Dataset Information

Remnant Cholesterol and Its Visit-to-Visit Variability Predict Cardiovascular Outcomes in Patients With Type 2 Diabetes: Findings From the ACCORD Cohort.

ABSTRACT:

Objective

Remnant cholesterol (remnant-C) predicts atherosclerotic cardiovascular disease, regardless of LDL-cholesterol (LDL-C) levels. This study assessed the associations between remnant-C and cardiovascular outcomes in type 2 diabetes.

Research design and methods

This post hoc analysis of the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial used patient (type 2 diabetes >3 months) remnant-C and major adverse cardiovascular event (MACE) data from the study database. The associations between remnant-C and MACEs were evaluated using Cox proportional hazards regression analyses. We examined the relative MACE risk in remnant-C versus LDL-C discordant/concordant groups using clinically relevant LDL-C targets by discordance analyses.

Results

The baseline analysis included 10,196 participants, with further visit-to-visit variability analysis including 9,650 participants. During follow-up (median, 8.8 years), 1,815 patients (17.8%) developed MACEs. After adjusting for traditional cardiovascular risk factors, each 1-SD increase in remnant-C was associated with a 7% higher MACE risk (hazard ratio [HR] 1.07, 95% CI 1.02-1.12, P = 0.004). In the fully adjusted model, the visit-to-visit remnant-C variability calculated using logSD (HR 1.41, 95% CI 1.18-1.69, P < 0.001) and logARV (HR 1.45, 95% CI 1.22-1.73, P < 0.001) was associated with MACEs. Residual lipid risk (remnant-C ≥31 mg/dL) recognized individuals at a higher MACE risk, regardless of LDL-C concentrations. Within each LDL-C subgroup (>100 or ≤100 mg/dL), high baseline remnant-C was associated with a higher MACE risk (HR 1.37, 95% CI 1.09-1.73, P = 0.007; HR 1.22, 95% CI 1.04-1.41, P = 0.015, respectively).

Conclusions

Remnant-C levels were associated with MACEs in patients with type 2 diabetes independent of LDL-C, and visit-to-visit remnant-C variability helped identify those with higher cardiovascular risk.

SUBMITTER: Fu L

PROVIDER: S-EPMC9472497 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Remnant Cholesterol and Its Visit-to-Visit Variability Predict Cardiovascular Outcomes in Patients With Type 2 Diabetes: Findings From the ACCORD Cohort.

Fu Liyao L Tai Shi S Sun Jiaxing J Zhang Ningjie N Zhou Ying Y Xing Zhenhua Z Wang Yongjun Y Zhou Shenghua S

Diabetes care 20220901 9

<h4>Objective</h4>Remnant cholesterol (remnant-C) predicts atherosclerotic cardiovascular disease, regardless of LDL-cholesterol (LDL-C) levels. This study assessed the associations between remnant-C and cardiovascular outcomes in type 2 diabetes.<h4>Research design and methods</h4>This post hoc analysis of the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial used patient (type 2 diabetes >3 months) remnant-C and major adverse cardiovascular event (MACE) data from the study datab ...[more]

PMID: 35834242

Similar Datasets

Project description:BackgroundAlthough recent guidelines advocate for HbA1c target individualization, a comprehensive criterion for patient categorization remains absent. This study aimed to categorize HbA1c variability levels and explore the relationship between glycemic control, cardiovascular outcomes, and mortality across different degrees of variability.MethodsAction to Control Cardiovascular Risk in Diabetes study data were used. HbA1c variability was measured using the HbA1c variability score (HVS) and standard deviation (SD). K-means and K-medians clustering were used to combine the HVS and SD.ResultsK-means clustering was the most stable algorithm with the lowest clustering similarities. In the low variability group, intensive glucose-lowering treatment significantly reduced the risk of adverse cardiovascular outcomes (HR: 0·78 [95% CI: 0·63, 0·97]) without increasing mortality risk (HR: 1·07 [0.81, 1·42]); the risk of adverse cardiovascular events (HR: 1·33 [1·14, 1·56]) and all-cause mortality (HR: 1·23 [1·01,1·51]) increased with increasing mean HbA1c. In the high variability group, treatment increased the risk of cardiovascular events (HR: 2.00 [1·54, 2·60]) and mortality (HR: 2·20 [1·66, 2·92]); a higher mean HbA1c (7·86%, [7·66%, 8·06%]) had the lowest mortality risk, when the mean HbA1c was < 7·86%, a higher mean HbA1c was associated with a lower mortality risk (HR: 0·63 [0·42, 0·95]). In the medium variability group, a mean HbA1c around 7·5% was associated with the lowest risk.ConclusionsHbA1c variability can guide glycemic control targets for patients with type 2 diabetes. For patients with low variability, the lower the HbA1c, the lower the risk. For those with medium variability, controlling HbA1c at 7·5% provides the maximum benefit. For patients with high variability, a mean HbA1c of around 7·8% presents the lowest risk of all-cause mortality, a lower HbA1c did not provide cardiovascular benefits but instead increased the mortality risk. Further studies, especially those with patients that reflect the general population with type 2 diabetes undergoing the latest therapeutic approaches, are essential to validate the conclusions of this study.

Project description:AimTo explore the association between the non-high-density lipoprotein cholesterol (HDL-C)/HDL-C ratio (NHHR) and the risk of major adverse cardiovascular events (MACEs) and overall mortality in patients with type 2 diabetes mellitus (T2DM).Materials and methodsNHHR, calculated as (total cholesterol - HDL-C)/HDL-C, was evaluated in 10,188 participants. Cox proportional hazard regression models were employed to assess the association of NHHR with future risk of MACEs and overall mortality. Restricted cubic spline analysis, smooth curve fitting and piecewise regression models were utilized to explore the non-linear correlation and establish the threshold. Subgroup and interaction analyses verified the robustness of the findings. The area under the receiver operating characteristic area under the curve assessed the additional predictive value of NHHR beyond conventional risk factors.ResultsAfter adjusting for confounding factors, each 1-unit increase in NHHR was associated with a 12% increased risk of MACEs (hazard ratio [HR]: 1.12, 95% confidence interval [CI]: 1.07-1.16; p < 0.0001), a 5% increase in overall mortality (HR: 1.05, 95% CI: 1.01-1.10; p = 0.0256), a 10% increase in cardiovascular disease mortality (HR 1.10, 95% CI: 1.03-1.18; p = 0.0074), an 12% increase in non-fatal myocardial infarction (HR: 1.12, 95% CI: 1.05-1.18; p = 0.0002), and an 11% increase in non-fatal stroke (HR: 1.11, 95% CI: 1.02-1.20; p = 0.0123). Analyses showed a non-linear relationship between NHHR and MACEs in patients with T2DM (non-linearity p < 0.001). A two-stage linear regression model identified a threshold for MACEs at 6.28. Integration NHHR into the conventional model significantly enhanced predictive accuracy for MACEs.ConclusionsNHHR is a predictor of the risk of developing MACEs and overall mortality in patients with T2DM, with higher NHHR values independently associated with increased future MACE risks after full adjustment for confounders.

Project description:Aims/hypothesisElevated remnant cholesterol is observationally and causally associated with increased risk of atherosclerotic cardiovascular disease (ASCVD) in the general population. This association is not well studied in individuals with diabetes, who are often included in clinical trials of remnant cholesterol-lowering therapy. We tested the hypothesis that elevated remnant cholesterol is associated with increased risk of ASCVD in individuals with diabetes. We also explored the fraction of excess risk conferred by diabetes which can be explained by elevated remnant cholesterol.MethodsWe included 4569 white Danish individuals with diabetes (58% statin users) nested within the Copenhagen General Population Study (2003-2015). The ASCVDs peripheral artery disease, myocardial infarction and ischaemic stroke were extracted from national Danish health registries without losses to follow-up. Remnant cholesterol was calculated from a standard lipid profile.ResultsDuring up to 15 years of follow-up, 236 individuals were diagnosed with peripheral artery disease, 234 with myocardial infarction, 226 with ischaemic stroke and 498 with any ASCVD. Multivariable adjusted HR (95% CI) per doubling of remnant cholesterol was 1.6 (1.1, 2.3; p=0.01) for peripheral artery disease, 1.8 (1.2, 2.5; p=0.002) for myocardial infarction, 1.5 (1.0, 2.1; p=0.04) for ischaemic stroke, and 1.6 (1.2, 2.0; p=0.0003) for any ASCVD. Excess risk conferred by diabetes was 2.5-fold for peripheral artery disease, 1.6-fold for myocardial infarction, 1.4-fold for ischaemic stroke and 1.6-fold for any ASCVD. Excess risk explained by elevated remnant cholesterol and low-grade inflammation was 14% and 8% for peripheral artery disease, 26% and 16% for myocardial infarction, 34% and 34% for ischaemic stroke, and 24% and 18% for any ASCVD, respectively. LDL-cholesterol did not explain excess risk, as it was not higher in individuals with diabetes. We also explored the fraction of excess risk conferred by diabetes which can be explained by elevated remnant cholesterol.Conclusions/interpretationElevated remnant cholesterol was associated with increased risk of ASCVD in individuals with diabetes. Remnant cholesterol and low-grade inflammation explained substantial excess risk of ASCVD conferred by diabetes. Whether remnant cholesterol should be used as a treatment target remains to be determined in randomised controlled trials.

Dataset Information

Remnant Cholesterol and Its Visit-to-Visit Variability Predict Cardiovascular Outcomes in Patients With Type 2 Diabetes: Findings From the ACCORD Cohort.

Objective

Research design and methods

Results

Conclusions

Publications

Remnant Cholesterol and Its Visit-to-Visit Variability Predict Cardiovascular Outcomes in Patients With Type 2 Diabetes: Findings From the ACCORD Cohort.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets