Niacin and progression of CKD.

Niacin is the oldest drug available for the treatment of dyslipidemia. It has been studied extensively and tested in clinical trials of atherosclerotic cardiovascular disease prevention and regression in the general population, but not specifically in patients with chronic kidney disease (CKD), who are at extremely high residual risk despite current therapy. Despite the current controversy about recent trials with niacin, including their limitations, there may be a place for this agent in select patients with CKD with dyslipidemia. Niacin has a favorable unique impact on factors affecting the rate of glomerular filtration rate decline, including high-density lipoprotein (HDL) particle number and function, triglyceride levels, oxidant stress, inflammation and endothelial function, and lowering of serum phosphorus levels by reducing dietary phosphorus absorption in the gastrointestinal tract. These effects may slow glomerular filtration rate decline and ultimately improve CKD outcomes and prevent cardiovascular risk. This review presents the clinically relevant concept that niacin holds significant potential as a renoprotective therapeutic agent. In addition, this review concludes that clinical investigations to assess the effect of niacin (in addition to aggressive low-density lipoprotein cholesterol lowering) on reduction of cardiovascular events in patients with CKD with very low HDL cholesterol (or those with identified dysfunctional HDL) and elevated triglyceride levels need to be considered seriously to address the high residual risk in this population.

Precision Medicine and Personalized Management of Lipoprotein and Lipid Disorders in Chronic and End-Stage Kidney Disease.

Precision medicine is an emerging field that calls for individualization of treatment strategies based on characteristics unique to each patient. In lipid management, current guidelines are driven mainly by clinical trial results that presently indicate that patients with non-dialysis-dependent chronic kidney disease (CKD) should be treated with a ß-hydroxy ß-methylglutaryl-CoA reductase inhibitor, also known as statin therapy. For patients with end-stage kidney disease (ESKD) being treated with hemodialysis, statin therapy has not been shown to successfully reduce poor outcomes in trials and therefore is not recommended. The two major guidelines dissent on whether statin therapy should be of moderate or high intensity in non-dialysis-dependent CKD patients, but often leave the prescribing clinician to make that decision. These decisions often are complicated by the increased concerns for adverse events such as myopathies in patients with advanced kidney disease and ESKD. In the future, there may be an opportunity to further identify CKD and ESKD patients who are more likely to benefit from lipid-modifying therapy as opposed to those who likely will suffer from its side effects using precision medicine tools. For now, data from genetics studies and subgroup analyses may provide insight for future research directions in this field and we review some of the work that has been published in this regard.

Glucose dynamics in Type I diabetes: insights from the classic and linear minimal models.

This study demonstrates that the classic minimal model (MM) and the linear minimal model (LMM) are able to follow the dynamics of glucose in Type I diabetes. LMM precision is better than the MM with systematic lower mean values for the coefficient of variation (CV) in all characteristic model parameters. LMM S(I)(L)=7.40 is not significantly different from MM S(I)=10.71 (units 1/min per muU/ml, alpha=0.001) with a strong correlation (R(s) = 0.83, alpha=0.01). LMM S(G)(L)=0.0407 appears to be significantly different to S(G)=0.0266 (units 1/min, alpha=0.001) but correlates very well (R(s)=0.91,alpha=0.01). Since residuals appear to be heteroscedastic, further work is required to address the effect of modeling and signal processing on them. For the data under study, the models are not able to fit two-thirds of the data windows available. This is because none of the models are able to follow complex situations such as the presence of several bolus injections, the absence of insulin supply or inappropriate insulin dosage. A synthesis of the patterns found in these windows is presented which would be useful for the development of new models for fitting these data.

Can continuous glucose monitoring provide objective documentation of hypoglycemia unawareness?

OBJECTIVE: To establish criteria defining hypoglycemia as detected by the continuous glucose monitoring system (CGMS) in patients with type 1 diabetes that best predict hypoglycemia unawareness (HUN), established by a validated questionnaire. METHODS: Adult patients were selected for inclusion in this study if they had long-standing type 1 diabetes, a fasting level of C peptide of < or = 0.6 ng/mL, commitment to achieving glycemic control, and a hemoglobin A1c value no higher than 9%. After clinical data and self-monitoring of plasma glucose data were collected, patients underwent a 72-hour glucose monitoring session with use of a Medtronic-MiniMed CGMS. The presence of HUN was determined by a questionnaire. Factors independently associated with HUN were estimated by multivariate independent analysis. RESULTS: Our study group consisted of 60 patients (33 women and 27 men) who ranged in age from 18 to 84 years (mean, 50.4) and had had diabetes for 5 to 56 years (mean, 23.8). The best predictor of HUN was the maximal duration of hypoglycemia, as determined by the CGMS (P = 0.001). Detection of hypoglycemic episodes with a duration of more than 90 minutes identified patients who had HUN with an 88% specificity and 75% sensitivity. HUN was also significantly associated with use of angiotensin-converting enzyme inhibitors or angiotensin receptor blockers (P = 0.003) and with a longer duration of diabetes (P = 0.008). CONCLUSION: The CGMS can be used for objective detection of patients with HUN.

Reverse Epidemiology of Traditional Cardiovascular Risk Factors in the Geriatric Population.

Traditional risk factors of cardiovascular death in the general population, including body mass index (BMI), serum cholesterol, and blood pressure (BP), are also found to relate to outcomes in the geriatric population, but in an opposite direction. Some degrees of elevated BMI, serum cholesterols, and BP are reportedly associated with lower, instead of higher, risk of death among the elderly. This phenomenon is termed "reverse epidemiology" or "risk factor paradox" (such as obesity paradox) and is also observed in a variety of chronic disease states such as end-stage renal disease requiring dialysis, chronic heart failure, rheumatoid arthritis, and AIDS. Several possible causes are hypothesized to explain this risk factor reversal: competing short-term and long-term killers, improved hemodynamic stability in the obese, adipokine protection against tumor necrosis factor-α, lipoprotein protection against endotoxins, and lipophilic toxin sequestration by the adipose tissue. It is possible that the current thresholds for intervention and goal levels for such traditional risk factors as BMI, serum cholesterol, and BP derived based on younger populations do not apply to the elderly, and that new levels for such risk factors should be developed for the elderly population. Reverse epidemiology of conventional cardiovascular risk factors may have a bearing on the management of the geriatric population, thus it deserves further attention.

Combination therapy for the treatment of dyslipidemia.

Statins have been proven to reduce cardiovascular risk, and guidelines for cardiovascular prevention recommend statin therapy in a wide range of patients. However, in spite of the dramatic success in large randomized clinical trials, two thirds of patients administered statins are not protected against cardiovascular events. This has prompted a search for additional targets for therapy. The pandemic of metabolic syndrome and type 2 diabetes has led to a dramatic increase in the prevalence of dyslipidemia. This, in turn, has prompted a resurgence of the search for drugs and algorithms that favorably affect high-density lipoprotein (HDL) and very low-density lipoprotein (VLDL) metabolism and function. Fibrates are the best-studied class of agents to be used as an addition to statins since they have also been proven to reduce clinical events as a monotherapy. However, there is a need for large safety trials of statin-fibrate combination therapy. Statin-niacin combination therapy has proven to be safe and effective in altering lipoprotein pattern. Randomized clinical trials and more research on the mechanism of action of niacin are necessary. Inhibitors of cholesterol ester transfer protein and HDL therapy drugs are in early developmental stages, and are the most promising potential additions to the current arsenal.

Associations between inflammatory markers, traditional risk factors, and complications in patients with type 2 diabetes mellitus.

OBJECTIVE: Inflammatory markers predict cardiovascular events in a wide range of patients. Two factors, fibrinogen (FIB) and high-sensitivity C reactive protein (CRP), are currently entering clinical practice as cardiovascular risk predictors. In patients with type 2 diabetes mellitus, we sought to examine the relationship between macrovascular disease, urinary albumin/creatinine ratio (ACR), and FIB or CRP, as well as the relationship of FIB and CRP with traditional risk predictors of these complications of diabetes. METHODS: In 202 consecutive patients with type 2 diabetes mellitus from a diabetes clinic, clinical and biochemical data were obtained and a cross-sectional analysis was performed. RESULTS: Patients with macrovascular disease had higher FIB (P=.02) but not higher CRP. They were older, more likely to have retinopathy or elevated serum creatinine, had higher ACR and lower HDL cholesterol. They were more likely to be treated with statins, beta-blockers, and ASA. Adjustment for statin therapy did not result in significant differences in CRP levels according to macrovascular disease status. Both FIB (P=.01) and CRP (P=.02) were significantly higher in patients with ACR whose values were in the proteinuria range. In multivariate analysis, both FIB (P=.001) and CRP (P=.03) were positively correlated with ACR, but no association was seen between CRP and ACR when FIB was entered in the model. Other factors positively associated with ACR were age, diastolic blood pressure, retinopathy, and hemoglobin A1c (HbA1c). FIB and CRP were strongly correlated (R=.49, P< or =.001) and this effect was independent of statin therapy. CRP was positively associated with body mass index (BMI), serum triglycerides, and sulfonylurea therapy and negatively associated with metformin therapy. Patients on statin therapy had significantly higher FIB and lower CRP. Women on hormone replacement therapy (HRT) had significantly lower FIB and higher CRP. CONCLUSIONS: In patients with diabetes: (1) the two markers, FIB and CRP, are interrelated; (2) FIB is significantly associated with presence of microvascular disease, independent of CRP; (3) CRP is strongly associated with metabolic factors but not with complications of diabetes, independently of FIB; (4) statins and HRT were divergently associated with CRP and FIB as HRT was associated with lower FIB and higher CRP, while statins showed the reverse association; and (5) CRP and FIB provide different information about the characteristics and consequences of diabetes mellitus because of divergent associations with biological indicators and therapeutic agents.

Metabolic syndrome and other factors associated with increased risk of diabetes.

The prevalence of diabetes has increased dramatically in the last 3 decades. Metabolic syndrome is a strong risk factor for incident diabetes. Among components of metabolic syndrome, obesity and abnormal carbohydrate metabolism are the most significant predictors. Primary care physicians should identify patients at risk and monitor their fasting glucose and/or postprandial glucose to enable timely diagnosis of diabetes and appropriate interventions. Lifestyle interventions that help reduce body weight and pharmacologic interventions that address insulin resistance and/or postprandial glycemia may help prevent diabetes. Intensive cardiovascular risk factor management should be an integral component of any diabetes prevention plan.

Optimizing diabetes management through glucose profiling: a case-based approach.

It is well documented that tight glucose control prevents the microvascular complications of diabetes, and many studies suggest that postprandial hyperglycemia may be associated with macrovascular complications. Maintaining target glucose values is challenging, as therapies are often not targeted to individual glucose excursion patterns. Postprandial SMBG values may be more tightly correlated to HbA1c than are fasting values. Studies of patients with pregnancies complicated by diabetes demonstrate that using SMBG around meals significantly improves glucose control and pregnancy outcomes. Adopting this model in type 2 diabetes may help achieve better glycemic control.

Enhancing parameter precision and the minimal modeling approach in type I diabetes.

An evaluation of a simple model including external perturbations was evaluated for its usefulness in predicting diabetic patients' behavior. The model proposed has been derived from Cobelli and Marl's comprehensive model and is structurally identifiable. The optimization was carried out on data gathered using CGMS (Medtronic MiniMed) on 3 subjects. The model was also optimized after performing a model-based signal enhancement. The results obtained before and after signal enhancement showed a promising reduction in the variation coefficient of the estimated parameters. This reduction is expected to be useful in the design of a closed loop controller for subcutaneous insulin delivery.