Non-fasting Lipid Research Articles

Fetal phthalates and bisphenols and childhood lipid and glucose metabolism. A population-based prospective cohort study

Background and aimsFetal exposure to endocrine disruptors such as phthalates and bisphenols may lead to developmental metabolic adaptations. We examined associations of maternal phthalate and bisphenol urine concentrations during pregnancy with lipids, insulin, and glucose concentrations at school age. MethodsIn a population-based, prospective cohort study among 757 mother–child pairs, we measured maternal phthalate and bisphenol urine concentrations in first, second and third trimester of pregnancy. We measured non-fasting lipids, glucose and insulin blood concentrations of their children at a mean age of 9.7 (standard deviation 0.2) years. Analyses were performed for boys and girls separately. ResultsAn interquartile range (IQR) higher natural log transformed third trimester maternal urine phthalic acid concentration was associated with a 0.20 (95% confidence interval (CI) 0.07–0.34) standard deviation score (SDS) higher triglycerides concentration among boys. Maternal bisphenol urine concentrations were not associated with non-fasting lipid concentrations during childhood. An IQR higher natural log transformed second trimester maternal high molecular weight phthalates (HMWP) and di-2-ethylhexylphthalate (DEHP) urine concentration were associated with a 0.19 (95% CI 0.31–0.07) respectively 0.18 (95% CI 0.31–0.06) SDS lower glucose concentration among boys. An IQR higher natural log transformed third trimester maternal bisphenol F urine concentration was associated with a 0.22 (95% CI 0.35–0.09) SDS lower non-fasting insulin concentration among boys. ConclusionsOur results suggest potential persisting sex specific effects of fetal exposure to phthalates and bisphenols on childhood lipid concentrations and glucose metabolism. Future studies are needed for replication and exploring underlying mechanisms.

ASSOCIATION OF THE SERUM METABOLOMIC PROFILE BY NUCLEAR MAGNETIC RESONANCE SPECTROSCOPY WITH SPERM PARAMETERS: A CROSS SECTIONAL STUDY OF 325 MEN

Are 155 circulating metabolic measures relevant to lifestyle and metabolic health associated with sperm parameters (as measured by concentration, motility and total motile sperm count (TMSC))? An extensive range of metabolites were not associated with semen parameters, however, several metabolites exhibited differential direction of associations with the odds of a low TMSC and warrant replication. Robust identification of additional modifiable and non-modifiable risk factors for poor semen quality have had limited success. An alternative approach to identify risk factors for an abnormal semen analysis would be to examine circulating metabolites by means of a high throughput cost efficient NMR platform, which may provide insights into downstream factors as well as more upstream exposures. Cross-sectional study of 325 men prospectively recruited between 1 April 2017 and 31 March 2019. Men intending to undergo assisted conception at a University Hospital, had a detailed demographic, lifestyle, fertility and medical history and semen analysis. Non-fasting serum lipids, lipoprotein subclasses, and low-molecular weight metabolites (including amino acids, glycolysis and inflammatory markers) were quantified by NMR spectroscopy. Multivariable linear and logistic regression were used to examine the associations of serum metabolic profiles (exposures), with functional sperm concentration, motility and TMSC (outcomes) with adjustment for confounders. Participants were mean 37.2 (SD 5.7) years and had a median sperm concentration of 35 million/ml (IQR 15, 69 million/ml) and median motility of 53% (IQR 42,67). 76% of men had a TMSC >15 Million, 10% 5-15 Million and 14% <5 Million. In both univariate and confounder adjusted analyses an extensive range of lipids and lipoproteins, glycolysis related metabolites, amino acids, ketone bodies, creatinine or albumin, did not show strong statistical evidence of associated with sperm concentration, motility, or the odds of having a reduced or low TMSC (all PBonferroni > 0.0029). Sperm parameters were measured on a single sample, in accordance with recent WHO guidance, and by non-automated techniques which may have introduced random measurement error that could have attenuated to the null. This study provides preliminary data on a range of metabolic pathways and their association with semen parameters. The differential direction of associations with sperm motility and potentially of important clinical effect sizes warrant further exploration and replication in a larger prospective study.

Initial Clinical Experience with PCSK9 Inhibitors to Lower LDL Cholesterol in a University Lipid Clinic Setting

Proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors have demonstrated significant lowering of low-density lipoprotein (LDL) cholesterol in patients with atherosclerotic cardiovascular disease (ASCVD) and familial hypercholesterolemia (FH). We retrospectively reviewed data concerning use of PCSK9 inhibitors from patients in our university-based adult lipid clinic. Data collected included clinical pre-treatment variables and pre-and post-treatment non-fasting lipid profiles. Of 165 candidates, 163 were approved for PCSK9 inhibition (90% ASCVD and 10% FH). A majority of patients (72%) had statin intolerance. Treatment was provided and assessed in 141 patients. After three doses of medications, LDL cholesterol fell from 170 + 58 mg/dL to 76 + 45 mg/dL (55%, P&lt;0.001). There were no differences in efficacy according to sex, elevated lipoprotein(a), and the PCS-K9 inhibitor utilized. Continued efficacy was evaluated in 101 patients with LDL decreasing further from initial follow-up to long-term follow-up over an average of 14 months (74 ± 44 mg/dL to 68 ± 41 mg/dL). Permanent discontinuation of PCS-K9 inhibitor because of side effects occurred in 11% of patients. When strict adherence to guidelines was applied, &gt;95% approval rate was obtained, and there was similar efficacy in LDL lowering to what has been previously reported irrespective of statin intolerance.

To fast or not to fast: Lipid measurement and cardiovascular disease risk estimation in rural sub-Saharan Africa.

BackgroundCardiovascular disease (CVD) morbidity and mortality are increasing in sub-Saharan Africa (sSA), highlighting the need for tools to enable CVD risk stratification in the region. Although non-HDL-cholesterol (nHDL-C) has been promoted as a method to measure lipids without a requirement for fasting in the USA, its diagnostic validity has not been assessed in sSA. We sought to estimate: 1) the association between LDL-cholesterol (LDL-C) and nHDL-C, 2) the impact of fasting on their measurement, and 3) their correlation with carotid atherosclerosis, within a rural Ugandan population with high HIV prevalence.MethodsWe collected traditional CVD risk factors, blood for serum lipid levels, self-reported fasting status, and performed carotid ultrasonography in 301 participants in rural Uganda. We fit regression models, stratified by fasting status, to estimate associations between carotid intima media thickness (cIMT), LDL-C, and nHDL-C.ResultsMedian age was 50 years (interquartile range = 46-54), 49% were female, 51% were HIV-positive, and at the time of blood collection, 70% had fasted overnight. Mean LDL-C, nHDL-C, and triglycerides in the non-fasting and fasting groups were 85 vs 88 mg/dL (P = 0.39), 114 vs 114 mg/dL (P = 0.98), and 130 vs 114 mg/dL (P = 0.05) mg/dL, respectively. In unadjusted models, mean cIMT (mm) was associated with both increased LDL-C (β = 0.0078 per 10mg/dL, P < 0.01) and nHDL-C (β = 0.0075, P < 0.01), and these relationships were similar irrespective of fasting status. After adjustment for traditional CVD risk factors, we observed similar associations, albeit with muted effect sizes within the fasting group.ConclusionsWe found a high correlation between LDL-C and nHDL-C, and both were correlated with cIMT, irrespective of fasting or HIV serostatus in rural Uganda. Our findings support use of either fasting or non-fasting serum lipids for CVD risk estimation in rural sSA.

Comparison of fasting and non-fasting lipid profile in healthy adult population

Lipid profile is done in fasting blood specimen commonly, the reasons being: 1. Triglycerides remain elevated for several hours in postprandial state, 2. Reference range are established for fasting serum lipid profile.This study was proposed to compare the lipid profiles obtained in fasting and non-fasting conditions. If a reliable correlation between fasting and non-fasting lipid profile will be obtained, assay for lipids in non-fasting state may be adopted for clinical evaluation. This might help in reducing the difficulties faced in obtaining the sample in fasting state. This was a cross-sectional study, conducted from October 2011 to October 2013. Total of 200 subjects were included in the study. Two Samples were collected from each individual, one sample after 8-12 hours fasting and second sample in non-fasting state (random sample). Total cholesterol, Triglycerides, HDL-cholesterol were analyzed by standard methods and, LDL-cholesterol was calculated using Friedewald’s formula. Significant increase was observed in non-fasting Triglyceride and VLDL-C as compared to fasting samples in total population, but we observed significant difference in total cholesterol and LDL-C in total population. Significant reduction was observed in HDL-C in non-fasting state as compared to fasting state. Positive correlation was observed between fasting and non-fasting total cholesterol triglyceride, VLDL-C, HDL-C and LDL-C in the total population. Non-fasting sample can be used to measure Total cholesterol and HDL-C. Non-fasting sample can be used to measure triglyceride, VLDL-C and LDL-C provided reference intervals are established in non-fasting state for the same in larger population.

Nonfasting Lipid Profile May Suffice to Manage Dyslipidemia.

Patients with major mental illness and especially those who receive antipsychotic drugs are at increased risk of metabolic syndrome. Dyslipidemia is part of the metabolic syndrome. Dyslipidemia is associated with an increased risk of cardiovascular, cerebrovascular, and other diseases. A fasting lipid profile is traditionally ordered to determine the need for and to monitor lipid-lowering treatment. However, a recent study showed that fasting and nonfasting lipid levels, obtained from the same patients, almost identically predicted hard 3-year cardiovascular event risks; the risks with fasting and nonfasting levels were closely similar in various secondary analyses, as well. This supports the stance of major medical associations in the field to accept nonfasting lipid levels to guide the treatment of dyslipidemia in the primary and secondary prevention of cardiovascular and cerebrovascular disease events.

Fasting Versus Non-Fasting in Assessing Lipid Profile and Complete Blood Picture

Coronary Heart Disease (CHD) is the world’s leading cause of death and represents a serious global health problem. The general recommendations to operators in the prevention of CHD should include complete lipid profile testing, that is Total Cholesterol(TC), Total Triglycerides(TG), High Density Lipoprotein (HDL), Low Density Lipoprotein (LDL) and Very Low Density Lipoprotein (VLDL). Recent recommendations have supported non-fasting lipid assessment. On the other hand, classification of dyslipidemias was derived in fasting samples, and cohort studies and clinical trials have performed fasting assessments.The aim of this study was to evaluate fasting versus non-fasting in measuring lipid profile & complete blood picture.A total of 80 female were divided into four groups of 20 female each. The 1st three groups were fasting for 4, 6,14 hours respectively and the 4th group was non-fasting. Blood samples were taken from these females for biochemical & hematological investigations.The lipid profile parameters were measured using Synchron CX4 clinical system Beckman Coulter Inc., Brea, CA. Complete Blood Picture was measured by using automated hematological analyzers BC-3000 plus (Hamburg, Germany). Statistical analysis was carried out using SPSS( Statistical Package for Social Sciences) number 22.Biochemically, for TC,TG & VLDL, it was found that fasting 6 , 14 hours gave significant differences (P< 0.05) when compared with non-fasting group while there were non-significant results for the mean level of HDL & LDL between groups . Regarding hematological assessment, there were non-significant differences between groups in measuring Hemoglobin, Red blood cells, White blood cells, Platelet counts.Since non-fasting may weaken the accuracy in diagnosing some forms of hyperlipidemia, we proposed that laboratories & organizations should also offer measurement of fasting triglycerides according to clinical situations , as in the case of very high non-fasting triglyceride concentration

Comparison Between Measuring of Lipid Profile in Fasting and Non-Fasting States: A Cross-Sectional Study from Iraq

Background: Dyslipidemia is one of the important risk factors for cardiovascular diseases (CVD) and is usually determined by measuring lipid profiles in fasting state. Recent researches showed that non-fasting lipid profiles changed minimally in response to food and may be superior to the prediction of CVD. Objectives: To evaluate whether there is any change in the measurement of lipid profile in fasting and non-fasting states and its effect on patients’ management. Methods: A cross-sectional observational study was performed from January to November 2017, on 194 patients with an age range of 20 to 78 years, attending Faiha Specialized Diabetes, Endocrine, and Metabolism Center (FDEMC) and Basrah General Hospital. Clinical, demographic and laboratory characteristics of the participants were collected in fasting and non-fasting states. Results: Both triglycerides (TG) and very low-density lipoprotein cholesterol (VLDL-C) were significantly higher when measured in the non-fasting state (P = 0.004, 0.004), with a mean increase in TG by 29.39 ± 60 mg/dL (0.3 ± 0.6 mmol/L), and VLDL-C increase by 5.9 ± 12.3 mg/dL (0.15 ± 0.31 mmol/L). These patterns of changes in TG and VLDL-C were observed mainly in patients aged < 55 years, women, obese patients, non-smokers, diabetics, hypertensive, non-CVD patients, and patients without statins. While total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol (HDL-C) did not change significantly. Conclusions: The study showed that non-fasting measurements of both TG and VLDL were significantly higher compared to the fasting state. A finding that was not present in TC, LDL-C, and HDL-C measurements.

Comparison of the nonfasting and fasting lipid profiles of the patients admitted in the cardiology department of a tertiary hospital in Bangladesh

Background: Evidence relaxes the obligation of fasting for a lipid profile test. There is a scarcity of data comparing the fasting and nonfasting lipid profiles in our setting. Objectives: We conducted this study to observe the differences in the components of the lipid profile between the nonfasting and fasting states. Materials and Methods: In this cross-sectional study, 275 patients admitted in the cardiology department of a tertiary hospital in Bangladesh were evaluated; the study participants were categorized as having an acute myocardial infarction (AMI), unstable angina (UA), and no acute coronary syndrome (non-ACS). Serum total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglyceride (TG) were measured in both nonfasting and fasting states in all. Results: All the measured components of the lipid profile, e.g., serum TC, HDL-C, LDL-C, and TG, were higher in the nonfasting state than the fasting state in the study participants with AMI. However, those with UA and those without ACS (non-ACS) had no significant differences in fasting and nonfasting levels of TC, HDL-C, and LDL-C through their TG level was significantly higher in the nonfasting state. Conclusion: Nonfasting blood sample, which is more convenient, may be used for assessing the lipid profile in the majority of the patients advised for the test.

Comparison of Fasting and Non-fasting Lipid Profile in Young Healthy Adults

Background and Aim: It is necessary to find out whether fasting blood samples are must for lipid profile determination. Aim of this study to find out is there any difference between fasting and non-fasting lipid profile in young healthy adults. Methods: This study was done on 100 MBBS students of medical college. Lipid profile was done in these healthy young adults for fasting and postprandial statuses. Results: The lipid profile parameters were compared in both the groups of fasting and postprandial statuses. In fasting group, the mean total cholesterol level was 192.1 mg/dl and mean postprandial total cholesterol level was 194.98 mg/dl (P = 0.0407). The mean fasting serum triglyceride level was 121.16 mg/dl and mean postprandial serum triglyceride level was 126.18 mg/dl (P = 0.0001). The mean fasting high density lipoprotein (HDL) level was 45.08 mg/dl and mean postprandial HDL was 43.84 mg/dl (P = 0.0656). The mean fasting serum VLDL level was 24.23 mg/dl and mean postprandial VLDL level was 25.24 mg/dl (P = 0.0001). The mean fasting LDL was 122.8 mg/dl and mean postprandial LDL was 125.9 mg/dl (P = 0.0416). Conclusion: Finally, from this study we found that there is no significant clinical difference between fasting and non-fasting levels of total cholesterol, HDL, LDL, VLDL and TG. Thus, for estimation of lipid profile we can use the blood samples at any time or irrespective of mealtime.

Predictive Value of Non-fasting Blood Lipid Levels for Cardiovascular Events in Community Population(PICC Study)

Predictive Value of Non-fasting Blood Lipid Levels for Cardiovascular Events in Community Population(PICC Study)

Prevalence of Hypertension and Associated Risk Factors in Suburban Tamil Nadu

Background: Hypertension (HTN) is an important risk factor for cardiovascular mortality in India. HTN prevalence data are predominantly available for urban and rural populations in India but not in the mushrooming suburban areas. This study was conducted to estimate the prevalence of HTN and associated risk factors in suburban Tamil Nadu. Methods: In this Kovai Medical Center Hospital Non-Communicable Disease Study, we enrolled adults >20 years of age residing at Thadagam (suburban) in Coimbatore district, Tamil Nadu, India. All participants had a detailed questionnaire and anthropometric measurements. Blood samples were taken for glycosylated hemoglobin, nonfasting lipid profile, and serum creatinine. Prevalence of HTN (self-reported cases of HTN or systolic blood pressure ≥140 mm Hg and or diastolic blood pressure ≥90 mm Hg) was estimated. Multivariable logistic regression analysis was used to identify factors influencing HTN. Results: A total of 1030 participants were involved in this study. The prevalence of HTN was 47.1% in this area, with similar prevalence in both genders. The ratio of known HTN to newly diagnosed HTN was 1:1.3. Nearly 5% of adults between 20 and 39 years had HTN in this cohort. On multivariate logistic regression, after adjustment for age and sex, HTN was significantly associated with diabetes and atherosclerosis. Conclusions: This study identified a high prevalence of HTN in suburban region of Tamil Nadu. Aggressive screening protocols and targeted treatment are the need of the hour to reduce the burden of HTN and cardiovascular diseases in suburban India.

Postprandial Hypertriglyceridaemia Revisited in the Era of Non-Fasting Lipid Profile Testing: A 2019 Expert Panel Statement, Narrative Review.

Postprandial hypertriglyceridaemia, defined as an increase in plasma triglyceride-containing lipoproteins following a fat meal, is a potential risk predictor of atherosclerotic cardiovascular disease and other chronic diseases. Several non-modifiable factors (genetics, age, sex and menopausal status) and lifestyle factors (diet, physical activity, smoking status, obesity, alcohol and medication use) may influence postprandial hypertriglyceridaemia. This narrative review considers the studies published over the last decade that evaluated postprandial hypertriglyceridaemia. Additionally, the genetic determinants of postprandial plasma triglyceride levels, the types of meals for studying postprandial triglyceride response, and underlying conditions (e.g. familial dyslipidaemias, diabetes mellitus, metabolic syndrome, non-alcoholic fatty liver and chronic kidney disease) that are associated with postprandial hypertriglyceridaemia are reviewed; therapeutic aspects are also considered.

Postprandial Hypertriglyceridaemia Revisited in the Era of Non-fasting Lipid Profiles: Executive Summary of a 2019 Expert Panel Statement.

Postprandial Hypertriglyceridaemia Revisited in the Era of Non-fasting Lipid Profiles: Executive Summary of a 2019 Expert Panel Statement.

Postprandial Hypertriglyceridaemia Revisited in the Era of Non-Fasting Lipid Profile Testing: A 2019 Expert Panel Statement, Main Text.

Residual vascular risk exists despite the aggressive lowering of Low-Density Lipoprotein Cholesterol (LDL-C). A contributor to this residual risk may be elevated fasting, or non-fasting, levels of Triglyceride (TG)-rich lipoproteins. Therefore, there is a need to establish whethe a standardised Oral Fat Tolerance Test (OFTT) can improve atherosclerotic Cardiovascular (CV) Disease (ASCVD) risk prediction in addition to a fasting or non-fasting lipid profile. An expert panel considered the role of postprandial hypertriglyceridaemia (as represented by an OFTT) in predicting ASCVD. The panel updated its 2011 statement by considering new studies and various patient categories. The recommendations are based on expert opinion since no strict endpoint trials have been performed. Individuals with fasting TG concentration <1 mmol/L (89 mg/dL) commonly do not have an abnormal response to an OFTT. In contrast, those with fasting TG concentration ≥2 mmol/L (175 mg/dL) or nonfasting ≥2.3 mmol/L (200 mg/dL) will usually have an abnormal response. We recommend considering postprandial hypertriglyceridaemia testing when fasting TG concentrations and non-fasting TG concentrations are 1-2 mmol/L (89-175 mg/dL) and 1.3-2.3 mmol/L (115-200 mg/dL), respectively as an additional investigation for metabolic risk prediction along with other risk factors (obesity, current tobacco abuse, metabolic syndrome, hypertension, and diabetes mellitus). The panel proposes that an abnormal TG response to an OFTT (consisting of 75 g fat, 25 g carbohydrate and 10 g proteins) is >2.5 mmol/L (220 mg/dL). Postprandial hypertriglyceridaemia is an emerging factor that may contribute to residual CV risk. This possibility requires further research. A standardised OFTT will allow comparisons between investigational studies. We acknowledge that the OFTT will be mainly used for research to further clarify the role of TG in relation to CV risk. For routine practice, there is a considerable support for the use of a single non-fasting sample.

Age-specific and sex-specific reference intervals for non-fasting lipids and apolipoproteins in 7260 healthy Chinese children and adolescents measured with an Olympus AU5400 analyser: a cross-sectional study

AimsEthnic, demographic, lifestyle, genetic and environmental factors influence lipids and apolipoproteins. The aim of this study was to establish age-specific and gender-specific reference intervals for non-fasting lipids and apolipoproteins in...

Association of Cardiac Events with Fasting or Nonfasting Lipid Testing

Based on several population-level analyses of the association of cardiac events with fasting and nonfasting lipid levels, several guidelines now

Association of Nonfasting vs Fasting Lipid Levels With Risk of Major Coronary Events in the Anglo-Scandinavian Cardiac Outcomes Trial–Lipid Lowering Arm

Recent guidelines have recommended nonfasting for routine testing of lipid levels based on comparisons of nonfasting and fasting populations. However, no previous study has examined the association of cardiovascular outcomes with fasting vs nonfasting lipid levels measured in the same individuals. To compare the association of nonfasting and fasting lipid levels with prospectively ascertained coronary and vascular outcomes and to evaluate whether a strategy of using nonfasting instead of fasting lipid level measurement would result in misclassification of risk for individuals undergoing evaluation for initiation of statin therapy. This post hoc prospective follow-up of a randomized clinical trial included 8270 of 10 305 participants from the Anglo-Scandinavian Cardiac Outcomes Trial-Lipid Lowering Arm (ASCOT-LLA) with nonfasting and fasting lipid levels measured 4 weeks apart (including 6855 participants with no prior vascular disease) (median follow-up, 3.3 years; interquartile range, 2.8-3.6 years). Data were collected from February 1, 1998, to December 31, 2002, and analyzed from February 1, 2016, to November 30, 2018. Multivariable Cox models, adjusted for cardiovascular risk factors, were calculated for 40-mg/dL (1-mmol/L) higher values of nonfasting and fasting lipids. The trial's primary end point consisted of major coronary events (nonfatal myocardial infarction [MI] and fatal coronary heart disease [212 events]). Secondary analyses examined atherosclerotic cardiovascular disease (ASCVD) events (including MI, stroke, and ASCVD death [351 events]). Among the 8270 participants (82.1% male; mean [SD] age, 63.4 [8.5] years), nonfasting samples had modestly higher triglyceride levels and similar cholesterol levels compared to fasting samples. Associations of nonfasting lipid levels with coronary events were similar to those for fasting lipid levels. For example, adjusted hazard ratios (HRs) per 40-mg/dL of low-density lipoprotein cholesterol were 1.32 (95% CI, 1.08-1.61; P = .007) for nonfasting levels and 1.28 (95% CI, 1.07-1.55; P = .008) for fasting levels. For the primary prevention group, adjusted HRs were 1.42 (95% CI, 1.13-1.78; P = .003) for nonfasting levels and 1.37 (95% CI, 1.11-1.69; P = .003) for fasting levels. Results were consistent by randomized treatment arm (atorvastatin calcium, 10 mg/d, or placebo) and similar for ASCVD events. Concordance of fasting and nonfasting lipid levels for classifying participants into appropriate ASCVD risk categories was high (94.8%). Measurement of nonfasting and fasting lipid levels yields similar results in the same individuals for association with incident coronary and ASCVD events. These results suggest that routine measurement of nonfasting lipid levels may help facilitate ASCVD risk screening and treatment, including consideration of when to initiate statin therapy.

2018 Cholesterol Clinical Practice Guidelines: Synopsis of the 2018 American Heart Association/American College of Cardiology/Multisociety Cholesterol Guideline.

In November 2018, the American Heart Association and American College of Cardiology (AHA/ACC) released a new clinical practice guideline on cholesterol management. It was accompanied by a risk assessment report on primary prevention of atherosclerotic cardiovascular disease (ASCVD). A panel of experts free of recent and relevant industry-related conflicts was chosen to carry out systematic reviews and meta-analyses of randomized controlled trials (RCTs) that examined cardiovascular outcomes. High-quality observational studies were used for estimation of ASCVD risk. An independent panel systematically reviewed RCT evidence about the benefits and risks of adding nonstatin medications to statin therapy compared with receiving statin therapy alone in persons who have or are at high risk for ASCVD. The guideline endorses a heart-healthy lifestyle beginning in childhood to reduce lifetime risk for ASCVD. It contains several new features compared with the 2013 guideline. For secondary prevention, patients at very high risk may be candidates for adding nonstatin medications (ezetimibe or proprotein convertase subtilisin/kexin type 9 [PCSK9] inhibitors) to statin therapy. In primary prevention, a clinician-patient risk discussion is still strongly recommended before a decision is made about statin treatment. The AHA/ACC risk calculator first triages patients into 4 risk categories. Those at intermediate risk deserve a focused clinician-patient discussion before initiation of statin therapy. Among intermediate-risk patients, identification of risk-enhancing factors and coronary artery calcium testing can assist in the decision to use a statin. Compared with the 2013 guideline, the new guideline gives more attention to percentage reduction in low-density lipoprotein cholesterol as a treatment goal and to long-term monitoring of therapeutic efficacy. To simplify monitoring, nonfasting lipid measurements are allowed.

Comparison of fasting versus non-fasting lipid profile in school children aged 9-11

Autosomal dominant polycystic kidney disease (ADPKD) is one of the most prevalent causes of kidney transplantation (KTx) worldwide. About 40% of ADPKD patients require peritransplant native kidney nephrectomy (NKN). The decision regarding qualification for NKN usually relies on the surgeon’s expertise. Currently used qualification criteria are subjective and incomparable between clinical centers. There is a need to identify the indications for NKN by applying radiologically based methods to the decision-making process.To assess the usefulness of radiologic parameters in the qualification process of ADPKD waitlist candidates for the NKN procedure.A retrospective, observational study in a cohort of ADPKD patients in a single institution was conducted. The study included the participation of waitlist candidates and kidney transplant recipients with computed tomography (CT) or magnetic resonance imaging (MRI) obtained in the peritransplant period. The correlation of imaging-based measurements with the results of clinical qualification for the NKN procedure was assessed.In the years 2012 to 2019, 19 patients completed the inclusion criteria. Total kidney volume (TKV) values were statistically more significant in the NKN group (n = 10) than in the non-NKN group (n = 9), with medians of 3351 mL and 1654 mL, respectively (P = .016). There were no significant differences between the groups in terms of the ratio of complex cyst volume to TKV, with the NKN group having a ratio of 19.2% and the non-NKN group 15.6% (P = .095). Venous compression was found only in the NKN group (n = 2).TKV highly correlates with the results of clinical qualification for NKN. Radiologic assessment enables the detection of complicated cysts or clinically silent states of venous compression. Pretransplant imaging should be routinely obtained.