Low-density Lipoprotein Cholesterol Measurement Research Articles

Comparison of Different estimated Formulas with Direct Estimation of Low-density Lipoprotein Cholesterol

ABSTRACT Introduction Recent recommendations of the Adult Treatment Panel and the Adolescents Treatment Panel of the National Cholesterol Education Program make the low-density lipoprotein cholesterol (LDL-C) levels in serum the basis of classification and management of hypercholesterolemia. This makes accurate reporting of LDL-C decisive in the management of coronary heart disease (CHD). Direct measurement of LDL by homogeneous method is accurate but reagent is costly. Therefore, we have to compare different calculated LDL values with direct LDL (D-LDL) values. Aim The aim of this study was (1) to decide if LDL-C level was underestimated/overestimated after it was calculated using the formulae compared with direct measurement of LDL-C and (2) to choose the best calculated method that compares maximum with the direct method. Materials and methods We measured total cholesterol (TC), triglycerides (TG), high-density lipoprotein (HDL), D-LDL by direct homogeneous method in 500 fasting samples. Simultaneously, Friedewald's (F-LDL-C), modified Friedewald's (MF-LDL-C), and Anandaraja's (A-LDL-C) formulas were also used for calculation of LDL-C. Results A good correlation was found between D-LDL-C as compared with F-LDL-C, MF-LDL-C, and A-LDL-C. Pearson's coefficient of correlation between MF-LDL-C and D-LDL-C was 0.94, which was moderately higher than other calculated methods. Pearson's coefficient of correlation between A-LDL-C and D-LDL-C was 0.92 and F-LDL-C and D-LDL was 0.93. Conclusion In conclusion, among the three LDL-C formulas, the Friedewald formula and Anandaraja' s formulas give a higher percentage of error compared with the modified Friedewald formula Therefore, modified Friedewald's formula is better than the other two formulae for calculating LDL-C in a more cost-effective manner and can be used in large population studies. How to cite this article Kanani DN, Mishra A. Comparison of Different Estimated Formulas with Direct Estimation of Low-density Lipoprotein Cholesterol. Indian J Med Biochem 2017;21(2):151-156.

Hematologic, Plasma Biochemical, and Lipid Panel Reference Intervals in Orange-winged Amazon Parrots ( Amazona amazonica ).

To establish reference intervals in orange-winged Amazon parrots ( Amazona amazonica ) for the complete blood count, plasma biochemical values, and lipid panel and to evaluate age- and sex-related variations, blood samples were obtained from 29 healthy juvenile and adult parrots. Concentrations of total protein, bile acids, phosphorus, total cholesterol, low-density-lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol were significantly higher in adult compared with juvenile birds, while uric acid concentration was significantly higher in juveniles. The white blood cell count, lymphocyte count, and phosphorus and potassium concentrations were significantly higher in females, while chloride concentration was significantly higher in males. In this species, direct measurement of LDL-C resulted in lower concentrations than LDL-C calculated with the Friedewald formula. Assessment of the agreement between the calculated and measured LDL-C concentrations indicated a systematic bias of 19.1 mg/dL and a proportional bias of 1.07. A correction factor of -19 mg/L could be applied to the Friedewald formula, to obtain a result closer to the measured LDL-C, providing clinically acceptable (<20% difference) agreement in 66% of the samples. Triglyceride concentrations within the range measured in healthy birds of the present study did not significantly affect the bias between calculated and directly measured LDL-C. Further studies are needed to investigate the impact of nutritional factors, genetics, and exercise on biochemistry and lipoprotein panel analytes in orange-winged Amazon parrots.

A consensus statement on lipid management after acute coronary syndrome.

In patients admitted for acute coronary syndrome (ACS), the guidelines of the European Society of Cardiology give a Class I, Level A recommendation for the prescription of high-intensity statins to be initiated as early as possible, regardless of the low-density lipoprotein cholesterol (LDL-C) level. Although statins are widely prescribed after ACS, the intensity of therapy and the proportion of patients achieving target LDL-C values are often not in line with recommendations due to a lack of compliance with guidelines by the physicians, a lack of compliance with treatment or poor tolerance by patients, and poor dose adaptation. In this context, a group of French physicians came together to define strategies to facilitate and improve the management of lipid-lowering therapy after ACS. This paper outlines the scientific rationale for the use of statins at the acute phase of ACS, the utility of ezetimibe, the measurement of LDL-C during the course of ACS, the opportunities for detecting familial hypercholesterolaemia and the results of the consensus for the management of lipid-lowering therapy, illustrated in two decision-making algorithms.

Relation of Variability of Low-Density Lipoprotein Cholesterol and Blood Pressure to Events in Patients With Previous Myocardial Infarction from the IDEAL Trial

In patients with previous myocardial infarction (MI), aggressive hypertension control and low-density lipoprotein cholesterol (LDL-C) reduction are important secondary prevention measures. However, residual risk remains despite aggressive treatment. Whether variability in blood pressure (BP) and LDL-C can explain this residual risk is not known. Patients enrolled in the Incremental Decrease in End Points Through Aggressive Lipid-Lowering trial with at least 1 post-baseline measurement of LDL-C and blood pressure (BP) were included. Visit-to-visit LDL-C and BP variabilities were evaluated using various measures of variability. Primary outcome was any coronary event with the secondary outcomes of any cardiovascular event (CV), MI, stroke, death, and CV death. Among the 8,658 patients included, each 1-SD (10.8mg/dl) increase in LDL-C variability increased the risk of any coronary event (adjusted HR [HRadj] 1.07; 95% CI 1.04 to 1.11; p <0.0001), any CV event, MI, and death (HRadj 1.19; 95% CI 1.14 to 1.25; p <0.0001). Similarly, each 1-SD (7.2mm Hg) increase in systolic BP variability increased the risk of any coronary event (HRadj 1.15; 95% CI 1.10 to 1.20; p <0.0001), any CV event, MI, stroke, death (HRadj 1.28; 95% CI 1.18 to 1.38; p <0.0001), and CV death. Compared with the group with low variability for both LDL-C and systolic BP, the group with high variability for both had a significant increase in any coronary event (HRadj 1.48; 95% CI 1.30 to 1.70), any CV event (HRadj 1.43; 95% CI 1.27 to 1.61), and MI (HRadj 1.87; 95% CI 1.46 to 2.41). In conclusions, in patients with a history of MI, variabilities in LDL-C and BP are powerful and independent predictors of CV events including death.

Characterization and cholesterol management in patients with cardiovascular events and/or type 2 diabetes in the Netherlands

Objective: To describe clinical characteristics and cholesterol management of patients with cardiovascular events (CVEs) and/or type 2 diabetes mellitus (T2DM) with high low-density lipoprotein cholesterol (LDL-C) > 1.8 mmol/L in the Netherlands.Research design and methods: From the PHARMO Database Network a cross-sectional cohort was constructed. The descriptive study included patients on lipid modifying therapy (LMT) in 2009, classified as high cardiovascular risk based on a history of T2DM or CVE, with 2010 LDL-C levels above 1.8 mmol/L (2011 European Society of Cardiology [ESC] target). Sub-cohorts were created: T2DM + CVE from the T2DM cohort and multiple CVE from the CVE only cohort.Main outcome measures: Clinical characteristics and drug treatment were determined at the time of the last LDL-C measurement in 2010.Results: Of 10,864 very high risk patients, 66% had T2DM, 37% of whom also had CVE. In the CVE only cohort (34%), 18% had multiple events. More regular check-ups skewed inclusion towards diabetes patients. T2DM vs. CVE cohort characteristics were: 53% vs. 63% male, 42% vs. 27% obese, 19% vs. 24% current smoker, 54% vs. 51% systolic blood pressure <140 mmHg, with similar proportions in the sub-cohorts. Proportions reaching the Dutch guideline LDL-C target of <2.5 mmol/L were 56% (T2DM), 57% (T2DM + CVE), 48% (CVE only) and 53% (multiple CVE only). Frequencies of high intensity dose statin (simvastatin ≥80 mg, atorvastatin ≥40 mg or rosuvastatin ≥20 mg) were 6% (T2DM), 9% (T2DM + CVE, CVE only) and 14% (multiple CVE only); 1–2% received additional ezetimibe and 3–5% received non-statin LMT only, including ezetimibe.Conclusion: Despite LMT, >40% of the patients above ESC target also failed to reach the less stringent Dutch target, even in the higher risk groups. Therefore, management of hypercholesterolemia after CVE or T2DM should be optimized to improve cardiovascular outcomes. There is substantial room for improving other cardiovascular risk factors.

Obstructive sleep apnea is associated with visit-to-visit variability in low-density lipoprotein-cholesterol in patients with coronary artery disease.

Visit-to-visit variability in low-density lipoprotein-cholesterol (LDL-C) was found to be a novel predictor of adverse cardiac events. Obstructive sleep apnea (OSA), an emerging cardiovascular risk factor, is characterized by sympathetic activation and increased oxidative stress which are regulators of LDL-C metabolism. We hypothesized that OSA was associated with LDL-C variability. We prospectively recruited 190 patients with coronary artery disease for an overnight sleep study. Statin was prescribed upon discharge for 186 patients. Serum LDL-C levels were measured at clinic every 3 to 6months. Severity of OSA (on the basis of apnea-hypopnea index (AHI)) was correlated with visit-to-visit LDL-C variability (on the basis of variation independent of mean (VIM)) in outpatient clinic. The mean AHI was 21.9 ± 18.9. Using an AHI cut-off of 5-14.9, 15-29.9, and ≥30, the prevalence of mild, moderate, and severe OSA was 26.3, 18.9, and 27.4%, respectively. After 53.2 ± 25.3months, LDL-C was recorded over 8.1 ± 4.2 measurements. VIM positively correlated with AHI (Pearson's r = 0.183, p = 0.016), but not body mass index, baseline and mean follow-up LDL-C levels, and number of LDL-C measurements. In multiple linear regression analysis, AHI remained an independent predictor of VIM after adjusting for diabetes mellitus and hyperlipidemia. A 10-unit rise in AHI led to a 3.8% increase in VIM (95% CI 0.1 to 7.4%; p = 0.044). This is the first study to show the independent correlation between OSA severity and visit-to-visit LDL-C variability. Our finding contributes to the understanding of the vasculopathic effects of OSA.

Abstract 1771: Metabolic dysregulation and cancer mortality in a national cohort of African-Americans and whites

Abstract Introduction: Complex biological pathways link metabolic dysregulation (obesity, hypertension, dyslipidemia and diabetes) with cancer tumorigenesis, progression and metastasis, and those include higher circulating insulin, chronic inflammation, and increased visceral fat stores and estrogen. In this study, we examine the association between metabolic dysregulation and cancer mortality in a racially diverse cohort of adults. Methods: A total of 25,038 African-American and White adults recruited through the prospective Reason for Geographic and Racial Disparities in Stroke (REGARDS) study were included in this study. Socio-demographics, medical history, and biomarkers (including blood pressure, fasting blood glucose, C-reactive protein, HDL and LDL cholesterol, height, weight, waist and hip measurements) were assessed at baseline. Metabolic dysregulation was defined in two ways: 1) based on Alberti et al. (2009) criteria of at least three of: high blood pressure, elevated triglycerides, reduced HDL cholesterol, elevated fasting blood glucose and high BMI; and 2) factor analysis of 15 variables indicative of metabolic abnormalities, including BMI, diabetes, triglycerides, total cholesterol, diastolic and systolic blood pressure, and fasting blood glucose. Cox proportional hazards regression analysis was used to model the hazards of cancer mortality in relation to each individual component as well as the cluster of metabolic dysregulation. Results: About 51% of African-American females, 38% of African-American males, 38% of White females and 40% of White males met the joint criteria for metabolic dysregulation. White females in the highest quartile of the factor associated with high fasting blood glucose and diabetes experienced a 2-fold increase in cancer mortality (HR: 2.02, 95% CI: 1.27 - 3.20) compared to those in the lowest quartile. In crude analysis, elevated HDL cholesterol (HR: 1.16, 95% CI: 1.02 - 1.31), elevated blood pressure (HR: 1.33, 95% CI: 1.15 - 1.54), and elevated fasting blood glucose (HR: 1.23, 95% CI: 1.09 - 1.40) were each associated with higher mortality, although these associations were attenuated after adjusting for gender, race, age, and SES. However, in the fully adjusted model, having at least three of the five metabolic dysregulation components was associated with a 46-61% increased hazard of cancer-related death compared with having none (HR for 5 components: 1.61, 95% CI: 1.02 - 2.55). Conclusion: There are marked racial differences in the prevalence of metabolic dysregulation, and the strong association with cancer mortality suggests that this may be a major factor in the observed and persistent disparities in cancer mortality. Metabolic abnormalities are highly modifiable through lifestyle changes and medication; appropriate prevention strategies have significant potential to reduce the risk of tumor metastasis, recurrence and death. Citation Format: Tomi Akinyemiju, Justin X. Moore, Suzanne Judd, Monika Safford, Maria Pisu. Metabolic dysregulation and cancer mortality in a national cohort of African-Americans and whites. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 1771.

Clinical Significance of Low Density Lipoprotein Cholesterol Measurements: Direct Versus Indirect Method

Introduction: Estimation of low density lipoprotein cholesterol (LDL-C) is crucial in management of coronary artery disease patients. The management of dyslipidemia is largely based on the concentration of LDL-C. The objective of this study was to compare direct measurement of LDL-C determined by a homogenous method with LDL-C estimation done by Friedewald formula (FF) in heterogeneous populations. Methods: In this cross sectional study, we measured LDL-C by homogenous method (D-LDL-C) in 1,000 fasting samples &amp; compared with FF (F–LDL-C) used for calculation of LDL-C. The measurements of total cholesterol (TC) and triglycerides (TG) were performed using traditional enzymatic methods. The measurements of high density lipoprotein cholesterol (HDL-C) and LDL-C were performed using direct methods with precipitation, and the estimation of the LDL-C fraction was calculated using the FF. Results: Correlation analysis shows that the two methods had significant correlation (p&lt;0.0001). However the FF had positive bias in regard to direct method with TG levels ≤150 mg/dL. No bias was observed between the methods for TG levels from 151-200 mg/dL &amp; from 201-300 mg/dL. Whereas, TG levels from 301-400 mg/dL shows negative bias by FF. Conclusion: The Friedewald’s formula does not shows homogenous performance for estimating LDL-C levels in samples with different TG levels as compared with that of direct method.

Diagnostic Yield and Clinical Utility of Sequencing Familial Hypercholesterolemia Genes in Patients With Severe Hypercholesterolemia

BackgroundApproximately 7% of American adults have severe hypercholesterolemia (untreated low-density lipoprotein [LDL] cholesterol ≥190 mg/dl), which may be due to familial hypercholesterolemia (FH). Lifelong LDL cholesterol elevations in FH mutation carriers may confer coronary artery disease (CAD) risk beyond that captured by a single LDL cholesterol measurement. ObjectivesThis study assessed the prevalence of an FH mutation among those with severe hypercholesterolemia and determined whether CAD risk varies according to mutation status beyond the observed LDL cholesterol level. MethodsThree genes causative for FH (LDLR, APOB, and PCSK9) were sequenced in 26,025 participants from 7 case-control studies (5,540 CAD case subjects, 8,577 CAD-free control subjects) and 5 prospective cohort studies (11,908 participants). FH mutations included loss-of-function variants in LDLR, missense mutations in LDLR predicted to be damaging, and variants linked to FH in ClinVar, a clinical genetics database. ResultsAmong 20,485 CAD-free control and prospective cohort participants, 1,386 (6.7%) had LDL cholesterol ≥190 mg/dl; of these, only 24 (1.7%) carried an FH mutation. Within any stratum of observed LDL cholesterol, risk of CAD was higher among FH mutation carriers than noncarriers. Compared with a reference group with LDL cholesterol <130 mg/dl and no mutation, participants with LDL cholesterol ≥190 mg/dl and no FH mutation had a 6-fold higher risk for CAD (odds ratio: 6.0; 95% confidence interval: 5.2 to 6.9), whereas those with both LDL cholesterol ≥190 mg/dl and an FH mutation demonstrated a 22-fold increased risk (odds ratio: 22.3; 95% confidence interval: 10.7 to 53.2). In an analysis of participants with serial lipid measurements over many years, FH mutation carriers had higher cumulative exposure to LDL cholesterol than noncarriers. ConclusionsAmong participants with LDL cholesterol ≥190 mg/dl, gene sequencing identified an FH mutation in <2%. However, for any observed LDL cholesterol, FH mutation carriers had substantially increased risk for CAD.

Increased Remnant Cholesterol Explains Part of Residual Risk of All-Cause Mortality in 5414 Patients with Ischemic Heart Disease.

Increased concentrations of remnant cholesterol are causally associated with increased risk of ischemic heart disease. We tested the hypothesis that increased remnant cholesterol is a risk factor for all-cause mortality in patients with ischemic heart disease. We included 5414 Danish patients diagnosed with ischemic heart disease. Patients on statins were not excluded. Calculated remnant cholesterol was nonfasting total cholesterol minus LDL and HDL cholesterol. During 35836 person-years of follow-up, 1319 patients died. We examined both calculated and directly measured remnant cholesterol; importantly, however, measured remnant cholesterol made up only 9% of calculated remnant cholesterol at nonfasting triglyceride concentrations <1 mmol/L (89 mg/dL) and only 43% at triglycerides >5 mmol/L (443 mg/dL). Multivariable-adjusted hazard ratios for all-cause mortality compared with patients with calculated remnant cholesterol concentrations in the 0 to 60th percentiles were 1.2 (95% CI, 1.1-1.4) for patients in the 61st to 80th percentiles, 1.3 (1.1-1.5) for the 81st to 90th percentiles, 1.5 (1.1-1.8) for the 91st to 95th percentiles, and 1.6 (1.2-2.0) for patients in the 96th to 100th percentiles (trend, P < 0.001). Corresponding values for measured remnant cholesterol were 1.0 (0.8-1.1), 1.2 (1.0-1.4), 1.1 (0.9-1.5), and 1.3 (1.1-1.7) (trend, P = 0.006), and for measured LDL cholesterol 1.0 (0.9-1.1), 1.0 (0.8-1.2), 1.0 (0.8-1.3), and 1.1 (0.8-1.4) (trend, P = 0.88). Cumulative survival was reduced in patients with calculated remnant cholesterol ≥1 mmol/L (39 mg/dL) vs <1 mmol/L [log-rank, P = 9 × 10(-6); hazard ratio 1.3 (1.2-1.5)], but not in patients with measured LDL cholesterol ≥3 mmol/L (116 mg/dL) vs <3 mmol/L [P = 0.76; hazard ratio 1.0 (0.9-1.1)]. Increased concentrations of both calculated and measured remnant cholesterol were associated with increased all-cause mortality in patients with ischemic heart disease, which was not the case for increased concentrations of measured LDL cholesterol. This suggests that increased concentrations of remnant cholesterol explain part of the residual risk of all-cause mortality in patients with ischemic heart disease.

How are metabolic control targets of patients with Type 1 diabetes mellitus achieved in daily practice in the area with high diabetes prevalence?

AimsWe assessed the prevalence of Type 1 diabetes mellitus and determined how the targets established in the guidelines for patients with Type 1 diabetes mellitus were achieved in clinical practice in North Karelia, Finland. MethodsAll adult Type 1 diabetes mellitus patients (n=1075) were identified from the regional electronic patient database. The data for HbA1c and LDL cholesterol measurements during the years 2013 and 2014 were obtained from medical records. ResultsThe prevalence of Type 1 diabetes mellitus in the adult population in North Karelia was 0.8%, which is among the highest worldwide. HbA1c and LDL cholesterol were measured in 93% and 90% of participants, respectively. Nineteen percent of patients reached the HbA1c target of <7.0% (53mmol/mol) and 45% attained LDL cholesterol <2.5mmol/l. Overall, 26% of patients over 60 years old with diabetes achieved glycaemic control targets compared with 13–16% of younger patients with diabetes. ConclusionsGlycaemic control was in line with the recommendations in only one-fifth of Type 1 diabetes mellitus patients and less than half of them had LDL cholesterol levels within the target range. Interestingly, older Type 1 diabetes mellitus patients met the glycaemic control target more often than younger patients with diabetes. The targets established for patients with Type 1 diabetes mellitus are not achieved satisfactorily in daily practice.

Effects of Small Dense LDL in Diabetic Nephropathy in Females with Type 2 Diabetes Mellitus

Objective: This study investigated the association between small-dense low-density lipoprotein (sdLDL) and diabetic nephropathy (DN) in type 2 diabetic patients. Methods: A total of 172 type 2 diabetic patients (95 men and 77 women) who had not taken lipid-lowering agents were enrolled in this study. Measured LDL cholesterol fractionates into seven parts (LDL1 through 7) according to the size and the extent of charge. Using this system, we analyzed mean LDL particle size and the proportion of sdLDL (the percent of LDL3 through 7 over whole LDL). DN was defined as the albumin-to-creatinine ratio (ACR) ≥30 mg/g after excluding other causes of proteinuria. Results: The mean LDL cholesterol, LDL cholesterol size, proportion of sdLDL and ACR did not differ significantly between males and females. The presence of DN was negatively correlated with mean LDL size (r=-0.33, p value=0.02) and positively correlated with the proportion of sdLDL (r=0.34, p value=0.01) in females but not in males. After adjusting for other confounding factors related to DN, mean LDL size and proportion of sdLDL remained independent risk factors for DN in females [for mean LDL size, Odds ratio (OR)=0.86, 95% Confidence interval (CI)=0.77-0.96, p=0.01; for proportion of sdLDL, OR=1.07, 95% CI: 1.10-1.12, p=0.01], but not in males. Conclusion: sdLDL is closely related to DN in female type 2 diabetic patients. Further studies are necessary to clarify the association of sdLDL and DN with gender. (J Lipid Atheroscler 2016 June;5(1):11-19)

Method of LDL cholesterol measurement influences classification of LDL cholesterol treatment goals: clinical research study.

Low-density lipoprotein cholesterol (LDL-C) has been clearly associated with the risk of developing coronary heart disease. The best and most convenient method for determining LDL-C has come under increased scrutiny in recent years. We present comparisons of the Friedewald calculated LDL-C (C-LDL-C) and direct LDL-C (D-LDL-C) using 3 different homogenous assays. This highlights differences between the 2 methods of LDL-C measurement and how this affects the classification of samples into different LDL-C treatment goals as determined by the National Cholesterol Education Program Adult Treatment Panel III guidelines thus potentially affecting treatment strategies. Lipid profiles of a total of 2208 clinic patients were retrieved from the Central Arkansas VA Healthcare System clinical laboratory database. Samples studied were of 1-week period during the 3 periods studied: 2000 (period 1), 2002 (period 2), and 2005 (period 3). Different homogenous assays for D-LDL-C measurement were used for each of the 3 periods. There is a fundamental disagreement between D-LDL-C and C-LDL-C, although Pearson correlation coefficients are 0.93, 0.97, and 0.98 for periods 1, 2, and 3, respectively. Using the model for period 1, when C-LDL-C is 70 mg/dL, the predicted D-LDL-C is 95 mg/dL (36% higher). The differences between C-LDL-C and predicted D-LDL-C progressively decrease at higher LDL-C cut points. In the assay used in period 3, there are 290 samples with D-LDL-C values between 100 and 130 mg/dL. Of these, only 182 samples show agreement with C-LDL-C values, whereas 90 samples with a D-LDL-C in the 100- to 130-mg/dL range are in the 70- to 100-mg/dL range using the C-LDL-C assay. Although the κ statistics suggests the LDL-C measures have relatively high levels of agreement, the significant generalized McNemar tests (P < 0.01) provide additional evidence of disagreement between C-LDL-C and D-LDL-C during all the 3 periods. Our results highlight D-LDL-C measurements using 3 different assays during 3 different periods. In all assays, there is a substantial lack of agreement between D-LDL-C and C-LDL-C, which, in most cases, resulted in higher D-LDL-C values than C-LDL-C. This leads to clinically significant misclassification of patient's LDL-C to a different LDL-C treatment goal, which would potentially result in more drug usage, thus exposing patients to more potential adverse effects and at a much greater cost with little evidence of benefit.

Abstract 17184: Achievement Of LDL-cholesterol Reduction Targets is Associated With Reduced Cardiovascular Disease Risk Among Patients With Familial Hypercholesterolemia in a Large Electronic Medical Record Database

Introduction: Heterozygous familial hypercholesterolemia (FH) is common but under-recognized, with an estimated prevalence of 1:200-1:500 and an associated high risk of premature cardiovascular disease (CVD). Little is known regarding the association between change in low-density lipoprotein cholesterol (LDL-C) and long-term CVD risk in FH patients. We hypothesized that FH patients who achieved LDL-C &lt; 100 mg/dL or reduction ≥50% post-statin initiation would have reduced risk of non-fatal myocardial infarction (MI) or revascularization. Methods: Using Dutch Lipid Network criteria components, 174 “probable” and 125 “definite” FH patients with LDL-C measurements available before and after statin initiation were identified in the Vanderbilt de-identified electronic medical records (EMR) Synthetic Derivative database, 1996-2014. First non-fatal MI or revascularization was identified via validated EMR algorithm with positive predictive value=92%. Hazard ratios (HR) and 95% confidence intervals (CI) were obtained from Cox regression models in relation to LDL-C levels (≥ vs. &lt;50% reduction or &lt; vs. &gt;100 mg/dL post-statin), adjusted for age, race, sex, blood pressure, smoking, and body mass index. Results: Mean (+/- SD) LDL-C levels prior to initiation of statin therapy were 207 (+/- 31) for probable and 304 (+/- 124) mg/dL for definite FH patients. Similar proportions of patients attained ≥50% reduction in LDL-C after statin initiation in both groups (24.1% and 26.4%), while 22.4% achieved LDL-C &lt; 100 mg/dL in the probable group compared to only 4.8% in the definite group. Over median follow-up of 5.4 years, 34 probable and 19 definite FH patients experienced non-fatal MI or revascularization. The HR (95% CI) among those with post-statin LDL-C &lt; 100 vs &gt;100 mg/dL was 0.59 (0.23-1.52) overall, with no evidence of effect modification by probable/definite FH status (likelihood ratio test (LRT) p-value=0.58). A similar pattern was observed for LDL-C change ≥50% vs &lt;50% (HR (95% CI) 0.58 (0.24-1.38), LRT p-value=0.44). Conclusions: In this small sample of FH patients, lowering LDL-C to &lt;100 mg/dL suggests a reduction in CVD risk, but few attained this LDL-C target. These results warrant further research in larger populations of this understudied condition.

Multiple Imputation: A Flexible Tool for Handling Missing Data.

In this issue of JAMA, Asch et al1 report results of a cluster-randomized clinical trial designed to evaluate the effects of physician financial incentives, patient incentives, or shared physician and patient incentives on low density lipoprotein cholesterol (LDL-C) levels among patients with high cardiovascular risk. Because 1 or more follow-up LDL-C measurements were missing for approximately 7% of participants, Asch et al used multiple imputation (MI) to analyze their data and concluded that shared financial incentives for physicians and patients, but not incentives to physicians or patients alone, resulted in the patients having lower LDL-C levels. Imputation is the process of replacing missing data with 1 or more specific values, to allow statistical analysis that includes all participants and not just those who do not have any missing data. Missing data are common in research. In a previous JAMA Guide to Statistics and Methods, Newgard and Lewis2 reviewed the causes of missing data. These are divided into 3 classes: 1) missing completely at random, the most restrictive assumption, indicating that whether a data point is missing is completely unrelated to observed and unobserved data; 2) missing at random, a more realistic assumption than missing completely at random, indicating whether a data point is missing can be explained by the observed data; or 3) missing not at random, meaning that the missingness is dependent on the unobserved values. Common statistical methods used for handling missing values were reviewed.2 When missing data occur, it is important to not exclude cases with missing information (analyses after such exclusion are known as complete case analyses). Single-value imputation methods are those that estimate what each missing value might have been and replace it with a single value in the data set. Single-value imputation methods include mean imputation, last observation carried forward, and random imputation. These approaches can yield biased results and are suboptimal. Multiple imputation better handles missing data by estimating and replacing missing values many times.

Prevalence of comorbidities and evaluation of their screening in spondyloarthritis: results of the international cross-sectional ASAS-COMOSPA study

BackgroundIncreased risk of some comorbidities has been reported in spondyloarthritis (SpA). Recommendations for detection/management of some of these comorbidities have been proposed, and it is known that a gap exists...

Nurse-Led, Telephone-Based, Secondary Preventive Follow-Up after Stroke or Transient Ischemic Attack Improves Blood Pressure and LDL Cholesterol: Results from the First 12 Months of the Randomized, Controlled NAILED Stroke Risk Factor Trial.

BackgroundEnhanced secondary preventive follow-up after stroke or transient ischemic attack (TIA) is necessary for improved adherence to recommendations regarding blood pressure (BP) and low-density lipoprotein cholesterol (LDL-C) levels. We investigated whether nurse-led, telephone-based follow-up was more efficient than usual care at improving BP and LDL-C levels at 12 months after hospital discharge.MethodsWe randomized 537 patients to either nurse-led, telephone-based follow-up (intervention) or usual care (control). BP and LDL-C measurements were performed at 1 month (baseline) and 12 months post-discharge. Intervention group patients who did not meet target values at baseline received additional follow-up, including titration of medication and lifestyle counselling, to reach treatment goals (BP < 140/90 mmHg, LDL-C < 2.5 mmol/L).ResultsAt 12 months, mean systolic BP, diastolic BP and LDL-C was 3.3 (95% CI 0.3 to 6.3) mmHg, 2.3 mmHg (95% CI 0.5 to 4.2) and 0.3 mmol/L (95% CI 0.1 to 0.4) lower in the intervention group compared to controls. Among participants with values above the treatment goal at baseline, the difference in systolic BP and LDL-C was more pronounced (8.0 mmHg, 95% CI 4.0 to 12.1, and 0.6 mmol/L, 95% CI 0.4 to 0.9). A larger proportion of the intervention group reached the treatment goal for systolic BP (68.5 vs. 56.8%, p = 0.008) and LDL-C (69.7% vs. 50.4%, p < 0.001).ConclusionsNurse-led, telephone-based secondary preventive follow-up, including medication adjustment, was significantly more efficient than usual care at improving BP and LDL-C levels by 12 months post-discharge.Trial RegistrationISRCTN Registry ISRCTN23868518

Statin Use, Incident Dementia and Alzheimer Disease in Elderly African Americans.

To investigate the association between statin use, incident dementia, and Alzheimer disease (AD) in a prospective elderly African American cohort. Two stage design with a screening interview followed by a comprehensive in-home assessment conducted over an eight-year period. Diagnoses of incident AD and dementia were made by consensus. Statin use was collected at each evaluation. Measurements of low-density lipoprotein cholesterol (LDL), C-reactive protein (CRP) and APOE genotype were obtained from baseline blood samples. Logistic regression models were used to test the association of statin use on incident dementia and AD and its possible association with lipid and CRP levels. Indianapolis, Indiana. From an original cohort of 2629 participants, a subsample of 974 African Americans aged >70 years with normal cognition, at least one follow up evaluation, complete statin information, and biomarker availability were included. Incident dementia and incident AD. After controlling for age at diagnosis, sex, education level, presence of the APOE ε4 allele and history of stroke for the incident dementia model, baseline use of statins was associated with a significantly decreased risk of incident dementia (OR=.44, P=.029) and incident AD (OR=.40, P=.029). The significant effect of statin use on reduced AD risk and trend for dementia risk was found only for those participants who reported consistent use over the observational period (incident AD: P=.034; incident dementia: P=.061). Additional models found no significant interaction between baseline statin use, baseline LDL, or CRP level and incident dementia/AD. Consistent use of statin medications during eight years of follow-up resulted in significantly reduced risk for incident AD and a trend toward reduced risk for incident dementia.

Difference in bias approach for commutability assessment: application to frozen pools of human serum measured by 8 direct methods for HDL and LDL cholesterol.

We used a difference in bias approach to evaluate the commutability of 4 frozen serum pools for 8 direct methods for measurement of HDL and LDL cholesterol (HDLC and LDLC). Freshly collected nonfrozen sera from 138 diseased and 37 nondiseased patients and 4 frozen pools from the CDC Lipid Standardization Program were measured by direct methods and by the beta-quantification reference measurement procedure of the CDC. We used an error components model to estimate the difference in the bias component of error plus its uncertainty for frozen pools vs patient samples between the direct method and the reference procedure. Frozen pools with bias differences less than a critical value determined by either medical requirements for bias or the random error components of the measurement procedures were considered commutable. On the basis of medical requirement criteria, 1 of the 4 frozen pools was commutable for most of the HDLC methods for both diseased and nondiseased patients, and none was commutable for LDLC methods. On the basis of random error criteria, all of the frozen pools were generally commutable for all of the HDLC methods for both diseased and nondiseased patients, and 1 of the 4 frozen pools was generally commutable for most of the LDLC methods for both diseased and nondiseased patients. Commutability was assessed as the closeness of agreement of the difference in bias between a reference material and a set of patient samples. Criteria for commutability could be based on fixed medical requirements for bias or on random error components.

Glycemic and Cholesterol Control Versus Single-Goal Control in US Veterans with Newly Diagnosed Type 2 Diabetes: A Retrospective Observational Study.

IntroductionA majority of patients with diabetes do not have levels of glycated hemoglobin (HbA1c) and low-density lipoprotein cholesterol (LDL-C) under control, either individually or in combination. The objective was to assess the clinical benefits and patient characteristics associated with dual-goal achievement [HbA1c <7% (53 mmol/mol) and LDL-C <100 mg/dL] versus only LDL-C goal achievement in adults with newly diagnosed type 2 diabetes.MethodsNewly diagnosed patients with ≥2 measures of LDL-C and HbA1c were identified in the South Central Veterans Affairs Health Care Network (01/2004–06/2010). The index date was the first HbA1c assessment within 3 months of the first type 2 diabetes diagnosis. Multivariate Cox proportional hazards models were used to assess the association between time-varying goal achievement and post-index microvascular and cardiovascular complications. Patient characteristics associated with dual-goal achievement in the 7–12 months post-index were identified using a logistic regression.ResultsThe sample included 16,829 patients. Compared with LDL-C goal achievement, dual-goal achievement was associated with lower risk of microvascular complications [hazard ratio (95% confidence interval): 0.69 (0.63, 0.76)]. Other outcomes did not differ between those two groups. Characteristics associated with dual-goal achievement (44.2% of patients) include prior dual-goal achievement, older age, and use of lipid-lowering drugs.ConclusionDual-goal achievement in newly diagnosed type 2 diabetes is associated with a lower risk of microvascular complications versus only LDL-C goal achievement. Although dual-goal achievement rates are suboptimal, early and regular intervention will increase its likelihood.FundingDaiichi Sankyo, Inc., Parsippany, NJ, USA.Electronic supplementary materialThe online version of this article (doi:10.1007/s13300-015-0122-2) contains supplementary material, which is available to authorized users.