 and 0.77, respectively, and for the final models, including all significant risk factors, were 0.75 and 0.82. Although many conventional CVD risk factors apply in T1DM, hyperglycemia is an important risk factor second only to age.
Project description:Introduction: Age is a major risk factor that affects the likelihood of developing atherosclerotic cardiovascular disease (ASCVD). The anticipated 10-year ASCVD risk for nearly all individuals aged 70 years and older surpasses conventional risk thresholds. When considering treatment for risk factors, it is important to take into account ASCVD risk modifiers, such as malnutrition, polypharmacy, and comorbidities. Objectives: The aim of this study was to estimate ASCVD risk in apparently healthy (without established ASCVD) elderly persons. We also evaluated several biochemical and clinical indicators to better characterize the studied population. Patients and methods: A total of 253 elderly individuals aged 70 years and older, who were apparently healthy and did not have established atherosclerotic cardiovascular disease (ASCVD), were enrolled in the study. The Systemic Coronary Risk Estimation 2-Older Persons (SCORE2-OP) model was utilized to assess their 10-year risk of developing ASCVD. Results: Among the 253 participants, 41 (16.2%) were classified as high risk, while 212 (83.8%) were categorized as very high risk. No individuals had a low ASCVD risk (defined as less than 7.5%). The median 10-year risk of developing ASCVD for the study group was 23% (ranging from 17% to 32%). The number of individuals identified as very high risk increased significantly with age, with nearly all participants aged 75 years and older being considered very high risk. An age of 75 years or older is associated with a very high risk for ASCVD, supported by a C-statistic of 0.92, which reflects a positive predictive value (PPV) of 99% and a negative predictive value (NPV) of 52% (p < 0.001). Conclusions: Elderly individuals without established ASCVD constitute a varied group. The majority were identified as being at very high risk for ASCVD. Age and hypertension were the primary factors contributing to this risk. Furthermore, modifiers of ASCVD risk, including malnutrition, polypharmacy, and multimorbidity, were commonly observed.
Project description:Aims/hypothesisType 2 diabetes is a heterogeneous disease process with variable trajectories of CVD risk. We aimed to evaluate four phenomapping strategies and their ability to stratify CVD risk in individuals with type 2 diabetes and to identify subgroups who may benefit from specific therapies.MethodsParticipants with type 2 diabetes and free of baseline CVD in the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial were included in this study (N = 6466). Clustering using Gaussian mixture models, latent class analysis, finite mixture models (FMMs) and principal component analysis was compared. Clustering variables included demographics, medical and social history, laboratory values and diabetes complications. The interaction between the phenogroup and intensive glycaemic, combination lipid and intensive BP therapy for the risk of the primary outcome (composite of fatal myocardial infarction, non-fatal myocardial infarction or unstable angina) was evaluated using adjusted Cox models. The phenomapping strategies were independently assessed in an external validation cohort (Look Action for Health in Diabetes [Look AHEAD] trial: n = 4211; and Bypass Angioplasty Revascularisation Investigation 2 Diabetes [BARI 2D] trial: n = 1495).ResultsOver 9.1 years of follow-up, 789 (12.2%) participants had a primary outcome event. FMM phenomapping with three phenogroups was the best-performing clustering strategy in both the derivation and validation cohorts as determined by Bayesian information criterion, Dunn index and improvement in model discrimination. Phenogroup 1 (n = 663, 10.3%) had the highest burden of comorbidities and diabetes complications, phenogroup 2 (n = 2388, 36.9%) had an intermediate comorbidity burden and lowest diabetes complications, and phenogroup 3 (n = 3415, 52.8%) had the fewest comorbidities and intermediate burden of diabetes complications. Significant interactions were observed between phenogroups and treatment interventions including intensive glycaemic control (p-interaction = 0.042) and combination lipid therapy (p-interaction < 0.001) in the ACCORD, intensive lifestyle intervention (p-interaction = 0.002) in the Look AHEAD and early coronary revascularisation (p-interaction = 0.003) in the BARI 2D trial cohorts for the risk of the primary composite outcome. Favourable reduction in the risk of the primary composite outcome with these interventions was noted in low-risk participants of phenogroup 3 but not in other phenogroups. Compared with phenogroup 3, phenogroup 1 participants were more likely to have severe/symptomatic hypoglycaemic events and medication non-adherence on follow-up in the ACCORD and Look AHEAD trial cohorts.Conclusions/interpretationClustering using FMMs was the optimal phenomapping strategy to identify replicable subgroups of patients with type 2 diabetes with distinct clinical characteristics, CVD risk and response to therapies.
Project description:Aims/hypothesisThis study explored the hypothesis that significant abnormalities in the metabolism of intestinally derived lipoproteins are present in individuals with type 2 diabetes on statin therapy. These abnormalities may contribute to residual CVD risk.MethodsTo investigate the kinetics of ApoB-48- and ApoB-100-containing lipoproteins, we performed a secondary analysis of 11 overweight/obese individuals with type 2 diabetes who were treated with lifestyle counselling and on a stable dose of metformin who were from an earlier clinical study, and compared these with 11 control participants frequency-matched for age, BMI and sex. Participants in both groups were on a similar statin regimen during the study. Stable isotope tracers were used to determine the kinetics of the following in response to a standard fat-rich meal: (1) apolipoprotein (Apo)B-48 in chylomicrons and VLDL; (2) ApoB-100 in VLDL, intermediate-density lipoprotein (IDL) and LDL; and (3) triglyceride (TG) in VLDL.ResultsThe fasting lipid profile did not differ significantly between the two groups. Compared with control participants, in individuals with type 2 diabetes, chylomicron TG and ApoB-48 levels exhibited an approximately twofold higher response to the fat-rich meal, and a twofold higher increment was observed in ApoB-48 particles in the VLDL1 and VLDL2 density ranges (all p < 0.05). Again comparing control participants with individuals with type 2 diabetes, in the latter, total ApoB-48 production was 25% higher (556 ± 57 vs 446 ± 57 mg/day; p < 0.001), conversion (fractional transfer rate) of chylomicrons to VLDL was around 40% lower (35 ± 25 vs 82 ± 58 pools/day; p=0.034) and direct clearance of chylomicrons was 5.6-fold higher (5.6 ± 2.2 vs 1.0 ± 1.8 pools/day; p < 0.001). During the postprandial period, ApoB-48 particles accounted for a higher proportion of total VLDL in individuals with type 2 diabetes (44%) compared with control participants (25%), and these ApoB-48 VLDL particles exhibited a fivefold longer residence time in the circulation (p < 0.01). No between-group differences were seen in the kinetics of ApoB-100 and TG in VLDL, or in LDL ApoB-100 production, pool size and clearance rate. As compared with control participants, the IDL ApoB-100 pool in individuals with type 2 diabetes was higher due to increased conversion from VLDL2.Conclusions/interpretationAbnormalities in the metabolism of intestinally derived ApoB-48-containing lipoproteins in individuals with type 2 diabetes on statins may help to explain the residual risk of CVD and may be suitable targets for interventions.Trial registrationClinicalTrials.gov NCT02948777.
Project description:AimsChronic kidney disease (CKD) and diabetes mellitus increase atherosclerotic cardiovascular diseases (ASCVD) risk. However, the association between renal outcome of diabetic kidney disease (DKD) and ASCVD risk is unclear.MethodsThis retrospective study enrolled 218 type 2 diabetic patients with biopsy-proven DKD, and without known cardiovascular diseases. Baseline characteristics were obtained and the 10-year ASCVD risk score was calculated using the Pooled Cohort Equation (PCE). Renal outcome was defined as progression to end-stage renal disease (ESRD). The association between ASCVD risk and renal function and outcome was analyzed with logistic regression and Cox analysis.ResultsAmong all patients, the median 10-year ASCVD risk score was 14.1%. The median of ASCVD risk score in CKD stage 1, 2, 3, and 4 was 10.9%, 12.3%, 16.5%, and 14.8%, respectively (p = 0.268). Compared with patients with lower ASCVD risk (<14.1%), those with higher ASCVD risk had lower eGFR, higher systolic blood pressure, and more severe renal interstitial inflammation. High ASCVD risk (>14.1%) was an independent indicator of renal dysfunction in multivariable-adjusted logistic analysis (OR, 3.997; 95%CI, 1.385-11.530; p = 0.010), though failed to be an independent risk factor for ESRD in patients with DKD in univariate and multivariate Cox analysis.ConclusionsDKD patients even in CKD stage 1 had comparable ASCVD risk score to patients in CKD stage 2, 3, and 4. Higher ASCVD risk indicated severe renal insufficiency, while no prognostic value of ASVCD risk for renal outcome was observed, which implied macroangiopathy and microangiopathy in patients with DKD were related, but relatively independent.