Visit-to-visit variability of lipid measurements as predictors of cardiovascular events

The association of fasting triglyceride variability with renal dysfunction and proteinuria in medical checkup participants

BACKGROUND

The association between the variability of triglyceride (TG) and chronic kidney disease (CKD) progression remains unclear. We examined whether intraindividual variability in fasting TG was associated with the exacerbation of CKD.

METHODS

We conducted a retrospective and observational study. 18,339 participants, who went through medical checkups and had checked their estimated glomerular filtration rate (eGFR) and semi-quantitative proteinuria by urine dipstick every year since 2017 for 4 years were registered. Variability in fasting TG was determined using the standard deviation (SD), and maximum minus minimum difference (MMD) between 2017 and 2021. The primary end point for the analysis of eGFR decline was eGFR < 60 mL/min/1.73 m2. The secondary end point for the analysis of proteinuria was the incidence of proteinuria ≥ ( ±) by urine dipstick.

RESULTS

The renal survival was lower in the higher-SD, and higher-MMD groups than in the lower-SD, and lower-MMD groups, respectively (log-rank test p < 0.001, and < 0.001, respectively). Lower SD and lower MMD were significantly associated with renal survival in the adjusted model (hazard ratio (HR), 1.12; 95% confidence intervals (CI), 1.04-1.21, and HR, 1.13; 95% CI 1.05-1.23, respectively). The non-incidence of proteinuria was lower in the higher-SD, and higher-MMD groups than in the lower-SD, and lower-MMD groups, respectively (log-rank test p < 0.001 and < 0.001, respectively).

CONCLUSION

Fasting TG variability was associated with CKD progression in participants who went through medical checkups.

Association between visit-to-visit lipid variability and risk of ischemic heart disease: a cohort study in China

AIMS

To explore the associations between visit-to-visit lipid variability and risk of ischemic heart disease (IHD) in a population-based cohort in China.

METHODS

We evaluated lipid variability in 30,217 individuals from the Yinzhou Health Information System who had ≥3 recorded lipid measurements during 2010-2014. We used various indicators including standard deviation (SD), coefficient of variation (CV), variability independent of the mean (VIM), and average real variability (ARV) to quantify the variability in triglycerides, total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C). We used Cox proportional hazards models to estimate hazard ratios (HRs) and 95% confidence intervals (CIs).

RESULTS

Overall, a total of 1305 participants with IHD were identified during the follow-up of 194,421 person-years. Subjects in Q4 had a 21% elevated risk of IHD (HR = 1.21, 95% CI: 1.03-1.41) for LDL-C variability (CV) compared with the reference (Q1). The HRs for Q4 vs Q1 were 1.21 (95% CI: 1.04-1.42) for HDL-C variability, and 1.28 (95% CI: 1.10-1.50) for TC variability. However, no association was observed between triglycerides variability and risk of IHD.

CONCLUSIONS

Higher variability in LDL-C, HDL-C, and TC levels was associated with an elevated risk of IHD, suggesting that lipid variability could be considered as an independent risk factor of IHD.

The association between variability of risk factors and complications in type 2 diabetes mellitus: a retrospective study

The variability in diabetes risk factors, such as uric acid and lipids, may influence the development of complications. This study aimed to investigate the influence of such variability on the occurrence of diabetic complications. A retrospective analysis of electronic medical records was conducted with type 2 diabetic patients who received treatment at a tertiary care hospital in Chengdu, Sichuan Province, between 2013 and 2022. The risk factor variability is presented as the standard deviation (SD). The associations between the variability and complications were examined using a binary logistic regression model. The study included 369 patients with type 2 diabetes. The findings revealed that outpatient special disease management served as a protective factor against the development of complications [OR = 0.53, 95% confidence interval (CI) (0.29-0.10)], particularly for the prevention of diabetic peripheral neuropathy [OR = 0.51, 95% CI (0.30-0.86)]. Variability in total cholesterol (TC-SD) was found to be a risk factor for the development of complications [OR = 2.42, 95% CI (1.18-4.97)] and acted as a risk factor for diabetic peripheral vasculopathy [OR = 2.50, 95% CI (1.25-5.02)]. TC-SD is a risk factor for the occurrence of diabetic peripheral neuropathy and diabetic peripheral vasculopathy, whereas outpatient special disease management functions as a protective factor against complications and diabetic peripheral neuropathy. Thus, in addition to glycaemic control, the regulation of lipid levels should be emphasized, particularly among patients without outpatient special disease management, to delay the onset of complications.

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.

Variability in Plasma Lipids Between Intensive Statin Therapy and Conventional-Dose Statins Combined with Ezetimibe Therapy in Patients with Coronary Atherosclerosis Disease

Dyslipidemia has been widely recognized as a significant risk factor for coronary atherosclerosis disease (CAD). In fact, lipid variability has emerged as a more reliable predictor of cardiovascular events. In this study, we aimed to examine the variability in plasma lipids under two different lipid-lowering regimens (intensive statin therapy versus the combination of conventional-dose statins with ezetimibe). In total, we have retrospectively examined 1275 patients with CAD from January 2009 to April 2019 and divided them into two groups: intensive statin group and conventional-dose statins combined with ezetimibe group. All patients were followed up for at least 1 year. Lipid variability was verified by standard deviation (SD), coefficient of variation (CV), and variability independent of mean (VIM) triple methods. Multiple linear regression and subgroup analyses were performed. In the overall participants, the mean age was 62.3 ± 10.4 years old, and 72.8% were male. Multivariate linear regression analysis indicated that the intensive statin group had lower variability in terms of total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), and non-high-density lipoprotein cholesterol (non-HDL-C) in all SD, CV, and VIM triple methods than statins combined with ezetimibe group (P for all <0.05). Similar results were established in the subgroup analyses based on atorvastatin or rosuvastatin, diabetes mellitus or not, and hypertension or not (P for all < 0.05). Thus, we can conclude that intensive statin therapy could contribute in lowering lipid variability than conventional-dose statins combined with ezetimibe therapy among patients with CAD.

Association Between Fluctuations in Blood Lipid Levels Over Time With Incident Alzheimer Disease and Alzheimer Disease-Related Dementias

BACKGROUND AND OBJECTIVES

Prevention strategies for Alzheimer disease and Alzheimer disease-related dementias (AD/ADRDs) are urgently needed. Lipid variability, or fluctuations in blood lipid levels at different points in time, has not been examined extensively and may contribute to the risk of AD/ADRD. Lipid panels are a part of routine screening in clinical practice and routinely available in electronic health records (EHR). Thus, in a large geographically defined population-based cohort, we investigated the variation of multiple lipid types and their association to the development of AD/ADRD.

METHODS

All residents living in Olmsted County, Minnesota on the index date January 1, 2006, aged 60 years or older without an AD/ADRD diagnosis were identified. Persons with ≥3 lipid measurements including total cholesterol, triglycerides, low-density lipoprotein cholesterol (LDL-C), or high-density lipoprotein cholesterol (HDL-C) in the 5 years before index date were included. Lipid variation was defined as any change in individual's lipid levels over time regardless of direction and was measured using variability independent of the mean (VIM). Associations between lipid variation quintiles and incident AD/ADRD were assessed using Cox proportional hazards regression. Participants were followed through 2018 for incident AD/ADRD.

RESULTS

The final analysis included 11,571 participants (mean age 71 years; 54% female). Median follow-up was 12.9 years with 2,473 incident AD/ADRD cases. After adjustment for confounding variables including sex, race, baseline lipid measurements, education, BMI, and lipid-lowering treatment, participants in the highest quintile of total cholesterol variability had a 19% increased risk of incident AD/ADRD, and those in highest quintile of triglycerides, variability had a 23% increased risk.

DISCUSSION

In a large EHR derived cohort, those in the highest quintile of variability for total cholesterol and triglyceride levels had an increased risk of incident AD/ADRD. Further studies to identify the mechanisms behind this association are needed.

Separate and Joint Associations of Remnant Cholesterol Accumulation and Variability With Carotid Atherosclerosis: A Prospective Cohort Study

Background We aimed to examine separate and joint associations of remnant cholesterol (RC) accumulation and variability with the risk of carotid atherosclerosis (CAS) in the general population. Methods and Results A total of 6213 participants who underwent 3 sequential health examinations during 2010 to 2015 were enrolled and were followed up until December 31, 2021. Cumulative RC (cumRC) and RC variability among the 3 visits were the exposure of interest in our study. Adjusted Cox models were performed to calculate the hazard ratio (HR) and 95% CI. C-statistics, integrated discrimination improvement, and the net reclassification index were used to estimate the incremental predictive ability. During a median follow-up of 4.00 years, 2613 participants developed CAS. Higher cumRC (HR, 1.33 [95% CI, 1.17-1.52]) and greater RC variability (HR, 1.22 [95% CI, 1.08-1.39]) were significantly associated with elevated risk of CAS, independent of traditional cardiovascular risk factors and low-density lipoprotein cholesterol. Participants were divided into 4 groups according to the median of cumRC and RC variability to assess their joint associations. Compared with "low cumRC and low variability," "high cumRC and high variability" had the highest risk of CAS, followed by "high cumRC and low variability" and "low cumRC and high variability." Finally, joint assessment of RC accumulation and variability had the significantly highest incremental effect on the predictive value of CAS versus single-time-point measures of RC. Conclusions Excessive cumRC levels and greater RC variability were each independently associated with higher incidence of CAS, and their coexistence could further yield significantly higher risks.

Variability in Lipid Levels and Risk for Cardiovascular Disease: An Electronic Health Record-Based Population Cohort Study

Background Larger within-patient variability of lipid levels has been associated with increased risk of cardiovascular disease (CVD); however, measures of lipid variability require ≥3 measurements and are not currently used clinically. We investigated the feasibility of calculating lipid variability within a large electronic health record-based population cohort and assessed associations with incident CVD. Methods and Results We identified all individuals ≥40 years of age who resided in Olmsted County, MN, on January 1, 2006 (index date), without prior CVD, defined as myocardial infarction, coronary artery bypass graft surgery, percutaneous coronary intervention, or CVD death. Patients with ≥3 measurements of total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, or triglycerides during the 5 years before the index date were retained. Lipid variability was calculated using variability independent of the mean. Patients were followed through December 31, 2020 for incident CVD. We identified 19 652 individuals (mean age 61 years; 55% female), who were CVD-free and had variability independent of the mean calculated for at least 1 lipid type. After adjustment, those with highest total cholesterol variability had a 20% increased risk of CVD (Q5 versus Q1 hazard ratio, 1.20 [95% CI, 1.06-1.37]). Results were similar for low-density lipoprotein cholesterol and high-density lipoprotein cholesterol. Conclusions In a large electronic health record-based population cohort, high variability in total cholesterol, high-density lipoprotein cholesterol, and low-density lipoprotein cholesterol was associated with an increased risk of CVD, independent of traditional risk factors, suggesting it may be a possible risk marker and target for intervention. Lipid variability can be calculated in the electronic health record environment, but more research is needed to determine its clinical utility.

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.

Risk for Behçet's disease gauged via high-density lipoprotein cholesterol: a nationwide population-based study in Korea

Behçet’s disease (BD) is a chronic inflammatory disease. Low levels of plasma high-density lipoprotein cholesterol (HDL-C) are associated with Crohn’s disease, another chronic inflammatory disease. However, the effects of low HDL-C levels on BD are unclear. We investigated the effects of HDL-C levels, and variability therein, on the risk for BD. We used the Korean National Health Insurance System database to identify 5,587,754 adults without a history of BD who underwent ≥ 3 medical examinations between 2010 and 2013. Mean HDL-C levels at each visit were used to calculate variability independent of the mean (VIM) and the coefficient of variation (CV). There were 676 new cases of BD (0.012%). The risk for BD was increased in participants with highly variable and low mean HDL-C levels. In a multivariate-adjusted model, the hazard ratios (95% confidence intervals) for BD incidence were 1.335 (1.058–1.684) in a high mean/high VIM group, 1.527 (1.211–1.925) in a low mean/low VIM group, and 2.096 (1.67–2.63) in a low mean/high VIM group compared to a high mean/low VIM group. Low mean HDL-C levels, and high variability therein, are independent risk factors for BD.

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.

Lipid variability and risk of microvascular complications in Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial: A post hoc analysis

BACKGROUND

Greater lipid variability may cause adverse health events among diabetic patients. We aimed to examine the effect of lipid variability on the risk of diabetic microvascular outcomes among type 2 diabetes mellitus patients.

METHODS

We assessed the association between visit-to-visit variability (measured by variability independent of mean) in high-density lipoprotein (HDL) cholesterol, low-density lipoprotein-cholesterol (LDL), triglyceride, and remnant cholesterol (RC) measurements among participants involved in the Action to Control Cardiovascular Risk in Diabetes (ACCORD) study and the risk of incident microvascular outcomes, including nephropathy, neuropathy, and retinopathy. Cox proportional hazards models were used to estimate the hazard ratios (HRs) and 95% confidence intervals (CIs), adjusted for potential confounders.

RESULTS

There were 2400, 2470, and 2468 cases of nephropathy, neuropathy, and retinopathy during a follow-up period of 22 600, 21 542, and 26 701 person-years, respectively. Higher levels of HDL, triglyceride, and RC variability were associated with an increased risk of incident nephropathy and neuropathy. Compared with the lowest quartile, the fully adjusted HRs (95% CI) for the highest quartile of HDL, triglyceride, and RC variability for nephropathy risk were 1.57 (1.22, 2.01), 1.50 (1.18, 1.92), and 1.40 (1.09, 1.80), respectively; and for neuropathy, the corresponding risks were 1.36 (1.05, 1.75), 1.47 (1.14, 1.91), and 1.35 (1.04, 1.74), respectively. Null association was observed between LDL variability and all microvascular complications. Additionally, all associations of variability in the other lipids with retinopathy risk were null.

CONCLUSION

Among individuals with type 2 diabetes mellitus, HDL, triglyceride, and RC variability were associated with increased risks of nephropathy and neuropathy but not retinopathy.

TRIAL REGISTRATION

ClinicalTrials.gov., no. NCT00000620.

Remnant Cholesterol Variability and Incident Ischemic Stroke in the General Population

BACKGROUND

Studies have demonstrated that remnant cholesterol is correlated with the risk of ischemic stroke. However, it is unknown whether visit-to-visit variability in remnant cholesterol concentration affects ischemic stroke. We sought to examine the role of remnant cholesterol variability in the subsequent development of ischemic stroke in the general population.

METHODS

We performed a post hoc analysis including eligible participants from the Kailuan Study cohort who underwent 3 health examinations and were free of atrial fibrillation, myocardial infarction, stroke, cancer, or known lipid-medication use from 2006 to 2010. Participants were followed up until the end of 2017. Variability was quantified as variability independent of the mean, average real variability, and SD. Multivariate analysis was performed using the Fine and Gray competing risk model to estimate subhazard ratios assuming death as a competing risk.

RESULTS

The final study cohort comprised 38 556 participants. After a median follow-up of 7.0 years, 1058 individuals were newly diagnosed with ischemic stroke. After adjusting for age (time scale), sex, smoking status, alcohol consumption, physical activity, hypertension, diabetes, family history of cardiovascular disease, body mass index, estimated glomerular filtration rate, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, triglycerides, and mean remnant cholesterol, the highest quartile (quartile 4) of variability independent of the mean of remnant cholesterol was associated with an increased ischemic stroke risk compared with the lowest quartile (quartile 1), (subhazard ratio, 1.27 [95% CI, 1.06-1.53]). For each 1-SD increase in variability independent of the mean of remnant cholesterol, the risk increased by 9% (subhazard ratio, 1.09 [95% CI, 1.03-1.16]). The association was also significant using average real variability and SD as indices of variability.

CONCLUSIONS

Greater remnant cholesterol variability was associated with a higher risk of ischemic stroke in the general population.

The Effect of Total Cholesterol Variability on Clinical Outcomes After Percutaneous Coronary Intervention

AIM

Exploring the risk factors of prognosis in patients undergoing percutaneous coronary intervention (PCI) is of great importance. Our aim of the study is to investigate the association between variability in total cholesterol (TC) level and major adverse cardiovascular and cerebrovascular events (MACCE) in patients after PCI.

METHODS

Between April 2004 and December 2009, 909 patients who underwent primary PCI and with at least three TC values were included in the final study. TC variability was calculated using four indices: standard deviation (SD), coefficient of variation (CV), the average successive variability (ASV), variability independent of the mean (VIM). MACCE comprised all-cause mortality, non-fatal myocardial infarction (MI), unplanned revascularization, hospitalization for heart failure, and non-fatal stroke.

RESULTS

There were 394 cases of MACCE during the follow-up period. When the subjects were divided into quartile groups by CV of TC, high CV groups were associated with a higher hazard ratio of MACCE than for lower CV groups. In multivariable adjusted models, TC variability and MACCE remained correlated [HR (95% CI): Q2, 1.17 (0.86-1.58); Q3, 1.38 (1.03-1.85); Q4, 1.63 (1.22-2.17)]. Similar patterns of MACCE were noted by quartiles of SD, ASV, and VIM.

CONCLUSION

Visit-to-visit TC variability is positively correlated with MACCE in patients after PCI.

Prediction of Atrial Fibrillation in Hospitalized Elderly Patients With Coronary Heart Disease and Type 2 Diabetes Mellitus Using Machine Learning: A Multicenter Retrospective Study

Background

The objective of this study was to use machine learning algorithms to construct predictive models for atrial fibrillation (AF) in elderly patients with coronary heart disease (CHD) and type 2 diabetes mellitus (T2DM).

Methods

The diagnosis and treatment data of elderly patients with CHD and T2DM, who were treated in four tertiary hospitals in Chongqing, China from 2015 to 2021, were collected. Five machine learning algorithms: logistic regression, logistic regression+least absolute shrinkage and selection operator, classified regression tree (CART), random forest (RF) and extreme gradient lifting (XGBoost) were used to construct the prediction models. The area under the receiver operating characteristic curve (AUC), sensitivity, specificity, and accuracy were used as the comparison measures between different models.

Results

A total of 3,858 elderly patients with CHD and T2DM were included. In the internal validation cohort, XGBoost had the highest AUC (0.743) and sensitivity (0.833), and RF had the highest specificity (0.753) and accuracy (0.735). In the external verification, RF had the highest AUC (0.726) and sensitivity (0.686), and CART had the highest specificity (0.925) and accuracy (0.841). Total bilirubin, triglycerides and uric acid were the three most important predictors of AF.

Conclusion

The risk prediction models of AF in elderly patients with CHD and T2DM based on machine learning algorithms had high diagnostic value. The prediction models constructed by RF and XGBoost were more effective. The results of this study can provide reference for the clinical prevention and treatment of AF.

Mean and Variability of Lipid Measurements and Risk for Development of Subclinical Left Ventricular Diastolic Dysfunction

BACKGROUND

Subclinical left ventricular diastolic dysfunction (LVDD) is an emerging consequence of increased insulin resistance, and dyslipidemia is one of the few correctable risk factors of LVDD. This study evaluated the role of mean and visit-to-visit variability of lipid measurements in risk of LVDD in a healthy population.

METHODS

This was a 3.7-year (interquartile range, 2.1 to 4.9) longitudinal cohort study including 2,817 adults (median age 55 years) with left ventricular ejection fraction >50% who underwent an annual or biannual health screening between January 2008 and July 2016. The mean, standard deviation (SD), coefficient of variation (CV), variability independent of the mean (VIM), and average real variability of total cholesterol, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), apolipoprotein B (apoB), non-HDL-C, and triglycerides were obtained from three to six measurements during the 5 years preceding the first echocardiogram.

RESULTS

Among the 2,817 patients, 560 (19.9%) developed LVDD. The mean of no component of lipid measurements was associated with risk of LVDD. CV (hazard ratio [HR], 1.35; 95% confidence interval [CI], 1.10 to 1.67), SD (HR, 1.27; 95% CI, 1.03 to 1.57), and VIM (HR, 1.26; 95% CI, 1.03 to 1.55) of LDL-C and all the variability parameters of apoB were significantly associated with development of LVDD. The association between CV-LDL and risk of LVDD did not have significant interaction with sex, increasing/decreasing trend at baseline, or use of stain and/or lipid-modifying agents.

CONCLUSION

The variability of LDL-C and apoB, rather than their mean, was associated with risk for LVDD.

Prognostic significance of visit-to-visit variability, and maximum and minimum LDL cholesterol in diabetes mellitus

BACKGROUND

Current guidelines for dyslipidemia management recommend that the LDL-C goal be lower than 70 mg/dL. The present study investigated the prognostic significance of visit-to-visit variability in LDL-C, and minimum and maximum LDL-C during follow-up in diabetes mellitus.

METHODS

The risk of outcomes in relation to visit-to-visit LDL-C variability was investigated in the Action to Control Cardiovascular Risk in Diabetes (ACCORD) Lipid trial. LDL-C variability indices were coefficient of variation (CV), variability independent of the mean (VIM), and average real variability (ARV). Multivariable Cox proportional hazards models were employed to estimate the adjusted hazard ratio (HR) and 95% confidence interval (CI).

RESULTS

Compared with the placebo group (n=2667), the fenofibrate therapy group (n=2673) had a significantly (P<0.01) lower mean plasma triglyceride (152.5 vs. 178.6 mg/dL), and total cholesterol (158.3 vs.162.9 mg/dL) but a similar mean LDL-C during follow-up (88.2 vs. 88.6 mg/dL, P>0.05). All three variability indices were associated with primary outcome, total mortality and cardiovascular mortality both in the total population and in the fenofibrate therapy group but only with primary outcome in the placebo group. The minimum LDL-C but not the maximum during follow-up was significantly associated with various outcomes in the total population, fenofibrate therapy and placebo group. The minimum LDL-C during follow-up ≥70 mg/dL was associated with an increased risk for various outcomes.

CONCLUSIONS

Visit-to-visit variability in LDL-C was a strong predictor of outcomes, independent of mean LDL-C. Patients with LDL-C controlled to less than 70 mg/dL during follow-up might have a benign prognosis. ClinicalTrials.gov number: NCT00000620.

The Association of Postprandial Triglyceride Variability with Renal Dysfunction and Microalbuminuria in Patients with Type 2 Diabetic Mellitus: A Retrospective and Observational Study

OBJECTIVE

We examined whether or not day-to-day variations in lipid profiles, especially triglyceride (TG) variability, were associated with the exacerbation of diabetic kidney disease.

METHODS

We conducted a retrospective and observational study. First, 527 patients with type 2 diabetes mellitus (DM) who had had their estimated glomerular filtration rate (eGFR) checked every 6 months since 2012 for over 5 years were registered. Variability in postprandial TG was determined using the standard deviation (SD), SD adjusted (Adj-SD) for the number of measurements, and maximum minus minimum difference (MMD) during the first three years of follow-up. The endpoint was a ≥40% decline from baseline in the eGFR, initiation of dialysis or death. Next, 181 patients who had no micro- or macroalbuminuria in February 2013 were selected from among the 527 patients for an analysis. The endpoint was the incidence of microalbuminuria, initiation of dialysis, or death.

RESULTS

Among the 527 participants, 110 reached a ≥40% decline from baseline in the eGFR or death. The renal survival was lower in the higher-SD, higher-Adj-SD, and higher-MMD groups than in the lower-SD, lower-Adj-SD, and lower-MMD groups, respectively (log-rank test p = 0.0073, 0.0059, and 0.0195, respectively). A lower SD, lower Adj-SD, and lower MMD were significantly associated with the renal survival in the adjusted model (hazard ratio, 1.62, 1.66, 1.59; 95% confidence intervals, 1.05-2.53, 1.08-2.58, 1.04-2.47, respectively). Next, among 181 participants, 108 developed microalbuminuria or death. The nonincidence of microalbuminuria was lower in the higher-SD, higher-Adj-SD, and higher-MMD groups than in the lower-SD, lower-Adj-SD, and lower-MMD groups, respectively (log-rank test p = 0.0241, 0.0352, and 0.0474, respectively).

CONCLUSIONS

Postprandial TG variability is a novel risk factor for eGFR decline and the incidence of microalbuminuria in patients with type 2 DM.

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.

HDL-C, longitudinal change and risk of mortality in a Chinese cohort study

BACKGROUND AND AIMS

High-density lipoprotein cholesterol (HDL-C) concentration and variability are both important factors of cardiovascular disease (CVD) and mortality. We aimed to explore the associations of HDL-C and longitudinal change in HDL-C with risk of mortality.

METHODS AND RESULTS

We recruited a total of 69,163 participants aged ≥40 years and had medical examination records of HDL-C during 2010-2014 from the Yinzhou District, Ningbo, China. Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated using Cox proportional hazards regression models. We observed a non-linear association of HDL-C with risks of non-accidental and CVD mortality. Compared with the moderate concentration group (1.4-1.6 mmol/L), HDL-C <1 mmol/L was associated with a higher risk of non-accidental mortality (HR: 1.13 (95% CI: 1.01-1.27)) and both HDL-C <1 mmol/L and ≥2 mmol/L were associated with a higher risk of CVD mortality (HRs: 1.23 (95% CI: 1.01-1.50) and 1.37 (95% CI: 1.03-1.82), respectively). Compared with the stable group ([-0.1, +0.1 mmol/L]), a large decrease ([-0.5, -0.3 mmol/L]) and very large decrease (<-0.5 mmol/L) in HDL-C were associated with a higher risk of non-accidental mortality (HRs: 1.40 (95% CI: 1.21-1.63) and 1.78 (95% CI: 1.44-2.20), respectively). Similar results were observed for CVD mortality and cancer mortality.

CONCLUSION

Extremely low or high HDL-C and a large decrease or very large decrease in HDL-C were associated with a higher risk of cause-specific mortality. Monitoring of HDL-C may have utility in identifying individuals at higher risk of mortality.

Attenuating the Variability of Lipids Is Beneficial for the Hypertension Management to Reduce the Cardiovascular Morbidity and Mortality in Older Adults

Objective: To investigate the beneficial of attenuating the variability of lipids to the hypertension management in older adults.

Methods: Between April 2008 and November 2010, 1,244 hypertensive patients aged ≥60 years were recruited and randomized into placebo and rosuvastatin groups. Outcomes and inter-visit plasma lipids variability were assessed.

Results: Over an average follow-up of 83.5 months, the coefficients of variation (CVs) in total cholesterol (TCHO), triglycerides, high-density lipoprotein cholesterol (HDL-c), and low-density lipoprotein cholesterol (LDL-c) were significantly lower in the rosuvastatin group than the placebo group (p < 0.05). The risks of composite cardiovascular event, myocardial infarction, coronary revascularization, heart failure, total stroke, ischemic stroke, cardiovascular death, and all-cause death were significantly lower in the rosuvastatin group than the placebo group (all p < 0.05). The differences in the risks were significantly diminished after the CVs for TCHO, triglycerides, HDL-c, and LDL-c were separately included as confounders. One-SD of CVs for TCHO, triglycerides, HDL-c, and LDL-c increment were significantly associated with the risks of composite cardiovascular event, myocardial infarction, heart failure, total stroke, ischemic stroke, cardiovascular death, and all-cause death, respectively (all p < 0.05).

Conclusions: Rosuvastatin significantly attenuated the intra-visit variability in lipids and decreased the risk of cardiovascular mortality and morbidity. Controlling the variability of lipids is as important as antihypertensive treatment to reduce the cardiovascular morbidity and mortality in the management of older hypertensive patients.

Clinical Trial Registration:ChiCTR.org.cn, ChiCTR-IOR-17013557.

Variability of risk factors and diabetes complications

Several studies suggest that, together with glucose variability, the variability of other risk factors, as blood pressure, plasma lipids, heart rate, body weight, and serum uric acid, might play a role in the development of diabetes complications. Moreover, the variability of each risk factor, when contemporarily present, may have additive effects. However, the question is whether variability is causal or a marker. Evidence shows that the quality of care and the attainment of the target impact on the variability of all risk factors. On the other hand, for some of them causality may be considered. Although specific studies are still lacking, it should be useful checking the variability of a risk factor, together with its magnitude out of the normal range, in clinical practice. This can lead to an improvement of the quality of care, which, in turn, could further hesitate in an improvement of risk factors variability.

The association of blood lipid parameters variability with ischemic stroke in hypertensive patients

BACKGROUND AND AIMS

The relationship between lipid variability and stroke among patients with hypertension were inconclusive. We aimed to investigate the association of lipid variability with ischemic stroke in hypertensive patients.

METHODS AND RESULTS

This retrospective cohort study included 4995 individuals with hypertension between 2013 and 2015, and recorded their status of ischemic stroke until the end of 2018. The variability in total cholesterol (TC), triglyceride (TG), low-density lipoprotein cholesterol (LDL-C) and high-density lipoprotein cholesterol (HDL-C) were measured using the standard deviation (SD), coefficient of variation (CV), variability independent of the mean (VIM) and average absolute difference between successive values (ASV). Multivariate Cox proportional hazards models with hazard ratios (HRs) and 95% confidence interval (CI) were performed. There were 110 cases of ischemic stroke during a median follow up of 4.2 years. The multivariable adjusted HRs and 95% CIs comparing the highest versus the lowest quartiles of SD of TC, LDL-C, HDL-C and TG were 4.429 (95% CI: 2.292, 8.560), 2.140 (95% CI: 1.264, 3.621), 1.368 (95% CI: 0.793, 2.359) and 1.421 (95% CI: 0.800, 2.525), respectively. High variability in TC and LDL-C were associated with a higher risk for ischemic stroke. Similarly, the results were consistent when calculating variability of TC and LDL-C using CV, ASV and VIM, and in various subgroup analyses.

CONCLUSION

Higher variability of TC and LDL-C associated with the risk of ischemic stroke among hypertensive patients. These findings suggest reducing variability of lipid parameters may decrease adverse outcomes.

Greater variability in lipid measurements associated with kidney diseases in patients with type 2 diabetes mellitus in a 10-year diabetes cohort study

This study aimed to evaluate the associations between variability of lipid parameters and the risk of kidney disease in patients with type 2 diabetes mellitus. Low-density lipoprotein-cholesterol, total cholesterol to high-density lipoprotein-cholesterol ratio and triglyceride were specifically addressed in this study. This retrospective cohort study included 105,552 patients aged 45-84 with type 2 diabetes mellitus and normal kidney function who were managed under Hong Kong public primary care clinics during 2008-2012. Those with kidney disease (estimated glomerular filtration rate < 60 mL/min/1.73 m2 or urine albumin to creatinine ratio ≥ 3 mg/mmol) were excluded. Variabilities of low-density lipoprotein-cholesterol, total cholesterol to high-density lipoprotein-cholesterol ratio and triglyceride were determined using the standard deviation of the respective parameter obtained from a mixed effects model to minimize regression dilution bias. The associations between lipid variability and renal outcomes including incident kidney disease, renal function decline defined as ≥ 30% reduction in estimated glomerular filtration rate since baseline, and end-stage renal disease (estimated glomerular filtration rate < 15 mL/min/1.73 m2) were evaluated by multivariable Cox regression. After a median follow-up of 66.5 months (0.5 million person-years in total), 49,653 kidney disease, 29,358 renal function decline, and 1765 end-stage renal disease cases were recorded. Positive linear associations between low-density lipoprotein-cholesterol and total cholesterol to high-density lipoprotein-cholesterol ratio variabilities and the risk of all renal outcomes were demonstrated. However, no association between triglyceride variability and any outcome was found. Each mmol/L increase in low-density lipoprotein-cholesterol variability was associated with 20% (Hazard ratio 1.20 [95% CI 1.15-1.25]), 38% (Hazard ratio 1.37 [95% CI 1.30-1.45]), and 108% (Hazard ratio 2.08 [95% CI 1.74-2.50]) higher risk in incident kidney disease, renal function decline and end-stage renal disease respectively. Similarly, each unit increase in total cholesterol to high-density lipoprotein-cholesterol ratio variability was associated with 35% (Hazard ratio 1.15 [95% CI 1.10-1.20]), 33% (Hazard ratio 1.33 [95% CI 1.26-1.40]), and 75% (Hazard ratio 1.75 [95% CI 1.46-2.09]) heightened risk in incident kidney disease, renal function decline and end-stage renal disease respectively. Cholesterol variability may potentially be a useful predictor of kidney diseases in patients with type 2 diabetes mellitus. Attention should be drawn to cholesterol variability when managing diabetic patients and further research is warranted to investigate the modifiable risk factors for lipid variability.

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.

Impact of Mean and Variability of High-Density Lipoprotein-Cholesterol on the Risk of Myocardial Infarction, Stroke, and Mortality in the General Population

Background

A low level of high‐density lipoprotein‐cholesterol (HDL‐C) is a well‐known risk factor for cardiovascular events. Recent studies have also suggested that HDL‐C variability has a predictive role in patients with coronary artery disease. We investigated the combined effect of the mean and variability of HDL‐C on the risk of myocardial infarction (MI), stroke, and mortality in the general population.

Methods and Results

We selected 5 433 098 subjects in the Korean National Health Insurance System cohort who had no history of MI or stroke and who underwent ≥3 health examinations between 2009 and 2013. Visit‐to‐visit HDL‐C variability was calculated using the coefficient of variation, variability independent of the mean and average real variability. The low‐mean and high‐variability groups were defined as the lowest and highest quartiles of HDL‐C mean and variability, respectively. There were 27 605 cases of MI, 31 162 cases of stroke, and 50 959 deaths during the median follow‐up of 5.1±0.6 years. A lower mean or higher variability (coefficient of variation) of HDL‐C was associated with a higher risk of adverse outcomes, and the 2 measures had an additive effect. In the multivariable‐adjusted model, the hazard ratios (95% CIs) of the low‐mean/high‐variability group compared with the high‐mean/low‐variability group were 1.47 (1.41–1.54) for MI, 1.23 (1.18–1.28) for stroke, and 1.41 (1.36–1.45) for all‐cause mortality. Results were consistent when variability was modeled using variability independent of the mean or average real variability, and in various sensitivity and subgroup analyses.

Conclusions

Low mean and high variability of HDL‐C is associated with an increased risk of MI, stroke, and mortality.

Biomarker variability and cardiovascular disease residual risk

PURPOSE OF REVIEW

A number of cohorts and clinical trials have reported observing associations between intraindividual variation of biomarkers and manifestations of cardiovascular disease (CVD).

RECENT FINDINGS

Intraindividual (or 'visit-to-visit') variability of total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), apolipoprotein B, high-density lipoprotein cholesterol (HDL-C), non-HDL-C, and triglyceride have all been found to associate with CVD outcomes, independent of their mean absolute levels, independent of each other, and independent of other traditional risk factors. These findings have been confirmed recently in large cohort studies in different populations, and in post-hoc analyses of clinical trial data. Lipoprotein variability has been associated with myocardial infarction, other arterial disease including cerebrovascular, and with cardiovascular and overall mortality. The association of higher variability of LDL-C with atheroma progression has also been assessed directly using intravascular ultrasound and carotid intima-media thickness. The lipoprotein variability of an individual contributes to their residual risk of CVD, although the mechanism remains unclear.

SUMMARY

There is compelling evidence that lipoprotein variability contributes to residual risk; however, a more standardized approach is required before the risk attributable to variability can be assessed effectively.

Visit-to-Visit Variability of Lipids Measurements and the Risk of Stroke and Stroke Types: A Prospective Cohort Study

BACKGROUND AND PURPOSE

Previous studies suggested increased visit-to-visit variability of total cholesterol (TC) is associated with stroke. This study aimed to investigate the associations of various lipids measurements variability and the risk of stroke and stroke type (ischemic and hemorrhagic stroke).

METHODS

Fifty-one thousand six hundred twenty participants in the Kailuan Study without history of myocardial infarction, stroke, and cancer who underwent three health examinations during 2006 to 2010 were followed for incident stroke. Variability in TC, triglycerides, high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C) measurements were measured using the coefficient of variation (CV), standard deviation (SD), variability independent of the mean (VIM), and average real variability (ARV).

RESULTS

During a median of 6.04 years of follow-up, 1,189 incident stroke (1,036 ischemic and 160 hemorrhagic stroke) occurred. In the multivariable-adjusted model, the hazard ratio (HR) comparing participants in the highest versus lowest quartile of CV of HDL-C were 1.21 (95% confidence interval [CI], 1.02 to 1.45; P for trend=0.013) for ischemic stroke. The highest quartile of CV of LDL-C was associated with 2.17-fold risk of hemorrhagic stroke (HR, 2.17; 95% CI, 1.25 to 3.75; P for trend=0.002) compared with the lowest quartile. We did not observe any significant association between TC and triglycerides variability with any of stroke. Consistent.

RESULTS

were obtained when calculating variability index using SD, VIM, or ARV.

CONCLUSIONS

These findings suggest the high visit-to-visit HDL-C and LDL-C variability were associated with an increased incidence of ischemic and hemorrhagic stroke, respectively.

Low Lipid Levels and High Variability are Associated With the Risk of New-Onset Atrial Fibrillation

Background

While high levels of lipids and lipid variability are established risk factors for atherosclerotic cardiovascular disease, their roles in the development of atrial fibrillation (AF) are unclear, with previous studies suggesting a “cholesterol paradox.”

Methods and Results

A nationwide population‐based cohort of 3 660 385 adults (mean age 43.4 years) from the Korean National Health Insurance Service database, with ≥3 annual lipid measurements from 2009 to 2012 and without a history of AF or prescription of lipid‐lowering medication before 2012, were identified. Total cholesterol, low‐density lipoprotein cholesterol, high‐density lipoprotein cholesterol, and triglycerides levels were measured, and lipid variability was calculated using variability independent of the mean. The cohort was divided into quartiles by lipid levels and lipid variability and followed up for incident AF. During a median 5.4 years of follow‐up, AF was newly diagnosed in 27 581 (0.75%). AF development was inversely associated with high lipid levels (for top versus bottom quartile; total cholesterol, HR 0.78, 95% CI 0.76–0.81; low‐density lipoprotein cholesterol, HR 0.81, 95% CI 0.78–0.84; high‐density lipoprotein cholesterol, HR 0.94, 95% CI 0.91–0.98; triglycerides, HR 0.88, 95% CI 0.85–0.92). Meanwhile, AF development was associated with high lipid variability (for top versus bottom quartile; total cholesterol, HR 1.09, 95% CI 1.06–1.13; low‐density lipoprotein cholesterol, HR 1.12, 95% CI 1.08–1.16; high‐density lipoprotein cholesterol, HR 1.08, 95% CI 1.04–1.12; triglycerides, HR 1.05, 95% CI 1.01–1.08). Men showed greater risk reduction with high triglyceride levels and greater risk with high triglyceride variability for incident AF.

Conclusions

Low cholesterol levels and high cholesterol variability were associated with a higher risk of AF development.

HDL-Cholesterol, Its Variability, and the Risk of Diabetes: A Nationwide Population-Based Study

CONTEXT

The bidirectional relationship between low high-density lipoprotein cholesterol (HDL-C) and glucose intolerance is well established. Recent studies suggested an association of lipid variability with various health outcomes.

OBJECTIVE

To investigate the combined effect of HDL-C levels and their variability on the risk of diabetes.

DESIGN

A population-based cohort study.

SETTING AND PARTICIPANTS

In all, 5,114,735 adults without known diabetes in the Korean National Health Insurance System cohort who underwent three or more health examinations from 2009 to 2013 were included. Visit-to-visit HDL-C variability was calculated using variability independent of the mean (VIM) and the coefficient of variation (CV). Low mean and high variability groups were defined as the lowest and highest quartiles of HDL-C mean and variability, respectively.

MAIN OUTCOME MEASURES

Newly developed diabetes.

RESULTS

There were 122,192 cases (2.4%) of incident diabetes during the median follow-up of 5.1 years. Lower mean or higher variability of HDL-C was associated with higher risk of diabetes in a stepwise manner, and an additive effect of the two measures was noted. In the multivariable-adjusted model, the hazard ratios and 95% CIs for incident diabetes were 1.20 (1.18 to 1.22) in the high mean/high VIM group, 1.35 (1.33 to 1.37) in the low mean/low VIM group, and 1.40 (1.38 to 1.42) in the low mean/high VIM group compared with the high mean/low VIM group. Similar results were observed when modeling the variability using CV and in various subgroup analyses.

CONCLUSIONS

Low mean and high variability in HDL-C were independent predictors of diabetes with an additive effect. Both elevating and stabilizing HDL-C may be important goals for reducing diabetes risk.

Intra-individual variability of total cholesterol is associated with cardiovascular disease mortality: A cohort study

BACKGROUND AND AIMS

The relationship between serum total cholesterol (TC) and mortality remains inconsistent. Additionally, intra-individual variability of cholesterol has been of increasing interest as a new indicator for health outcomes. We aimed to examine the association between TC and its variability and risk of mortality.

METHODS AND RESULTS

We performed a retrospective cohort study with 122,645 individuals aged over 40 years in Ningbo, China. The intra-individual variability was calculated using four metrics including standard deviation, coefficient variation, variation independent of mean and average successive variability. Hazard ratios and 95% confidence intervals were estimated for the associations of baseline and variability in TC with risk of mortality by Cox proportional hazards regression models. During 591,585.3 person-years of follow-up, 4563 deaths (including 1365 from cardiovascular disease, 788 from stroke and 1514 from cancer) occurred. A U-shaped association was observed for baseline TC level and risk of total, cardiovascular and cancer mortality, with lowest mortality at 5.46 mmol/L, 5.04 mmol/L and 5.51 mmol/L, respectively. As compared with subjects with TC variability in the lowest quartile, individuals in the highest quartile had 21% higher risk of all-cause mortality (HR = 1.21, 95% CI: 1.05 to 1.40), and 41% higher risk of CVD mortality (HR = 1.41, 95%CI: 1.10 to 1.81).

CONCLUSION

Both too low and too high baseline TC level were associated with higher risk of total, cardiovascular disease and cancer mortality. Variability of TC could be a risk factor of total and CVD mortality, independent of mean TC level. Future studies are needed to confirm these findings.

The Clinical Importance of the Plasma Atherogenic Index, Other Lipid Indexes, and Urinary Sodium and Potassium Excretion in Patients with Stroke

OBJECTIVE

Cardiovascular complications are still the primary reason for high mortality rates worldwide. The determination of risk factors is important to prevent stroke. The aim of the present study was to analyze the importance of serum lipid indexes and urinary sodium (Na)/potassium (K) excretion in patients with stroke together with sex differences.

MATERIALS AND METHODS

A total of 50 (28 male and 22 female, mean age 65.9±14.6 years) patients with acute stroke were included in the study group, and 32 body mass index-matched healthy subjects were included in the control group. Lipid profiles [(cholesterol, triglyceride, very low-density lipoprotein, low-density lipoprotein, and high-density lipoprotein (HDL)], serum creatinine (Cre), erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), and Na, K, and Cre excretion in spot urine samples of the patients were recorded.

RESULTS

Systolic blood pressure (p=0.021), ESR (p=0.044), and CRP (p=0.042) were significantly higher in all patients in the stroke group; urinary Tanaka (K) (p=0.033), Kawazaki (K) (p=0.028), urinary spot Cre (p=0.012), and Na excretion (p=0.036) levels were found to be significantly lower in only male patients with stroke. The mean plasma atherogenic indexes were 0.57±0.24 in the study (stroke) group and 0.54±0.22 in the control group (p=0.61). Other lipid indexes, such as Castelli's risk index (CRI)-I (p=0.29), CRI-II (p=0.24), atherogenic coefficient (p=0.29), and non-HDL cholesterol (p=0.69), were not statistically different from the controls.

CONCLUSION

Urinary Na, K, and Cre excretion was significantly lower in male patients with stroke, and acute phase reactants were significantly higher in the entire stroke group than in controls. These parameters can be used as auxiliary biomarkers in the risk assessment of stroke.

GREATER LOW-DENSITY LIPOPROTEIN CHOLESTEROL VARIABILITY INCREASES THE RISK OF CARDIOVASCULAR EVENTS IN PATIENTS WITH TYPE 2 DIABETES MELLITUS

Objective: Variability in lipid levels has been associated with poor cardiovascular outcomes in patients with coronary artery disease. The aim of this study was to investigate whether low-density lipoprotein cholesterol (LDLC) variability can be used to predict cardiovascular events in patients with type 2 diabetes mellitus (DM). Methods: A total of 5,354 patients with type 2 DM were enrolled in this study. Cardiovascular events including peripheral arterial disease, coronary artery disease, stroke, and cardiovascular death were defined as the study endpoints, and standard deviations of lipid levels were used to define intra-individual lipid variability. Results: Univariate Cox proportional hazards analysis showed that LDL-C standard deviation (hazard ratio [HR] = 1.016; 95% confidence interval [CI] = 1.006 to 1.022; P<.001) was associated with a higher risk of cardiovascular events. Multivariate Cox proportional hazards analysis showed that an increase in LDL-C standard deviation significantly increased the risk of cardiovascular events (HR = 1.063; 95% CI = 1.025 to 1.102; P = .01). Kaplan-Meier analysis of cardiovascular event-free survival showed that the patients in tertiles 2 and 3 of the standard deviation of LDL-C had worse cardiovascular event-free survival compared to those in tertile 1. Conclusion: Variability in LDL-C could predict cardiovascular events in the patients with type 2 DM in this study. Abbreviations: CAD = coronary artery disease; CI = confidence interval; CVD = cardiovascular disease; DM = diabetes mellitus; eGFR = estimated glomerular filtration rate; HbA1c = glycosylated hemoglobin; HDL-C = high-density lipoprotein cholesterol; HR = hazard ratio; KMUHRD = Kaohsiung Medical University Hospital Research Database; LDL-C = low-density lipoprotein cholesterol; SD = standard deviation; UACR = urine albumin to creatinine ratio.

Variability in Total Cholesterol Concentration Is Associated With the Risk of Dementia: A Nationwide Population-Based Cohort Study

Introduction: Although total cholesterol (TC) variability is suggested as a risk factor for cardiovascular and cerebrovascular disease, there is no previous study to evaluate the association between TC variability and the development of dementia. Methods: Using the Korean National Health Insurance Service-Health Screening Cohort (NHIS-HEALS), the main outcomes were newly diagnosed all-cause dementia, Alzheimer's disease (AD), or vascular dementia (VaD) between January 1, 2008, and December 31, 2015. Visit-to-visit TC variability was measured as variability independent of the mean (TC-VIM), coefficient variance (TC-CV), and standard deviation (TC-SD). Results: In a total of 131,965 Koreans, there were 3,722 all-cause dementia (2.82%), 2,776 AD (2.10%), and 488 VaD (0.37%) during the median follow-up of 8.4 years. Kaplan-Meier curves showed increased cumulative incidences for all in the group of the highest quartiles of TC variability compared to the others. Regression using the Fine and Gray hazards model showed a steadily increasing risk of all-cause dementia with higher quartiles of TC variability. After adjusting for confounders including mean TC level and comparing the highest and lowest TC-VIM quartiles, the hazard ratios (HRs) for all-cause dementia and AD were 1.15 [95% confidence interval (CI) = 1.05-1.27; P = 0.003] and 1.12 (95% CI = 1.00-1.25; P = 0.040), respectively. The incidence of VaD was not significantly higher in the higher-quartile groups compared to that in the lowest-quartile group in TC-VIM variability (HR 1.22; 95% CI = 0.95-1.59; P = 0.122). These associations were consistent with TC variability defined by TC-CV or TC-SD. Conclusions: For the first time, we have demonstrated that a higher visit-to-visit variability in TC independent of mean TC is associated with an increased risk of all-cause dementia and AD in the general population.

Association of Variability in Body Mass Index and Metabolic Health With Cardiometabolic Disease Risk

Background Metabolic syndrome is associated with high risk of cardiovascular disease, although risk may differ according to the specific conditions present and variability in those conditions. Methods and Results We defined obesity (body mass index [BMI] ≥30 kg/m2) and metabolic health (<2 nonobesity National Cholesterol Education Program Adult Treatment Panel III conditions) among 3632 Framingham Heart Study offspring cohort participants (mean age, 50.8 years; 53.8% women) who were followed up from 1987 to 2014. We defined participants whose variance independent of the mean for a metabolic syndrome-associated measure was in the top quintile as being "variable" for that measure. Variable metabolic health was defined as ≥2 variable nonobesity metabolic syndrome components. We investigated the interaction between obesity and metabolic health in their associations with cardiometabolic disease and cardiovascular disease using Cox proportional hazards regression. In addition, we estimated the associations of BMI variability and variable metabolic health with study outcomes within categories of obesity and metabolic health status, respectively. We observed 567 incident obesity (41 439 person-years), 771 incident metabolically unhealthy state (25 765 person-years), 272 incident diabetes mellitus (56 233 person-years), 503 incident hypertension (12 957 person-years), 589 cardiovascular disease (60 300 person-years), and 195 chronic kidney disease (47 370 person-years) events on follow-up. Obesity and being metabolically unhealthy were independently and positively associated with all outcomes. BMI variability, compared with stable BMI, was associated with 163%, 67%, 58%, and 74% higher risks of having obesity, becoming metabolically unhealthy, having diabetes mellitus, and having hypertension, respectively, among nonobese participants. Variable metabolic health, compared with stable metabolic health, was associated with a 28% higher risk of cardiovascular disease, among metabolically healthy participants. Conclusions We did not observe evidence for a positive interaction between obesity and metabolic health status with regard to study outcomes. BMI and metabolic health variability are associated with adverse health outcomes.

Overall Quality of Care Predicts the Variability of Key Risk Factors for Complications in Type 2 Diabetes: An Observational, Longitudinal Retrospective Study

OBJECTIVE

An association between variability in clinical parameters (HbA_1c, blood pressure, cholesterol, and uric acid) and risk of complications in type 2 diabetes has been reported. In this analysis, we investigated to what extent such variability is associated with overall quality of care.

RESEARCH DESIGN AND METHODS

The quality of care summary score (Q-score) represents a validated, overall quality of care indicator ranging between 0 and 40; the higher the score, the better the quality of care provided by the diabetes center. We identified patients with five or more measurements of clinical parameters after the assessment of the Q-score. Multiple linear regression analyses assessed the role of the Q-score in predicting the variability of the different parameters.

RESULTS

Overall, 273,888 patients were analyzed. The variability of all the parameters systematically increased with decreasing Q-score values. At multivariate linear regression analysis, compared with a Q-score >25, a score <15 was associated with a significantly larger variation in HbA_1c, blood pressure, uric acid, total cholesterol, and LDL cholesterol and a lower variation in HDL cholesterol. The analysis of standardized β coefficients show that the Q-score has a larger impact on the variability of HbA_1c (0.34; P < 0.0001), systolic blood pressure (0.21; P < 0.0001), total cholesterol (0.21; P < 0.0001), and LDL cholesterol (0.20; P < 0.0001).

CONCLUSIONS

The variability of risk factors for diabetic complications is associated with quality of care. Quality of care improvement initiatives should be targeted to increase the achievement of the recommended target while reducing such variability.