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Whether lipid profiles should be collected from fasting or nonfasting individuals is controversial, particularly in the diabetic population. We examined the influence of normal food intake on lipid profiles in diabetic and nondiabetic individuals. We assessed plasma concentrations of lipids, lipoproteins, apolipoproteins, and albumin as a function of time since the last meal in 58 434 individuals (participation rate 45%) from the general population, 2270 of whom had diabetes mellitus. Similar patterns in the measured constituents were observed in the diabetic and nondiabetic populations. Triglycerides remained increased for 6-7 h in both populations after the last meal, whereas LDL cholesterol and albumin but not apolipoprotein B were reduced in both populations up to 5 h after normal food intake; after adjustment for hemodilution on the basis of albumin concentrations, the LDL cholesterol reductions were no longer present. Maximum observed mean differences from fasting concentrations in diabetic patients were -0.6 mmol/L, 0 mmol/L, 0.2 mmol/L, and 0.08 g/L (8 mg/dL) for LDL cholesterol, HDL cholesterol, triglycerides, and apolipoprotein B, respectively, and, correspondingly, -0.3 mmol/L, 0 mmol/L, 0.2 mmol/L, and 0.03 g/L (3 mg/dL) in individuals without diabetes. Triglycerides increased up to 0.2 mmol/L after normal food intake in individuals with and without diabetes, whereas the postprandial reductions in LDL cholesterol observed in both populations likely were caused by hemodilution due to fluid intake. No statistically significant differences in postprandial apolipoprotein B concentrations were found. These data may be useful for discussion during revisions of guidelines for lipid measurements in individuals with or without diabetes.

Abstract Objective To update the “Testosterone Therapy in Men With Androgen Deficiency Syndromes” guideline published in 2010. Participants The participants include an Endocrine Society–appointed task force of 10 medical content experts and a clinical practice guideline methodologist. Evidence This evidence-based guideline was developed using the Grading of Recommendations, Assessment, Development, and Evaluation approach to describe the strength of recommendations and the quality of evidence. The task force commissioned two systematic reviews and used the best available evidence from other published systematic reviews and individual studies. Consensus Process One group meeting, several conference calls, and e-mail communications facilitated consensus development. Endocrine Society committees and members and the cosponsoring organization were invited to review and comment on preliminary drafts of the guideline. Conclusions We recommend making a diagnosis of hypogonadism only in men with symptoms and signs consistent with testosterone (T) deficiency and unequivocally and consistently low serum T concentrations. We recommend measuring fasting morning total T concentrations using an accurate and reliable assay as the initial diagnostic test. We recommend confirming the diagnosis by repeating the measurement of morning fasting total T concentrations. In men whose total T is near the lower limit of normal or who have a condition that alters sex hormone–binding globulin, we recommend obtaining a free T concentration using either equilibrium dialysis or estimating it using an accurate formula. In men determined to have androgen deficiency, we recommend additional diagnostic evaluation to ascertain the cause of androgen deficiency. We recommend T therapy for men with symptomatic T deficiency to induce and maintain secondary sex characteristics and correct symptoms of hypogonadism after discussing the potential benefits and risks of therapy and of monitoring therapy and involving the patient in decision making. We recommend against starting T therapy in patients who are planning fertility in the near term or have any of the following conditions: breast or prostate cancer, a palpable prostate nodule or induration, prostate-specific antigen level > 4 ng/mL, prostate-specific antigen > 3 ng/mL in men at increased risk of prostate cancer (e.g., African Americans and men with a first-degree relative with diagnosed prostate cancer) without further urological evaluation, elevated hematocrit, untreated severe obstructive sleep apnea, severe lower urinary tract symptoms, uncontrolled heart failure, myocardial infarction or stroke within the last 6 months, or thrombophilia. We suggest that when clinicians institute T therapy, they aim at achieving T concentrations in the mid-normal range during treatment with any of the approved formulations, taking into consideration patient preference, pharmacokinetics, formulation-specific adverse effects, treatment burden, and cost. Clinicians should monitor men receiving T therapy using a standardized plan that includes: evaluating symptoms, adverse effects, and compliance; measuring serum T and hematocrit concentrations; and evaluating prostate cancer risk during the first year after initiating T therapy. This update to the Endocrine Society’s 2010 testosterone guideline, prepared by an expert panel, describes the diagnosis, screening, treatment, and monitoring of hypogonadal men.

Background Glycated haemoglobin (HbA1c) is an important outcome measure in diabetes clinical trials. For multicentre designs, HbA1c can be measured locally at participating centres or by sending blood samples to a central laboratory. This study analyses the agreement between local and central measurements, using 1-year follow-up data collected in a multicentre randomised controlled trial (RCT) of newly diagnosed children with type I diabetes. Methods HbA1c measurements were routinely analysed both locally and centrally at baseline and then at 3, 6, 9 and 12 months and the data reported in mmol/mol. Agreement was assessed by calculating the bias and 95 % limits of agreement, using the Bland-Altman analysis method. A predetermined benchmark for clinically acceptable margin of error between measurements was subjectively set as ±10 % for HbA1c. The percentage of pairs of measurements that were classified as clinically acceptable was calculated. Descriptive statistics were used to examine the agreement within centres. Treatment group was not considered. Results Five hundred and ninety pairs of measurement, representing 255 children and 15 trial centres across four follow-up time points, were compared. There was no significant bias: local measurements were an average of 0.16 mmol/mol (SD = 4.5, 95 % CI −0.2 to 0.5) higher than central. The 95 % limits of agreement were −8.6 to 9.0 mmol/mol (local minus central). Eighty percent of local measurements were within ±10 % of corresponding central measurements. Some trial centres were more varied in the differences observed between local and central measurements: IQRs ranging from 3 to 9 mmol/mol; none indicated systematic bias. Conclusions Variation in agreement between HbA1c measurements was greater than had been expected although no overall bias was detected and standard deviations were similar. Discrepancies were present across all participating centres. These findings have implications for the comparison of standards of clinical care between centres, the design of future multicentre RCTs and existing quality assurance processes for HbA1c measurements. We recommend that centralised HbA1c measurement is preferable in the multicentre clinical trial setting. Trial registration Eudract No. 2010-023792-25 , registered on 4 November 2010.

Background:Reference ranges for testosterone are essential for making a diagnosis of hypogonadism in men.Objective:To establish harmonized reference ranges for total testosterone in men that can be applied across laboratories by cross-calibrating assays to a reference method and standard.Population:The 9054 community-dwelling men in cohort studies in the United States and Europe: Framingham Heart Study; European Male Aging Study; Osteoporotic Fractures in Men Study; and Male Sibling Study of Osteoporosis.Methods:Testosterone concentrations in 100 participants in each of the four cohorts were measured using a reference method at Centers for Disease Control and Prevention (CDC). Generalized additive models and Bland-Altman analyses supported the use of normalizing equations for transformation between cohort-specific and CDC values. Normalizing equations, generated using Passing-Bablok regression, were used to generate harmonized values, which were used to derive standardized, age-specific reference ranges.Results:Harmonization procedure reduced intercohort variation between testosterone measurements in men of similar ages. In healthy nonobese men, 19 to 39 years, harmonized 2.5th, 5th, 50th, 95th, and 97.5th percentile values were 264, 303, 531, 852, and 916 ng/dL, respectively. Age-specific harmonized testosterone concentrations in nonobese men were similar across cohorts and greater than in all men.Conclusion:Harmonized normal range in a healthy nonobese population of European and American men, 19 to 39 years, is 264 to 916 ng/dL. A substantial proportion of intercohort variation in testosterone levels is due to assay differences. These data demonstrate the feasibility of generating harmonized reference ranges for testosterone that can be applied to assays, which have been calibrated to a reference method and calibrator.We cross-calibrated cohort-specific assays to a reference method at CDC and generated harmonized reference ranges for circulating testosterone levels in men, including age-adjusted reference ranges.

Folate (vitamin B9) plays a crucial role in fundamental cellular processes, including nucleic acid biosynthesis, methyl group biogenesis and amino acid metabolism. The detection and correction of folate deficiency prevents megaloblastic anaemia and reduces the risk of neural tube defects. Coexisting deficiencies of folate and vitamin B12 are associated with cognitive decline, depression and neuropathy. Folate deficiency and excess has also been implicated in some cancers. Excessive exposure to folic acid, a synthetic compound used in supplements and fortified foods, has also been linked to adverse health effects. Of at least three distinct laboratory markers of folate status, it is the total abundance of folate in serum/plasma that is used by the majority of laboratories. The analysis of folate in red cells is also commonly performed. Since the folate content of red cells is fixed during erythropoiesis, this marker is indicative of folate status over the preceding ~4 months. Poor stability, variation in polyglutamate chain length and unreliable extraction from red cells are factors that make the analysis of folate challenging. The clinical use of measuring specific folate species has also been explored. 5-Methyltetrahydrofolate, the main form of folate found in blood, is essential for the vitamin B12-dependent methionine synthase mediated remethylation of homocysteine to methionine. As such, homocysteine measurement reflects cellular folate and vitamin B12 use. When interpreting homocysteine results, age, sex and pregnancy, specific reference ranges should be applied. The evaluation of folate status using combined markers of abundance and cellular use has been adopted by some laboratories. In the presence of discordance between laboratory results and strong clinical features of deficiency, treatment should not be delayed. High folate status should be followed up with the assessment of vitamin B12 status, a review of previous results and reassessment of folic acid supplementation regime.

Metabolomics is a powerful tool that is increasingly used in clinical research. Although excellent sample quality is essential, it can easily be compromised by undetected preanalytical errors. We set out to identify critical preanalytical steps and biomarkers that reflect preanalytical inaccuracies. We systematically investigated the effects of preanalytical variables (blood collection tubes, hemolysis, temperature and time before further processing, and number of freeze-thaw cycles) on metabolomics studies of clinical blood and plasma samples using a nontargeted LC-MS approach. Serum and heparinate blood collection tubes led to chemical noise in the mass spectra. Distinct, significant changes of 64 features in the EDTA-plasma metabolome were detected when blood was exposed to room temperature for 2, 4, 8, and 24 h. The resulting pattern was characterized by increases in hypoxanthine and sphingosine 1-phosphate (800% and 380%, respectively, at 2 h). In contrast, the plasma metabolome was stable for up to 4 h when EDTA blood samples were immediately placed in iced water. Hemolysis also caused numerous changes in the metabolic profile. Unexpectedly, up to 4 freeze-thaw cycles only slightly changed the EDTA-plasma metabolome, but increased the individual variability. Nontargeted metabolomics investigations led to the following recommendations for the preanalytical phase: test the blood collection tubes, avoid hemolysis, place whole blood immediately in ice water, use EDTA plasma, and preferably use nonrefrozen biobank samples. To exclude outliers due to preanalytical errors, inspect the biomarker signal intensities reflecting systematic as well as accidental and preanalytical inaccuracies before processing the bioinformatics data.

A growing body of evidence from epidemiological data, animal studies, and clinical trials supports HDL as the next target to reduce residual cardiovascular risk in statin-treated, high-risk patients. For more than 3 decades, HDL cholesterol has been employed as the principal clinical measure of HDL and cardiovascular risk associated with low HDL-cholesterol concentrations. The physicochemical and functional heterogeneity of HDL present important challenges to investigators in the cardiovascular field who are seeking to identify more effective laboratory and clinical methods to develop a measurement method to quantify HDL that has predictive value in assessing cardiovascular risk. In this report, we critically evaluate the diverse physical and chemical methods that have been employed to characterize plasma HDL. To facilitate future characterization of HDL subfractions, we propose the development of a new nomenclature based on physical properties for the subfractions of HDL that includes very large HDL particles (VL-HDL), large HDL particles (L-HDL), medium HDL particles (M-HDL), small HDL particles (S-HDL), and very-small HDL particles (VS-HDL). This nomenclature also includes an entry for the pre-β-1 HDL subclass that participates in macrophage cholesterol efflux. We anticipate that adoption of a uniform nomenclature system for HDL subfractions that integrates terminology from several methods will enhance our ability not only to compare findings with different approaches for HDL fractionation, but also to assess the clinical effects of different agents that modulate HDL particle structure, metabolism, and function, and in turn, cardiovascular risk prediction within these HDL subfractions.

Different laboratory methods are used to quantify ferritin concentrations as a marker of iron status. A systematic review was undertaken to assess the accuracy and comparability of the most used methods for ferritin detection. National and regional databases were searched for prospective, retrospective, sectional, longitudinal and case-control studies containing the characteristics and performance of at least one method for serum/plasma ferritin determinations in humans published to date. The analysis included the comparison between at least 2 methods detailing: sensitivity, precision, accuracy, predictive values, inter-methods adjustment, and use of international reference materials. Pooled method performance was analyzed for each method and across methods. Search strategy identified 11893 records. After de-duplication and screening 252 studies were assessed, including 187 studies in the qualitative analysis and 148 in the meta-analysis. The most used methods included radiometric, nonradiometric and agglutination assays. The overall within-run imprecision for the most reported ferritin methods was 6.2±3.4% (CI 5.69-6.70%; n = 171), between-run imprecision 8.9±8.7% (CI 7.44-10.35%; n = 136), and recovery rate 95.6% (CI 91.5-99.7%; n = 94). The pooled regression coefficient was 0.985 among all methods analyzed, and 0.984 when comparing nonradiometric and radiometric methods, without statistical differences in ferritin concentration ranging from 2.3 to 1454 μμg/L. The laboratory methods most used to determine ferritin concentrations have comparable accuracy and performance. Registered in PROSPERO CRD42016036222.

Automatic assessment of hemoglobin (H), lipaemia (L) and icterus (I) in serum or plasma (HIL indices) is the mainstay for evaluating sample quality. We planned this study to verify whether in-house prepared internal quality control (IQC) materials may be suitable for quality assurance of HIL indices. Pools containing different values of each of the three HIL indices were prepared from routine plasma samples, divided in aliquots and frozen at -20°C. Stability of frozen materials was assessed by thawing one aliquot of each pool after different days of freezing (1, 4, 8, 15, 22 and 29), and by measuring HIL indices on baseline fresh samples and frozen-thawed aliquots with Roche Cobas c702. Five fresh liquid IQCs materials were also measured at the same time points. Intra-assay and inter-assay imprecision of HIL indices calculated with commercial IQC materials ranged between 1.1-2.0% and 1.6-3.3%, respectively. When target values of HIL indices were calculated using frozen-thawed aliquots, the inter-assay imprecision of in-house prepared materials was optimal, even better than that of commercial liquid IQCs (H-index, 0.8% versus 1.6%; L-index, 2.2% versus 2.5%; I-index, 0.8% versus 3.3%). In conclusion, in-house prepared IQC materials are cost-effective alternatives to commercial liquid IQCs for HIL quality assurance.

This study aimed to verify the reference interval(s) (RIs) for routine biochemistry tests in adult Turkish population using the reflimR method and compare them with the manufacturer-provided RIs. The RIs of 19 routine biochemical parameters, analyzed using Beckman Coulter analyzers between February and October 2024, were evaluated using the reflimR algorithm. The RIs were estimated separately for females and males using five indirect approaches (reflimR, refineR, KOSMIC, Hoffmann, and Bhattacharya). A traffic light algorithm based on permissible uncertainty was used to interpret whether the RIs limits calculated with reflimR were within the tolerance limits. Using reflimR, 40 of 76 RI limits were accepted, 21 required checking, and 15 were rejected for RI verification compared with the manufacturer-provided values. The comparison of reflimR with other indirect methods generally produced concordant results, except for the alanine aminotransferase (ALT), gamma-glutamyl transferase (GGT), and total bilirubin tests. The reflimR algorithm may offer a swift and accessible method for calculating and verifying RIs. Verification failures may arise from fundamental variations, including ethnicity, sex, age demographics, and geographic factors, between the manufacturer’s study results and our analyzed population.