Greater variability in lipid measurements associated with cardiovascular disease and mortality: A 10-year diabetes cohort study

Association Between Nutrients and Cardiovascular Diseases

Cardiovascular diseases (CVD) constitute a leading cause of global mortality. Inflammation and oxidative stress are key molecular underpinnings of CVD pathogenesis. This comprehensive review explores the multifaceted role of nutrients in cardiovascular health beyond their impact on cardiac events. The manuscript examines the influence of macronutrients such as fats and carbohydrates, as well as micronutrients including vitamins and folate, on CVD. Additionally, the interplay between dietary supplements and CVD risk reduction is investigated. The purpose of this manuscript is to provide a comprehensive overview of the diverse mechanisms through which nutrients contribute to cardiovascular well-being, addressing both cardioprotective effects and their broader implications. Through an analysis of pertinent studies, we illuminate the complex relationship between nutrition, lifestyle, and cardiovascular health, underscoring the significance of a holistic approach to CVD prevention and management.

Lipid variability and risk of microvascular complications in patients with diabetes: a systematic review and meta-analysis

BACKGROUND AND AIMS

The current systematic review aimed to elucidate the effects of lipid variability on microvascular complication risk in diabetic patients. The lipid components studied were as follows: High-density lipoprotein (HDL), High-density lipoprotein (LDL), Triglyceride (TG), Total Cholesterol (TC), and Remnant Cholesterol (RC).

METHOD

We carried out a systematic search in multiple databases, including PubMed, Web of Science, and SCOPUS, up to October 2nd, 2023. After omitting the duplicates, we screened the title and abstract of the studies. Next, we retrieved and reviewed the full text of the remaining articles and included the ones that met our inclusion criteria in the study.

RESULT

In this research, we examined seven studies, comprising six cohort studies and one cross-sectional study. This research was conducted in Hong Kong, China, Japan, Taiwan, Finland, and Italy. The publication years of these articles ranged from 2012 to 2022, and the duration of each study ranged from 5 to 14.3 years. The study group consisted of patients with type 2 diabetes aged between 45 and 84 years, with a diabetes history of 7 to 12 years. These studies have demonstrated that higher levels of LDL, HDL, and TG variability can have adverse effects on microvascular complications, especially nephropathy and neuropathic complications. TG and LDL variability were associated with the development of albuminuria and GFR decline. Additionally, reducing HDL levels showed a protective effect against microalbuminuria. However, other studies did not reveal an apparent relationship between lipid variations and microvascular complications, such as retinopathy. Current research lacks geographic and demographic diversity. Increased HDL, TG, and RC variability have been associated with several microvascular difficulties. Still, the pathogenic mechanism is not entirely known, and understanding how lipid variability affects microvascular disorders may lead to novel treatments. Furthermore, the current body of this research is restricted in its coverage. This field's lack of thorough investigations required a more extensive study and comprehensive effort.

CONCLUSION

The relationship between lipid variation (LDL, HDL, and TG) (adverse effects) on microvascular complications, especially nephropathy and neuropathic (and maybe not retinopathy), is proven. Physicians and health policymakers should be highly vigilant to lipid variation in a general population.

Association between menstrual cycle phase and metabolites in healthy, regularly menstruating women in UK Biobank, and effect modification by inflammatory markers and risk factors for metabolic disease

BACKGROUND

Preliminary evidence demonstrates some parameters of metabolic control, including glycaemic control, lipid control and insulin resistance, vary across the menstrual cycle. However, the literature is inconsistent, and the underlying mechanisms remain uncertain. This study aimed to investigate the association between the menstrual cycle phase and metabolites and to explore potential mediators and moderators of these associations.

METHODS

We undertook a cross-sectional cohort study using UK Biobank. The outcome variables were glucose; triglyceride; triglyceride to glucose index (TyG index); total, HDL and LDL cholesterol; and total to HDL cholesterol ratio. Generalised additive models (GAM) were used to investigate non-linear associations between the menstrual cycle phase and outcome variables. Anthropometric, lifestyle, fitness and inflammatory markers were explored as potential mediators and moderators of the associations between the menstrual cycle phase and outcome variables.

RESULTS

Data from 8694 regularly menstruating women in UK Biobank were analysed. Non-linear associations were observed between the menstrual cycle phase and total (p < 0.001), HDL (p < 0.001), LDL (p = 0.012) and total to HDL cholesterol (p < 0.001), but not glucose (p = 0.072), triglyceride (p = 0.066) or TyG index (p = 0.100). Neither anthropometric, physical fitness, physical activity, nor inflammatory markers mediated the associations between the menstrual cycle phase and metabolites. Moderator analysis demonstrated a greater magnitude of variation for all metabolites across the menstrual cycle in the highest and lowest two quartiles of fat mass and physical activity, respectively.

CONCLUSIONS

Cholesterol profiles exhibit a non-linear relationship with the menstrual cycle phase. Physical activity, anthropometric and fitness variables moderate the associations between the menstrual cycle phase and metabolite concentration. These findings indicate the potential importance of physical activity and fat mass as modifiable risk factors of the intra-individual variation in metabolic control across the menstrual cycle in pre-menopausal women.

Effect of cholesterol variability on the incidence of cataract, dementia, and osteoporosis: A study using a common data model

The effects of cholesterol variability on cataracts, dementia, and osteoporosis remain controversial. Using a common data model, we investigated the effects of variations in cholesterol levels on the development of cataracts, dementia, and osteoporosis. Patients who received statin therapy between 2011 and 2020 and those with 3 or more tests for total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglyceride (TG) levels were included. The patients were divided into those with a coefficient of variation (CV) of TC higher than the mean (high-CV group) and those with a lower CV of TC (low-CV group). Moreover, 1:1 propensity score matching was conducted based on demographic variables. Cataract, dementia, or osteoporosis was defined as having a diagnostic, drug, or surgical code based on the cohort definition. Of the 12,882 patients, cataracts, dementia, and osteoporosis were developed in 525 (4.1%), 198 (1.5%), and 438 (3.4%) patients, respectively. The stratified Cox proportional hazards model showed that the incidences of cataracts and osteoporosis were 1.38 and 1.45 times greater in the high-CV group than in the low-CV group, respectively. Our study revealed that TC variability is associated with developing cataracts and osteoporosis.

The LDL-C/ApoB ratio predicts cardiovascular and all-cause mortality in the general population

BACKGROUND

Generally, low-density lipoprotein (LDL) particle size can be inferred from the LDL cholesterol concentration to total apolipoprotein B concentration ratio (LDL-C/ApoB ratio, hereinafter called LAR), which is a good predictor of cardiovascular disease. However, the predictive ability of LAR for mortality risk in the general population is still unclear. This study aimed to explore the association between LAR and cardiovascular as well as all-cause mortality among American adults.

METHODS

The present study was a secondary analysis of existing data from the National Health and Nutrition Examination Survey (NHANES). The final analysis included 12,440 participants from 2005 to 2014. Survival differences between groups were visualized using Kaplan‒Meier curves and the log-rank test. The association of LAR with cardiovascular and all-cause mortality was evaluated using multivariate Cox regression and restricted cubic spline analysis. Age, sex, coronary artery disease, diabetes, lipid-lowering medication use and hypertriglyceridemia were analyzed in subgroup analyses.

RESULTS

The median age in the study cohort was 46.0 years [interquartile range (IQR): 31.0-62.0], and 6,034 (48.5%) participants were male. During the follow-up period, there were 872 (7.0%) all-cause deaths and 150 (1.2%) cardiovascular deaths. Compared with individuals without cardiovascular events, those who experienced cardiovascular deaths had a lower LAR (1.13 vs. 1.25) (P < 0.001). The adjusted Cox regression model indicated that lower LAR was an independent risk factor for both cardiovascular [hazard ratio (HR) = 0.304, 95% confidence interval (CI): 0.114-0.812] and all-cause mortality (HR = 0.408, 95% CI: 0.270-0.617). Moreover, a significant age interaction was observed (P for interaction < 0.05), and there was a strong association between LAR and mortality among participants over 65 years of age. Further analysis showed an inverse association between LAR and both cardiovascular and all-cause mortality.

CONCLUSIONS

LAR can independently predict cardiovascular and all-cause mortality in the general population.

Effects of metabolic parameters' variability on cardiovascular outcomes in diabetic patients

BACKGROUND

Metabolic abnormalities such as dyslipidemia, glucose and high blood pressure are common in diabetic patients. Visit-to-visit variabilities in these measures have been reported as potential residual cardiovascular risk factors. However, the relationship between these variabilities and their effects on cardiovascular prognosis have not been studied.

METHODS

A total of 22,310 diabetic patients with ≥ 3 measurements of systolic blood pressure (SBP), blood glucose, total cholesterol (TC), and triglyceride (TG) levels during a minimum of three years at three tertiary general hospitals were selected. They were divided into high/low variability groups for each variable based on the coefficient of variation (CV) values. The primary outcome was the incidence of major adverse cardiovascular events (MACE), a composite of cardiovascular death, myocardial infarction, and stroke.

RESULTS

All high CV groups had a higher incidence of MACE than those with low CV (6.0% vs. 2.5% for SBP-CV groups, 5.5% vs. 3.0% for TC-CV groups, 4.7% vs. 3.8% for TG-CV groups, 5.8% vs. 2.7% for glucose-CV groups). In multivariable Cox regression analysis,, high SBP-CV (HR 1.79 [95% CI 1.54-2.07], p < 0.01), high TC-CV (HR 1.54 [95% CI 1.34-1.77], p < 0.01), high TG-CV (HR 1.15 [95% CI 1.01-1.31], p = 0.040) and high glucose-CV (HR 1.61 [95% CI 1.40-1.86], p < 0.01) were independent predictors of MACE.

CONCLUSION

Variability of SBP, TC, TG and glucose are important residual risk factors for cardiovascular events in diabetic patients.

The relationship of low-density lipoprotein cholesterol and all-cause or cardiovascular mortality in patients with type 2 diabetes: a retrospective study

Background

The optimal levels of low-density lipoprotein cholesterol (LDL-C) in patients with type 2 diabetes (T2D) are not currently clear. In this study, we determined the relationship between various mean LDL-C and all-cause or cardiovascular mortality risks in patients with T2D, stratifying by albumin level, age, sex, and antilipid medication use. We also evaluated the association of LDL-C standard deviation (LDL-C-SD) and all-cause and cardiovascular mortality by type of antilipid medication use.

Methods

A total of 46,675 T2D patients with a prescription for antidiabetic agents >6 months from outpatient visits (2003-2018) were linked to Taiwan's National Death Registry to identify all-cause and cardiovascular mortality. The Poisson assumption was used to estimate mortality rates, and the Cox proportional hazard regression model was used to assess the relative hazards of respective mortality in relation to mean LDL-C in patient cohorts by albumin level, age, sex, and antilipid use adjusting for medications, comorbidities, and laboratory results. We also determined the overall, and anti-lipid-specific mortality rates and relative hazards of all-cause and cardiovascular mortality associated with LDL-C-SD using the Poisson assumption and Cox proportional hazard regression model, respectively.

Results

All-cause and cardiovascular mortality rates were the lowest in T2D patients with a mean LDL-C > 90-103.59 mg/dL in the normal albumin group (≥ 3.5 g/dL). Compared to T2D patients with a mean LDL-C > 90-103.59 mg/dL, those with a mean LDL-C ≤ 77 mg/dL had an elevated risk of all-cause mortality in both the normal and lower albumin groups. T2D patients with a mean LDL-C ≤ 90 and > 103.59-119 mg/dL had relatively higher risk of cardiovascular mortality in the normal albumin group, but in the lower albumin group (<3.5 g/dL), any level of mean LDL-C ≤ 119 mg/dL was not significantly associated with cardiovascular mortality. Increased risks of all-cause and cardiovascular mortality were observed in patients with a mean LDL-C ≤ 77 mg/dL in both sexes and in all age groups except in those aged <50 years, a lower mean LDL-C was not associated with cardiovascular mortality. Similarly, patients with an LDL-C-SD <10^th and > 90^th percentiles were associated with significant risks of all-cause and cardiovascular mortality. In statin users, but not fibrate users, lower and higher levels of mean LDL-C and LDL-C-SD were both associated with elevated risks of all-cause and cardiovascular mortality.

Conclusions

The optimal level of LDL-C was found to be >90-103.59 mg/dL in T2D patients. Lower and higher levels of mean LDL-C and LDL-C-SD were associated with all-cause and cardiovascular mortality, revealing U-shaped associations. Further studies are necessary to validate the relationship between optimal LDL-C levels and all-cause and cardiovascular mortality in patients with diabetes.

Mean versus variability of lipid measurements over 6 years and incident cardiovascular events: More than a decade follow-up

Background

Lipid variability (LV) has emerged as a contributor to the incidence of cardiovascular diseases (CVD), even after considering the effect of mean lipid levels. However, these associations have not been examined among people in the Middle East and North Africa (MENA) region. We aimed to investigate the association of 6-year mean lipid levels versus lipid variability with the risk of CVD among an Iranian population.

Methods

A total of 3,700 Iranian adults aged ≥ 30 years, with 3 lipid profile measurements, were followed up for incident CVD until March 2018. Lipid variability was measured as standard deviation (SD), coefficient of variation (CV), average real variability (ARV), and variability independent of mean (VIM). The effects of mean lipid levels and LV on CVD risk were assessed using multivariate Cox proportional hazard models.

Results

During a median 14.5-year follow-up, 349 cases of CVD were recorded. Each 1-SD increase in the mean levels of total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), TC/high-density lipoprotein cholesterol (HDL-C), and non-HDL-C increased the risk of CVD by about 26-29%; for HDL-C, the risk was significantly lower by 12% (all p-values < 0.05); these associations resisted after adjustment for their different LV indices. Considering LV, each 1-SD increment in SD and ARV variability indices for TC and TC/HDL-C increased the risk of CVD by about 10%; however, these associations reached null after further adjustment for their mean values. The effect of TC/HDL-C variability (measured as SD) and mean lipid levels, except for LDL-C, on CVD risk was generally more pronounced in the non-elderly population.

Conclusion

Six-year mean lipid levels were associated with an increased future risk of incident CVD, whereas LV were not. Our findings highlight the importance of achieving normal lipid levels over time, but not necessarily consistent, for averting adverse clinical outcomes.

Comparison of the effects of triglyceride variability and exposure estimate on clinical prognosis in diabetic patients

BACKGROUND

Hypertriglyceridemia is an important feature of dyslipidemia in type 1 and type 2 diabetic patients and associated with the development of atherosclerotic cardiovascular disease. Recently, variability of lipid profile has been suggested as a residual risk factor for cardiovascular disease. This study compared the clinical impact of serum triglyceride variability, and their cumulative exposure estimates on cardiovascular prognosis in diabetic patients.

METHODS

A total of 25,933 diabetic patients who had serum triglyceride levels measured at least 3 times and did not have underlying malignancy, myocardial infarction (MI), and stroke during the initial 3 years (modeling phase) were selected from three tertiary hospitals. They were divided into a high/low group depending on their coefficient of variation (CV) and cumulative exposure estimate (CEE). Incidence of major adverse event (MAE), a composite of all-cause death, MI, and stroke during the following 5 years were compared between groups by multivariable analysis after propensity score matching.

RESULTS

Although there was a slight difference, both the high CV group and the high CEE group had a higher cardiovascular risk profile including male-dominance, smoking, alcohol, dyslipidemia, and chronic kidney disease compared to the low groups. After the propensity score matching, the high CV group showed higher MAE incidence compared to the low CV group (9.1% vs 7.7%, p = 0.01). In contrast, there was no significant difference of MAE incidence between the high CEE group and the low CEE group (8.6% vs 9.1%, p = 0.44). After the multivariable analysis with further adjustment for potential residual confounding factors, the high CV was suggested as an independent risk predictor for MAE (HR 1.19 [95% CI 1.03-1.37]).

CONCLUSION

Visit-to-visit variability of triglyceride rather than their cumulative exposure is more strongly related to the incidence of MAE in diabetic patients.

Incremental value of risk factor variability for cardiovascular risk prediction in individuals with type 2 diabetes: results from UK primary care electronic health records

BACKGROUND

Cardiovascular disease (CVD) risk prediction models for individuals with type 2 diabetes are important tools to guide intensification of interventions for CVD prevention. We aimed to assess the added value of incorporating risk factors variability in CVD risk prediction for people with type 2 diabetes.

METHODS

We used electronic health records (EHRs) data from 83 910 adults with type 2 diabetes but without pre-existing CVD from the UK Clinical Practice Research Datalink for 2004-2017. Using a landmark-modelling approach, we developed and validated sex-specific Cox models, incorporating conventional predictors and trajectories plus variability of systolic blood pressure (SBP), total and high-density lipoprotein (HDL) cholesterol, and glycated haemoglobin (HbA1c). Such models were compared against simpler models using single last observed values or means.

RESULTS

The standard deviations (SDs) of SBP, HDL cholesterol and HbA1c were associated with higher CVD risk (P < 0.05). Models incorporating trajectories and variability of continuous predictors demonstrated improvement in risk discrimination (C-index = 0.659, 95% CI: 0.654-0.663) as compared with using last observed values (C-index = 0.651, 95% CI: 0.646-0.656) or means (C-index = 0.650, 95% CI: 0.645-0.655). Inclusion of SDs of SBP yielded the greatest improvement in discrimination (C-index increase = 0.005, 95% CI: 0.004-0.007) in comparison to incorporating SDs of total cholesterol (C-index increase = 0.002, 95% CI: 0.000-0.003), HbA1c (C-index increase = 0.002, 95% CI: 0.000-0.003) or HDL cholesterol (C-index increase= 0.003, 95% CI: 0.002-0.005).

CONCLUSION

Incorporating variability of predictors from EHRs provides a modest improvement in CVD risk discrimination for individuals with type 2 diabetes. Given that repeat measures are readily available in EHRs especially for regularly monitored patients with diabetes, this improvement could easily be achieved.

Novel Strategies for Assessing Associations Between Selenium Biomarkers and Cardiometabolic Risk Factors: Concentration, Visit-to-Visit Variability, or Individual Mean? Evidence From a Repeated-Measures Study of Older Adults With High Selenium

Background and Aims

Previous studies have focused only on the cardiometabolic effects of selenium concentrations. We explored whether selenium levels and their visit-to-visit variability (VVV) and individual mean (IM) are independently associated with cardiometabolic risk factors.

Methods

A three-wave repeated-measures study of older adults with high selenium (n = 201) was conducted in Beijing from 2016 to 2018. Whole blood selenium and urinary selenium concentrations were measured. VVV and IM were used to profile the homeostasis of the selenium biomarkers. Four indicators, namely standard deviation, coefficient of variation, average real variability, and variability independent of the mean, were employed to characterize VVV. We considered 13 cardiometabolic factors: four lipid profile indicators, three blood pressure indices, glucose, uric acid, waistline, hipline, waist-hip ratio, and sex-specific metabolic syndrome score. Linear mixed-effects regression models with random intercepts for the participants were employed to explore the associations of the selenium concentrations, VVV, and IM with the cardiometabolic factors.

Results

The geometric mean whole blood and urinary selenium levels were 134.30 and 18.00 μg/L, respectively. Selenium concentrations were significantly associated with numerous cardiometabolic factors. Specifically, whole blood selenium was positively associated with total cholesterol [0.22, 95% confidence interval (CI): 0.12, 0.33], low-density lipoprotein cholesterol (LDL-C; 0.28, 95% CI: 0.13, 0.42), glucose (0.22, 95% CI: 0.10, 0.34), and uric acid (0.16, 95% CI: 0.04, 0.28). After adjustment for VVV, the IM of whole blood selenium was positively correlated with total cholesterol (0.002, 95% CI: 0.001, 0.004), triglycerides (0.007, 95% CI: 0.004, 0.011), and LDL-C (0.002, 95% CI: 0.000, 0.004). However, we did not observe any robust associations between the VVV of the selenium biomarkers and cardiometabolic risk factors after adjustment for IM.

Conclusion

Our findings suggest that selenium concentrations and their IMs are significantly associated with cardiometabolic risk factors among older adults with high selenium. Longer repeated-measures studies among the general population are required to validate our findings and elucidate the relevant underlying mechanisms.

Lipid Variability and Risk of Cardiovascular Diseases and All-Cause Mortality: A Systematic Review and Meta-Analysis of Cohort Studies

No consensus has yet been reached on the associations of lipid variability (LV) with cardiovascular diseases (CVDs) and all-cause mortality. We aimed to quantify the associations of different types and metrics of LV with CVDs and all-cause mortality. PubMed, Medline, and Embase databases were searched for eligible cohort studies published until 14 December 2021. Lipids included total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglycerides (TG). Metrics of variability included standard deviation (SD), coefficient of variation (CV), and variation independent of the mean (VIM). The primary outcomes were CVDs and all-cause mortality. Random-effects meta-analysis was used to generate a summary of the relative risks (SRRs). Sources of heterogeneity were explored by subgroup analysis and meta-regression. A total of 11 articles based on seven cohorts were included. Participants in the top quartile of TC variability had an increased risk of CVDs (vs. bottom quartile: TC-CV: SRR 1.29, 95% CI 1.15-1.45; TC-SD: 1.28, 1.15-1.43; TC-VIM: 1.26, 1.13-1.41, respectively) and all-cause mortality (vs. bottom quartile: TC-CV: 1.28, 1.15-1.42; TC-SD: 1.32, 1.22-1.44; TC-VIM: 1.32, 1.25-1.40, respectively). Participants in the top quartile of HDL-C variability had an increased risk of CVDs (vs. bottom quartile: HDL-C-CV: 1.11, 1.07-1.15; HDL-C-SD: 1.18, 1.02-1.38; HDL-C-VIM: 1.18, 1.09-1.27, respectively) and all-cause mortality (vs. bottom quartile: HDL-C-CV: 1.29, 1.27-1.31; HDL-C-SD: 1.24, 1.09-1.41; HDL-C-VIM: 1.25, 1.22-1.27, respectively). LDL-C variability was also associated with an increased risk of CVDs (for top vs. bottom quartile; LDL-C-SD: 1.09, 1.02-1.17; LDL-C-VIM: 1.16, 1.02-1.32, respectively) and all-cause mortality (for top vs. bottom quartile; LDL-C-CV: 1.19, 1.04-1.36; LDL-C-SD: 1.17, 1.09-1.26, respectively). The relationships of TG variability with the risk of CVDs and all-cause mortality were inconclusive across different metrics. The effects of SRR became stronger when analyses were restricted to studies that adjusted for lipid-lowering medication and unadjusted for mean lipid levels. These findings indicate that the measurement and surveillance of lipid variability might have important clinical implications for risk assessment of CVDs and all-cause mortality.

Triglyceride-glucose index variability and incident cardiovascular disease: a prospective cohort study

Background

Recent studies have suggested that triglyceride-glucose (TyG) index is an independent predictor of cardiovascular disease (CVD). However, the impact of long-term visit-to-visit variability in TyG index on the risk of CVD is not known. We aimed to investigate the longitudinal association between baseline and mean TyG index as well as TyG index variability and incident CVD in a Chinese population.

Methods

We included 49,579 participants without previous history of CVD in the Kailuan study who underwent three health examinations (2006, 2008, and 2010) and were followed up for clinical events until 2019. TyG index was calculated as Ln [fasting triglyceride (mg/dL) × fasting glucose (mg/dL)/2]. We measured TyG index variability as the SD of the residuals obtained from a linear regression on the three TyG index measurements for each individual. Multivariate-adjusted Cox models were used to estimate the adjusted hazard ratio (aHR) and 95% confidence interval (CI) with incident CVD.

Results

During a median follow-up time of 9.0 years, 2404 developed CVD. The highest tertile (T3) of baseline and mean TyG index were each associated with higher CVD incidence as compared with the lowest tertile (T1): aHR, 1.25; 95% CI 1.11–1.42; and aHR 1.40; 95% CI 1.24–1.58, respectively. Tertile 3 of TyG index variability was associated with increased CVD incidence compared to T1 group (aHR, 1.12; 95% CI 1.01–1.24). Similar findings were observed in a series of sensitivity analyses.

Conclusion

Higher TyG index level and greater TyGindex variability were each independently associated with a higher incidence of CVD.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12933-022-01541-5.

Elevation of Hemoglobin A1c Increases the Atherosclerotic Plaque Vulnerability and the Visit-to-Visit Variability of Lipid Profiles in Patients Who Underwent Elective Percutaneous Coronary Intervention

Background

Increased plaque vulnerability and higher lipid variability are causes of adverse cardiovascular events. Despite a close association between glucose and lipid metabolisms, the influence of elevated glycated hemoglobin A1c (HbA1c) on plaque vulnerability and lipid variability remains unclear.

Methods

Among subjects undergoing percutaneous coronary intervention (PCI) from 2009 through 2019, 366 patients received intravascular optical coherence tomography (OCT) assessment and 4,445 patients underwent the scheduled follow-ups within 1 year after PCI. Vulnerability features of culprit vessels were analyzed by OCT examination, including the assessment of lipid, macrophage, calcium, and minimal fibrous cap thickness (FCT). Visit-to-visit lipid variability was determined by different definitions including standard deviation (SD), coefficient of variation (CV), and variability independent of the mean (VIM). Multivariable linear regression analysis was used to verify the influence of HbA1c on plaque vulnerability features and lipid variability. Exploratory analyses were also performed in non-diabetic patients.

Results

Among enrolled subjects, the pre-procedure HbA1c was 5.90 ± 1.31%, and the average follow-up HbA1c was 5.98 ± 1.16%. By OCT assessment, multivariable linear regression analyses demonstrated that patients with elevated HbA1c had a thinner minimal FCT (β = −6.985, P = 0.048), greater lipid index (LI) (β = 226.299, P = 0.005), and higher macrophage index (β = 54.526, P = 0.045). Even in non-diabetic patients, elevated HbA1c also linearly decreased minimal FCT (β = −14.011, P = 0.036), increased LI (β = 290.048, P = 0.041) and macrophage index (β = 120.029, P = 0.048). Subsequently, scheduled follow-ups were performed during 1-year following PCI. Multivariable linear regression analyses proved that elevated average follow-up HbA1c levels increased the VIM of lipid profiles, including low-density lipoprotein cholesterol (β = 2.594, P < 0.001), high-density lipoprotein cholesterol (β = 0.461, P = 0.044), non-high-density lipoprotein cholesterol (β = 1.473, P < 0.001), total cholesterol (β = 0.947, P < 0.001), and triglyceride (β = 4.217, P < 0.001). The result was consistent in non-diabetic patients and was verified when SD and CV were used to estimate variability.

Conclusion

In patients undergoing elective PCI, elevated HbA1c increases the atherosclerotic plaque vulnerability and the visit-to-visit variability of lipid profiles, which is consistent in non-diabetic patients.

Association between Variability of Metabolic Risk Factors and Cardiometabolic Outcomes

Despite strenuous efforts to reduce cardiovascular disease (CVD) risk by improving cardiometabolic risk factors, such as glucose and cholesterol levels, and blood pressure, there is still residual risk even in patients reaching treatment targets. Recently, researchers have begun to focus on the variability of metabolic variables to remove residual risks. Several clinical trials and cohort studies have reported a relationship between the variability of metabolic parameters and CVDs. Herein, we review the literature regarding the effect of metabolic factor variability and CVD risk, and describe possible mechanisms and potential treatment perspectives for reducing cardiometabolic risk factor variability.

The Effect of Berberine on Metabolic Profiles in Type 2 Diabetic Patients: A Systematic Review and Meta-Analysis of Randomized Controlled Trials

Objective

Rhizoma Coptidis is an herb that has been frequently used in many traditional formulas for the treatment of diabetic mellitus (DM) over thousands of years. Berberine, the main active component of Rhizoma Coptidis, has been demonstrated to have the potential effect of hypoglycemia. To determine the potential advantages of berberine for diabetic care, we conducted this systematic review and meta-analysis to examine the efficacy and safety of berberine in the treatment of patients with type 2 DM.

Methods

Eight databases including PubMed, Embase, Web of Science, the Cochrane library, China National Knowledge Infrastructure (CNKI), Chinese Biomedical Database (SinoMed), Wanfang Database, and Chinese VIP Information was searched for randomized controlled trials (RCTs) reporting clinical data regarding the use of berberine for the treatment of DM. Publication qualities were also considered to augment the credibility of the evidence. Glycemic metabolisms were the main factors studied, including glycosylated hemoglobin (HbA1c), fasting plasm glucose (FPG), and 2-hour postprandial blood glucose (2hPG). Insulin resistance was estimated by fasting blood insulin (FINS), homeostasis model assessment-insulin resistance (HOMA-IR), and body mass index (BMI). Lipid profiles were also assessed, including triglyceride (TG), total cholesterol (TC), low-density lipoprotein (LDL), and high-density lipoprotein (HDL), along with inflammation factors such as C-reactive protein (CRP), interleukin-6 (IL-6), and tumor necrosis factor-α (TNF-α). Serum creatinine (Scr), blood urea nitrogen (BUN), and adverse events were applied to evaluate the safety of berberine.

Results

Forty-six trials were assessed. Analysis of berberine applied alone or with standard diabetic therapies versus the control group revealed significant reductions in HbA1c (MD = −0.73; 95% CI (−0.97, −0.51)), FPG (MD = −0.86, 95% CI (−1.10, −0.62)), and 2hPG (MD = −1.26, 95% CI (−1.64, −0.89)). Improved insulin resistance was assessed by lowering FINS (MD = −2.05, 95% CI (−2.62, −1.48)), HOMA-IR (MD = −0.71, 95% CI (−1.03, −0.39)), and BMI (MD = −1.07, 95% CI (−1.76, −0.37)). Lipid metabolisms were also ameliorated via the reduction of TG (MD = −0.5, 95% CI (−0.61, −0.39)), TC (MD = 0.64, 95% CI (−0.78, −0.49)), and LDL (MD = 0.86, 95% CI (−1.06, −0.65)) and the upregulation of HDL (MD = 0.17, 95% CI (0.09, 0.25)). Additionally, berberine improved the inflammation factor.

Conclusion

There is strong evidence supporting the clinical efficacy and safety of berberine in the treatment of DM, especially as an adjunctive therapy. In the future, this may be used to guide targeted clinical use of berberine and the development of medications seeking to treat patients with T2DM and dyslipidemia.

Association between visit-to-visit variability of glycemic indices and lipid profile and the incidence of coronary heart disease in adults with type 2 diabetes

Coronary heart disease (CHD) is one of the major causes of mortality and morbidity in patients with type 2 diabetes mellitus. In this study, we aimed to assess the association between visit-to-visit variability of fasting blood sugar (FBS), HbA1c, blood sugar 2 h post-prandial (BS2hpp), lipid indices, creatinine, systolic and diastolic blood pressure (SBP, DBP) and incident CHD in patients with type 2 diabetes during a median follow-up of ten years. The current case-cohort study consisted of 1500 individuals with type 2 diabetes, followed up for the occurrence of CHD from 2002 to 2019. The patients had at least four annual follow-ups during which glycemic and lipid profile were measured. Co-efficient of variance (CV) for each parameter was calculated by 10-21 measurements. Cox regression analysis was performed to assess the association between CV of glycemic indices, lipid profile, blood pressure, creatinine, weight and incident CHD during the follow-up period. Hazard ratios (HR) were adjusted for the confounding variables. Glycemic indices variability (i.e., CV-HbA1c, CV-FBS, and CV-BS2hpp), were significantly higher in the group with incident CHD (P=0.034, P=0.042, and P=0.044, respectively). Hazard ratios were 1.42 (95 % CI=1.13-2.09) for CV-HbA1c, 1.37 (95 % CI=1.02-2.10) for CV-FBS, and 1.16 (95 % CI=1.01-1.63) for CV-BS2hpp (P=0.012, P=0.046, P=0.038, respectively). Creatinine was significantly higher in the group with incident CHD (P=0.036) and it was significantly associated with higher incidence of CHD (HR=1.14, 95 % CI=1.02-2.17, P=0.048). Visit to visit variability of glycemic indices of the patients with type 2 diabetes is associated with incident CHD independent of their baseline and mean values.

Effect of blood lipid variability on mortality in patients with type 2 diabetes: a large single-center cohort study

BACKGROUND

Dyslipidemia is a major cardiovascular risk factor and common in diabetes patients. Most guidelines focus on optimal lipid levels, while variation of lipid profiles is far less discussed. This study aims to investigate the association of visit-to-visit variability in blood lipids with all-cause, cardiovascular, and non-cardiovascular mortality in patients with type 2 diabetes.

METHODS

We identified 10,583 type 2 diabetes patients aged ≥ 30 years with follow-up ≥ 3 years and who participated in the Diabetes Care Management Program at a medical center in Taiwan. Variability in lipid profiles within 3 years after entry was calculated using coefficient of variation. Cox proportional hazard models were used to evaluate lipid variability in relation to subsequent mortality.

RESULTS

Over a mean follow-up of 6.4 years, 1838 all-cause deaths (809 cardiovascular deaths) were observed. For each 10% increase in variability in high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and total cholesterol, the hazard ratios (95% confidence intervals) of all-cause mortality were 1.30 (1.22-1.37), 1.05 (1.01-1.09), and 1.10 (1.03-1.16), respectively; those of cardiovascular mortality were 1.27 (1.16-1.39), 1.08 (1.02-1.15), and 1.16 (1.07-1.27), respectively. Each 10% increase in high-density lipoprotein cholesterol variability conveyed 31% greater risk of non-cardiovascular mortality. High variability in total cholesterol and low-density lipoprotein cholesterol increased all-cause mortality in subgroups of nonsmoking, regular exercising, non-dyslipidemia, and more severe status of diabetes at baseline.

CONCLUSIONS

Blood lipid variability except for triglyceride variability was associated with all-cause and cardiovascular mortality in patients with type 2 diabetes.

Glycemic and lipid variability for predicting complications and mortality in diabetes mellitus using machine learning

INTRODUCTION

Recent studies have reported that HbA1c and lipid variability is useful for risk stratification in diabetes mellitus. The present study evaluated the predictive value of the baseline, subsequent mean of at least three measurements and variability of HbA1c and lipids for adverse outcomes.

METHODS

This retrospective cohort study consists of type 1 and type 2 diabetic patients who were prescribed insulin at outpatient clinics of Hong Kong public hospitals, from 1st January to 31st December 2009. Standard deviation (SD) and coefficient of variation were used to measure the variability of HbA1c, total cholesterol, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C) and triglyceride. The primary outcome is all-cause mortality. Secondary outcomes were diabetes-related complications.

RESULT

The study consists of 25,186 patients (mean age = 63.0, interquartile range [IQR] of age = 15.1 years, male = 50%). HbA1c and lipid value and variability were significant predictors of all-cause mortality. Higher HbA1c and lipid variability measures were associated with increased risks of neurological, ophthalmological and renal complications, as well as incident dementia, osteoporosis, peripheral vascular disease, ischemic heart disease, atrial fibrillation and heart failure (p <  0.05). Significant association was found between hypoglycemic frequency (p <  0.0001), HbA1c (p <  0.0001) and lipid variability against baseline neutrophil-lymphocyte ratio (NLR).

CONCLUSION

Raised variability in HbA1c and lipid parameters are associated with an elevated risk in both diabetic complications and all-cause mortality. The association between hypoglycemic frequency, baseline NLR, and both HbA1c and lipid variability implicate a role for inflammation in mediating adverse outcomes in diabetes, but this should be explored further in future studies.

Greater variability in lipid measurements associated with cardiovascular disease and mortality: A 10-year diabetes cohort study

AIM

To examine the associations between variability in lipids and the risk of cardiovascular disease (CVD) and mortality in patients with type 2 diabetes based on low-density lipoprotein-cholesterol (LDL-C), the total cholesterol (TC) to high-density lipoprotein-cholesterol (HDL-C) ratio and triglycerides (TG).

MATERIALS AND METHODS

A retrospective cohort study included 125 047 primary care patients with type 2 diabetes aged 45-84 years without CVD during 2008-2012. The variability of LDL-C, TC to HDL-C and TG was determined using the standard deviation of variables in a mixed effects model to minimize regression dilution bias. The associations between variability in lipids and CVD and mortality risk were assessed by Cox regression. Subgroup analyses based on patients' baseline characteristics were also conducted.

RESULTS

A total of 19 913 CVD events and 15 329 mortalities were recorded after a median follow-up period of 77.5 months (0.8 million person-years), suggesting a positive linear relationship between variability in lipids and the risk of CVD and mortality. Each unit increase in the variability of LDL-C (mmol/L), the TC to HDL-C ratio and TG (mmol/L) was associated with a 27% (HR: 1.27 [95% CI: 1.20-1.34]), 31% (HR:1.31 [95% CI: 1.25-1.38]) and 9% (HR: 1.09 [95% CI: 1.04-1.15]) increase in the risk of composite endpoint of CVD and mortality, respectively. Age-specific effects were also found when comparing LDL-C variability, with patients aged 45-54 years (HR: 1.70 [95% CI: 1.42-2.02]) exhibiting a 53% increased risk for the composite endpoints than those aged 75-84 years (HR: 1.11 [95% CI: 1.01-1.23]). Similar age effects were observed for both the TC to HDL-C ratio and TG variability. Significant associations remained consistent among most of the subgroups.

CONCLUSIONS

Variability in respective lipids are significant factors in predicting CVD and mortality in primary care patients with type 2 diabetes, with the strongest effects related to LDL-C and the TC to HDL-C ratio and most significant in the younger age group of patients aged 45-54 years. Further study is warranted to confirm these findings.

Is Neck Circumference As Reliable As Waist Circumference for Determining Metabolic Syndrome?

Background: Metabolic syndrome (MS) comprises a cluster of risk factors for the development of cardiovascular diseases, which are among the leading causes of morbidity and mortality worldwide. Many studies have shown that neck circumference (NC) has validity in the measure of MS since it correlates positively with the traditional components. For these reasons, this study aimed at comparing waist circumference (WC) and NC for identifying MS parameters in patients treated at a cardiology unit. Methods: This study included 309 patients assisted in a Cardiology Unit. Biochemical and anthropometric parameters were evaluated. Correlations between neck and WC with anthropometric, biochemical, and atherogenic indices were evaluated. The diagnostic ability of neck and WC was assessed by using the receiver operating characteristics curve. Results: The patients had a mean age of 57.2 years, and 56% were men. The diagnosis of MS was present in 48% of men and 39% of women. Neck and WC showed a positive correlation with each other, and both showed positive correlations with the criteria for MS. Moreover, NC showed a positive correlation with body mass index (BMI), insulin, homeostatic model assessment (HOMA)-β, and C-reactive protein. WC showed a positive correlation with BMI, HOMA of insulin resistance (HOMA-IR), and Castelli Index I. Both neck and WC showed the ability to identify the presence of the MS. Conclusion: Both neck and WC showed a significant correlation with several of the metabolic parameters, including some used as criteria for the diagnosis of MS. In addition, both measures demonstrated a good ability to predict MS, making these measures promising for screening patients with this syndrome.