Agreement Between Fasting and Postprandial LDL Cholesterol Measured with 3 Methods in Patients with Type 2 Diabetes Mellitus

Estimation of Low-Density Lipoprotein Cholesterol Concentration Using Machine Learning

OBJECTIVE

Low-density lipoprotein cholesterol (LDL-C) can be estimated using the Friedewald and Martin-Hopkins formulas. We developed LDL-C prediction models using multiple machine learning methods and investigated the validity of the new models along with the former formulas.

METHODS

Laboratory data (n = 59,415) on measured LDL-C, high-density lipoprotein cholesterol, triglycerides (TG), and total cholesterol were partitioned into training and test data sets. Linear regression, gradient-boosted trees, and artificial neural network (ANN) models were formed based on the training data. Paired-group comparisons were performed using a t-test and the Wilcoxon signed-rank test. We considered P values <.001 with an effect size >.2 to be statistically significant.

RESULTS

For TG ≥177 mg/dL, the Friedewald formula underestimated and the Martin-Hopkins formula overestimated the LDL-C (P <.001), which was more significant for LDL-C <70 mg/dL. The linear regression, gradient-boosted trees, and ANN models outperformed the aforementioned formulas for TG ≥177 mg/dL and LDL-C <70 mg/dL based on a comparison with a homogeneous assay (P >.001 vs. P <.001) and classification accuracy.

CONCLUSION

Linear regression, gradient-boosted trees, and ANN models offer more accurate alternatives to the aforementioned formulas, especially for TG 177 to 399 mg/dL and LDL-C <70 mg/dL.

High glucose load and endotoxemia among overweight and obese Arab women with and without diabetes: An observational study

Dietary intake influences gut microbiota activity. Nevertheless, there is a lack of evidence available that illustrates the acute effects of high glucose meal on metabolic endotoxemia. The present study assessed the acute impact of high glucose meal on endotoxemia and other clinical parameters in Saudi females with varying degrees of glycemia.The subjects were 64 consenting pre-menopausal women, grouped into 3: control [n = 14 lean, non-T2DM, BMI = 22.2 ± 2.2 kg/m]; overweight [n = 16, non-T2DM, BMI = 28.5 ± 1.5 kg/m] and T2DM [n = 34, BMI = 35.2 ± 7.7 kg/m]. After an overnight fast, all subjects were given a standardized high-glucose (75 g) meal. Anthropometrics were taken and blood samples were withdrawn at baseline and postprandial (0, 2 and 4-hours), serum glucose, endotoxin and lipid profile were quantified.At baseline, total cholesterol, LDL-cholesterol, triglycerides and serum glucose levels were significantly higher (P values <.01) whereas significantly lower HDL-cholesterol levels (P < .01) were observed in T2DM subjects compared to other groups. Baseline endotoxin levels were highest in the overweight group (3.2 ± 1.1 mmol/L) as compared to control (2.0 ± 0.5 mmol/L) and T2DM (2.7 ± 1.2 mmol/L) (P = .046). HDL-cholesterol, LDL-cholesterol and triglycerides, significantly decreased in the T2DM group after 2 hours (P values <.05), whereas unremarkable changes observed in other groups. Lastly, endotoxin levels significantly increased only in the overweight group (3.2 ± 1.1 vs 4.2 ± 1.4 mmol/L; P < .05), 4 hours postprandial.High glucose meal elevates endotoxemia only among overweight subjects and impairs dysbiosis.

Fasting-Evoked En Route Hypoglycemia in Diabetes (FEEHD): From Guidelines to Clinical Practice

BACKGROUND

Lipid profiles have been used for the purposes of health screening and monitoring of the effects of lipid-lowering medications, especially in patients with diabetes who are prone to hyperlipidemia. Fasting for lipid profiles has been the norm for the past decades. This long-lasting tradition poses a risk of hypoglycemia, especially in patients with diabetes.

OBJECTIVE

Our aim is to review the overlooked occurrence of hypoglycemia in patients who fast for laboratory tests, especially lipid profile tests, and commute to the laboratory facility while fasting; a condition we titled "Fasting-Evoked En route Hypoglycemia in Diabetes patients" or "FEEHD". We also review its prevalence and clinical impact on patients with diabetes.

METHODS

We undertook an extensive literature search using search engines such as PubMed and Google Scholar. We used the following keywords for the search: Fasting, Non-fasting; Hypoglycemia; Hypoglycemic Agents; Laboratory Tests; Glucose, Hypoglycemia, Lipid Profiles, FEEHD.

RESULTS

Our literature review has shown that the prevalence of FEEHD is alarmingly high (17-21% of patients at risk). This form of hypoglycemia is under recognized in the clinical practice despite its frequent occurrence. Recent changes in various international guidelines have uniformly endorsed the utilization of non-fasting lipid profiles as the new standard for obtaining lipid profiles with the exception of certain conditions. Multiple studies showed the efficacy of non-fasting lipid tests in comparison to fasting lipid tests, in routine clinical practice.

CONCLUSION

We hope to increase awareness among clinicians about this overlooked and potentially harmful form of hypoglycemia in patients with diabetes, which can be easily avoided. We also hope to call upon clinicians to consider changing the habit of ordering lipid profiles in the fasting state, which has been recently shown to be largely unnecessary in routine clinical settings, with few exceptions in selected cases.

Quantifying Atherogenic Lipoproteins: Current and Future Challenges in the Era of Personalized Medicine and Very Low Concentrations of LDL Cholesterol. A Consensus Statement from EAS and EFLM

BACKGROUND

The European Atherosclerosis Society-European Federation of Clinical Chemistry and Laboratory Medicine Consensus Panel aims to provide recommendations to optimize atherogenic lipoprotein quantification for cardiovascular risk management.

CONTENT

We critically examined LDL cholesterol, non-HDL cholesterol, apolipoprotein B (apoB), and LDL particle number assays based on key criteria for medical application of biomarkers. (a) Analytical performance: Discordant LDL cholesterol quantification occurs when LDL cholesterol is measured or calculated with different assays, especially in patients with hypertriglyceridemia >175 mg/dL (2 mmol/L) and low LDL cholesterol concentrations <70 mg/dL (1.8 mmol/L). Increased lipoprotein(a) should be excluded in patients not achieving LDL cholesterol goals with treatment. Non-HDL cholesterol includes the atherogenic risk component of remnant cholesterol and can be calculated in a standard nonfasting lipid panel without additional expense. ApoB more accurately reflects LDL particle number. (b) Clinical performance: LDL cholesterol, non-HDL cholesterol, and apoB are comparable predictors of cardiovascular events in prospective population studies and clinical trials; however, discordance analysis of the markers improves risk prediction by adding remnant cholesterol (included in non-HDL cholesterol) and LDL particle number (with apoB) risk components to LDL cholesterol testing. (c) Clinical and cost-effectiveness: There is no consistent evidence yet that non-HDL cholesterol-, apoB-, or LDL particle-targeted treatment reduces the number of cardiovascular events and healthcare-related costs than treatment targeted to LDL cholesterol.

SUMMARY

Follow-up of pre- and on-treatment (measured or calculated) LDL cholesterol concentration in a patient should ideally be performed with the same documented test method. Non-HDL cholesterol (or apoB) should be the secondary treatment target in patients with mild to moderate hypertriglyceridemia, in whom LDL cholesterol measurement or calculation is less accurate and often less predictive of cardiovascular risk. Laboratories should report non-HDL cholesterol in all standard lipid panels.

Update on the laboratory investigation of dyslipidemias

The role of the clinical laboratory is evolving to provide more information to clinicians to assess cardiovascular disease (CVD) risk and target therapy more effectively. Current routine methods to measure LDL-cholesterol (LDL-C), the Friedewald calculation, ultracentrifugation, electrophoresis and homogeneous direct methods have established limitations. Studies suggest that LDL and HDL size or particle concentration are alternative methods to predict future CVD risk. At this time there is no consensus role for lipoprotein particle or subclasses in CVD risk assessment. LDL and HDL particle concentration are measured by several methods, namely gradient gel electrophoresis, ultracentrifugation-vertical auto profile, nuclear magnetic resonance and ion mobility. It has been suggested that HDL functional assays may be better predictors of CVD risk. To assess the issue of lipoprotein subclasses/particles and HDL function as potential CVD risk markers robust, simple, validated analytical methods are required. In patients with small dense LDL particles, even a perfect measure of LDL-C will not reflect LDL particle concentration. Non-HDL-C is an alternative measurement and includes VLDL and CM remnant cholesterol and LDL-C. However, apolipoprotein B measurement may more accurately reflect LDL particle numbers. Non-fasting lipid measurements have many practical advantages. Defining thresholds for treatment with new measurements of CVD risk remain a challenge. In families with genetic variants, ApoCIII and lipoprotein (a) may be additional risk factors. Recognition of familial causes of dyslipidemias and diagnosis in childhood will result in early treatment. This review discusses the limitations in current laboratory technologies to predict CVD risk and reviews the evidence for emergent approaches using newer biomarkers in clinical practice.

Risk of misclassification with a non-fasting lipid profile in secondary cardiovascular prevention

AIMS

Routinely fasting is not necessary for measuring the lipid profile according to the latest European consensus. However, LDL-C tends to be lower in the non-fasting state with risk of misclassification. The extent of misclassification in secondary cardiovascular prevention with a non-fasting lipid profile was investigated.

METHODS AND RESULTS

329 patients on lipid lowering therapy for secondary cardiovascular prevention measured a fasting and non-fasting lipid profile. Cut-off values for LDL-C, non-HDL-C and apolipoprotein B were set at <1.8mmol/l, <2.6mmol/l and <0.8g/l, respectively. Study outcomes were net misclassification with non-fasting LDL-C (calculated using the Friedewald formula), direct LDL-C, non-HDL-C and apolipoprotein B. Net misclassification <10% was considered clinically irrelevant. Mean age was 68.3±8.5years and the majority were men (79%). Non-fasting measurements resulted in lower LDL-C (-0.2±0.4mmol/l, P<0.001), direct LDL-C (-0.1±0.2mmol/l, P=0.001), non-HDL-C (-0.1±0.4mmol/l, P=0.004) and apolipoprotein B (-0.02±0.10g/l, P=0.004). 36.0% of the patients reached a fasting LDL-C target of <1.8mmol/l with a significant net misclassification of 10.7% (95% CI 6.4-15.0%) in the non-fasting state. In the non-fasting state net misclassification with direct LDL-C was 5.7% (95% CI 2.1-9.2%), 4.0% (95% CI 1.0-7.4%) with non-HDL-C and 4.1% (95% CI 1.1-9.1%) with apolipoprotein B.

CONCLUSION

Use of non-fasting LDL-C as treatment target in secondary cardiovascular prevention resulted in significant misclassification with subsequent risk of undertreatment, whereas non-fasting direct LDL-C, non-HDL-C and apolipoprotein B are reliable parameters.

Postprandial decrease in LDL-cholesterol in men with metabolic syndrome

BACKGROUND

In some epidemiological studies, blood lipids are determined at non-fasting state, which may impact cardiovascular risk estimation. The aim of this study was to evaluate postprandial LDL-C changes in men with newly diagnosed metabolic syndrome (MetSy).

METHODS

36 male patients were examined: 12 men with and 24 men without MetSy. The fat tolerance test was performed before and after a three-month hypolipidemic treatment. Serum lipids were measured using routine methods, lipid peroxides (LPO) colorimetrically, apolipoproteins A-I, B, and hsCRP immunoturbidimetrically.

RESULTS

The postprandial increase in triglycerides was associated with a decrease in LDL-C and a small decrease in apo B. In men with MetSy, the mean change in LDL-C (-19.5 ± 2.3 mg/dl) was greater than in healthy men (-5.7 ± 3.8 mg/dl). All lipid changes (ΔTG, ΔLDL-C and ΔLPO) were linearly dependent on the postprandial non-LDL-cholesterol. After three months of hypolipidemic treatment, in all men with MetSy, the apoB/apoA-I ratio remained the same as before the therapy.

CONCLUSION

In men diagnosed with MetSy, postprandial decreases in LDL-cholesterol may cause underestimation of cardiovascular risk. After three months of hypolipidemic treatment, there was only a partial reduction in this risk, as the apoB/apoA-I ratio remained the same.

The traditions and risks of fasting for lipid profiles in patients with diabetes

Fasting overnight has been traditionally recommended by clinicians when ordering laboratory tests for lipid profiles for the purposes of health screening or monitoring of the effects of lipid-lowering medications. Patients with diabetes are tested for lipid profiles at least annually. This deeply rooted tradition of fasting for lipid testing has recently been challenged. Several studies have shown little benefit obtained by testing lipids in fasting compared with postprandial states. Furthermore, recent studies have shown the importance of postprandial lipid spikes in the pathogenesis of cardiovascular disease. At the same time, recent reports have alerted the medical community to the risk of hypoglycemia in patients with diabetes on antidiabetic medications (particularly insulin and sulfonylureas) who are asked to fast for lab tests. This article reviews the literature on these emerging issues in lipid testing in patients with diabetes, and offers recommendations for lipid testing in these patients in view of these emerging discussions.

LDL cholesterol: controversies and future therapeutic directions

Lifelong exposure to raised concentrations of LDL cholesterol increases cardiovascular event rates, and the use of statin therapy as an adjunct to diet, exercise, and smoking cessation has proven highly effective in reducing the population burden associated with hyperlipidaemia. Yet, despite consistent biological, genetic, and epidemiological data, and evidence from randomised trials, there is controversy among national guidelines and clinical practice with regard to LDL cholesterol, its measurement, the usefulness of population-based screening, the net benefit-to-risk ratio for different LDL-lowering drugs, the benefit of treatment targets, and whether aggressive lowering of LDL is safe. Several novel therapies have been introduced for the treatment of people with genetic defects that result in loss of function within the LDL receptor, a major determinant of inherited hyperlipidaemias. Moreover, the usefulness of monoclonal antibodies that extend the LDL-receptor lifecycle (and thus result in substantial lowering of LDL cholesterol below the levels achieved with statins alone) is being assessed in phase 3 trials that will enrol more than 60,000 at-risk patients worldwide. These trials represent an exceptionally rapid translation of genetic observations into clinical practice and will address core questions of how low LDL cholesterol can be safely reduced, whether the mechanism of LDL-cholesterol lowering matters, and whether ever more aggressive lipid-lowering provides a safe, long-term mechanism to prevent atherothrombotic complications.