Reference Intervals (RIs) and clinical decision limits (CDLs) are a vital part of the information supplied by laboratories to support the interpretation of numerical clinical pathology results. RIs ...describe the typical distribution of results seen in a healthy reference population while CDLs are associated with a significantly higher risk of adverse clinical outcomes or are diagnostic for the presence of a specific disease. However, as the two concepts are sometimes confused, there is a need to clarify the differences between these terms and to ensure they are easily distinguished, especially because CDLs have a clinical association with specific diseases and risks, thereby implying that effective clinical interventions are available. It is important to note that, because population-based RIs are derived from the range of values expected in a typical community population, laboratory results that fall outside a RI do not necessarily indicate a disease but rather that additional medical follow-up and/or treatment may be warranted. In contrast, CDLs are associated with a risk of specific adverse outcomes, and are commonly used to interpret laboratory test results, including lipid parameters, glucose, hemoglobin A1c (HbA1c), and tumor markers, to determine risk of disease, to diagnose or to treat. In recent years, the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) Committee on Reference Intervals and Decision Limits (C-RIDL) has focused primarily on RIs and has performed multicenter studies to obtain common RIs. However, the broader responsibility of the Committee, from its name, includes "decision limits". C-RIDL now aims to emphasize the importance of the correct use of both RIs and CDLs and to encourage laboratories to specify the appropriate information to clinicians as needed. This review discusses RIs and CDLs in detail, describes the similarities and the differences between these two important tools in laboratory medicine, and clearly explains the processes used to define them. C-RIDL encourages the involvement of laboratory professionals in the establishment of both RIs and CDLs.
Celotno besedilo
Dostopno za:
DOBA, IJS, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK, VSZLJ
The understanding that hemoglobin A1c (HbA1c) represents the average blood glucose level of patients over the previous 120 days underlies the current management of diabetes. Even in making such a ...statement, we speak of "average blood glucose" as though "blood glucose" were itself a simple idea. When we consider all the blood glucose forms-arterial versus venous versus capillary, whole blood versus serum versus fluoride-preserved plasma, fasting versus nonfasting-we can start to see that this is not a simple issue. Nevertheless, it seems as though HbA1c correlates to any single glucose measurement. Having more than one measurement and taking those measurements in the preceding month improves the correlation further. In particular, by having glucose measurements that reflect both the relatively lower overnight glucose levels and measurements that reflect the postprandial peaks improves not only our ability to manage diabetes patients, but also our understanding of how HbA1c levels are determined. Modern continuous glucose monitoring (CGM) devices may take thousands of glucose results over a week. Several studies have shown that CGM glucose averages account for the vast proportion of the variation of HbA1c. The ability to relate HbA1c to average glucose may become a popular method for reporting HbA1c, eliminating current concerns regarding differences in HbA1c standardization. Hemoglobin A1c expressed as an average glucose may be more understandable to patients and improve not only their understanding, but also their ability to improve their diabetes management.
Objective Vitamin D deficiency is recognized as a global public health problem, but the population‐based prevalence of deficiency and its determinants in Australian adults is not known. This study ...evaluated the vitamin D status of Australian adults aged ≥25 years and risk factors associated with vitamin D deficiency in this population.
Design and Patients We studied a national sample of 11 247 Australian adults enrolled in the 1999/2000 Australian Diabetes, Obesity and Lifestyle (AusDiab) study drawn from 42 randomly selected districts throughout Australia.
Measurements Serum concentrations of 25‐hydroxyvitamin D 25(OH)D were measured by immunoassay. Vitamin D deficiency was defined as a concentration <50 nmol/l. Information on demographic and lifestyle factors was derived from interview‐administered questionnaires.
Results The mean serum 25(OH)D concentration was 63 nmol/l (95% CI: 59–67 nmol/l). Only 4% of the population had a level <25 nmol/l, but the prevalence of vitamin D deficiency (<50 nmol/l) was 31% (22% men; 39% women); 73% had levels <75 nmol/l. The prevalence of vitamin D deficiency increased significantly with age, was greater in women, in those of non‐Europid origin, in the obese and those who were physically inactive and with a higher level of education. Deficiency was also more common during winter and in people residing in southern Australia (latitude >35°S); 42% of women and 27% of men were deficient during summer–autumn, which increased to 58% and 35%, respectively, during winter–spring.
Conclusion Vitamin D deficiency is common in Australia affecting nearly one‐third of adults aged ≥25 years. This indicates that strategies are needed at the population level to improve vitamin D status of Australians.
To examine whether combined vitamin D and calcium supplementation improves insulin sensitivity, insulin secretion, β-cell function, inflammation and metabolic markers.
6-month randomized, ...placebo-controlled trial.
Ninety-five adults with serum 25-hydroxyvitamin D 25(OH)D ≤55 nmol/L at risk of type 2 diabetes (with prediabetes or an AUSDRISK score ≥15) were randomized. Analyses included participants who completed the baseline and final visits (treatment n = 35; placebo n = 45).
Daily calcium carbonate (1,200 mg) and cholecalciferol 2,000-6,000 IU to target 25(OH)D >75 nmol/L or matching placebos for 6 months.
Insulin sensitivity (HOMA2%S, Matsuda index), insulin secretion (insulinogenic index, area under the curve (AUC) for C-peptide) and β-cell function (Matsuda index x AUC for C-peptide) derived from a 75 g 2-h OGTT; anthropometry; blood pressure; lipid profile; hs-CRP; TNF-α; IL-6; adiponectin; total and undercarboxylated osteocalcin.
Participants were middle-aged adults (mean age 54 years; 69% Europid) at risk of type 2 diabetes (48% with prediabetes). Compliance was >80% for calcium and vitamin D. Mean serum 25(OH)D concentration increased from 48 to 95 nmol/L in the treatment group (91% achieved >75 nmol/L), but remained unchanged in controls. There were no significant changes in insulin sensitivity, insulin secretion and β-cell function, or in inflammatory and metabolic markers between or within the groups, before or after adjustment for potential confounders including waist circumference and season of recruitment. In a post hoc analysis restricted to participants with prediabetes, a significant beneficial effect of vitamin D and calcium supplementation on insulin sensitivity (HOMA%S and Matsuda) was observed.
Daily vitamin D and calcium supplementation for 6 months may not change OGTT-derived measures of insulin sensitivity, insulin secretion and β-cell function in multi-ethnic adults with low vitamin D status at risk of type 2 diabetes. However, in participants with prediabetes, supplementation with vitamin D and calcium may improve insulin sensitivity.
Australian New Zealand Clinical Trials Registry ACTRN12609000043235.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
To the Editor:
Kummer and colleagues (Aug. 18 issue)
1
draw timely attention to the serious problem of biotin interference in thyroid-function tests. As they report, biotin plays an important role in ...the treatment of patients with rare inborn errors of metabolism. Recently, however, high-dose biotin has been adopted in the treatment of multiple sclerosis,
2
and this has led to a succession of false diagnoses of thyrotoxicosis in patients with multiple sclerosis.
3
,
4
Biotin interference is not limited to thyroid-function tests.
5
Streptavidin–biotin is used extensively by laboratories to improve the sensitivity of many immunoassays. Biotin interfered with thyroid-function tests and other . . .
OBJECTIVE: To evaluate A1C for screening and diagnosis of undiagnosed type 2 diabetes defined by oral glucose tolerance testing in clinical and general populations. RESEARCH DESIGN AND METHODS: A1C ...cut offs (less-than or equal to5.5% to rule out diabetes; ≥7.0% to rule in diabetes) were derived from a clinical group (Melbourne Pathology MP group: n = 2,494; undiagnosed diabetes 34.6%) and then evaluated in a population-based sample (AusDiab group: n = 6,015; undiagnosed diabetes 4.6%). RESULTS: For diabetes in the MP and AusDiab groups, A1C at 5.5% gave sensitivities of 98.7 and 83.5%, while A1C at 7.0% gave specificities of 98.2 and 100%, respectively. Many (61.9-69.3%) with impaired A1C (5.6-6.9%) in both populations had abnormal glucose status. CONCLUSIONS: A1C less-than or equal to5.5% and ≥7.0% predicts absence or presence of type 2 diabetes, respectively, while at A1C 6.5-6.9% diabetes is highly probable in clinical and population settings. A high proportion of people with impaired A1C have abnormal glucose status requiring follow-up.
Gestational Diabetes Mellitus (GDM) increases the risk of type 2 diabetes. A register can be used to follow-up high risk women for early intervention to prevent progression to type 2 diabetes. We ...evaluate the performance of the world's first national gestational diabetes register.
Observational study that used data linkage to merge: (1) pathology data from the Australian states of Victoria (VIC) and South Australia (SA); (2) birth records from the Consultative Council on Obstetric and Paediatric Mortality and Morbidity (CCOPMM, VIC) and the South Australian Perinatal Statistics Collection (SAPSC, SA); (3) GDM and type 2 diabetes register data from the National Gestational Diabetes Register (NGDR). All pregnancies registered on CCOPMM and SAPSC for 2012 and 2013 were included-other data back to 2008 were used to support the analyses. Rates of screening for GDM, rates of registration on the NGDR, and rates of follow-up laboratory screening for type 2 diabetes are reported.
Estimated GDM screening rates were 86% in SA and 97% in VIC. Rates of registration on the NGDR ranged from 73% in SA (2013) to 91% in VIC (2013). During the study period rates of screening at six weeks postpartum ranged from 43% in SA (2012) to 58% in VIC (2013). There was little evidence of recall letters resulting in screening 12 months follow-up.
GDM Screening and NGDR registration was effective in Australia. Recall by mail-out to young mothers and their GP's for type 2 diabetes follow-up testing proved ineffective.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
It is unknown if high prolactin levels during pregnancy contribute to the development of gestational diabetes. We hypothesized that higher prolactin levels are associated with reduced glucose ...tolerance, as determined by higher 2‐h glucose level from an oral glucose tolerance test in pregnancy. The 75‐g oral glucose tolerance test was carried out at 28 weeks of gestation in 69 participants. A multiple regression analysis was used to determine the relationship between serum prolactin and 2‐h glucose levels. Multivariable regression analysis showed an independent and significant relationship between third trimester prolactin and 2‐h glucose levels post oral glucose tolerance test. Higher prolactin levels were associated with higher glucose levels independent of age, body mass index, gravidity and parity. Higher prolactin levels associated with reduced glucose tolerance in the third trimester of pregnancy suggests the possible independent role of prolactin in the pathogenesis of gestational diabetes.
This study is the first to demonstrate the observation for the hypothesis that higher prolactin levels are associated with glucose intolerance during pregnancy. Prolactin has metabolic impacts beyond lactation. We propose that high levels of prolactin may contribute to pregnancy‐induced hyperglycaemia similar to its effects in prolactinoma.
Context: Management of male infertility and/or androgen deficiency requires accurate hormonal measurements with valid reference intervals.
Objective: The objective of this study was to develop a ...valid reference panel of blood samples from healthy eugonadal young men with verified normal reproductive function and to use this panel to evaluate the performance of seven fully automated, commercial multiplex immunoassay platforms used to measure serum total testosterone (T), LH, and FSH.
Design: This was an observational study of consistency among seven different automated immunoassays for each of total T, LH, and FSH. Each method was implemented in two laboratories, with each repeating the analysis of the full reference panel samples twice. Serum T concentrations were also measured by gas chromatography/mass spectrometry (GC/MS), and serum inhibin B levels were determined by an ELISA.
Setting: The study was performed at commercial, high-volume, clinical pathology laboratories.
Participants: From 147 men screened, sera from 124 healthy, reproductively normal men (age, 21–35 yr) with normal sperm output were used as a reference panel. All laboratories selected for elite performance in the national immunoassay quality assurance program agreed to participate.
Main Outcome Measure(s): For each of the 868 assays, descriptive statistics were calculated in the natural and log-transformed scales and were analyzed by nested, repeated measures ANOVA after log transformation. Reference intervals, defined as 95% confidence limits, were calculated using arithmetic (natural scale), geometric (log scale) and nonparametric methods.
Results: Descriptive statistics and reference intervals for serum T, LH, and FSH differed widely and significantly between methods, but variation between laboratories for the same assay was negligible. All T methods showed significant differences in regression slope and intercept in deviance plots as well as in estimated reference ranges compared with the independent GC/MS reference method. Although similar between-method differences existed for gonadotropin assays, the smaller quantitative discrepancies allowed assignment of consensus reference intervals for serum FSH (1.3–8.4 IU/liter) and LH (1.6–8.0 IU/liter), although these differed from manufacturers’ currently quoted expected values.
Conclusions: Using a reference panel of sera from healthy eugonadal young men with verified normal reproductive function, major differences exist between commercial T immunoassays as well as divergence from the GC/MS standard. This impairs their clinical diagnostic utility and requires substantial improvements in automated T immunoassay technologies or a switch to GC/MS methods. Gonadotropin assays showed less variability, but current high-throughput immunoassays remain suboptimal to confirm accurate diagnosis of azoospermia or androgen deficiency.
PDF
