Background: Reference intervals for serum creatinine remain relevant despite the current emphasis on the use of the estimated glomerular filtration rate for assessing renal function. Many studies on creatinine reference values have been published in the last 20 years. Using criteria derived from published IFCC documents, we sought to identify universally applicable reference intervals for creatinine via a systematic review of the literature.Methods: Studies were selected for inclusion in the systematic review only if the following criteria were met: (a) reference individuals were selected using an “a priori” selection scheme, (b) preanalytical conditions were adequately described; (c) traceability of the produced results to the isotope dilution–mass spectrometry (IDMS) reference method was demonstrated experimentally, and (d) the collected data received adequate statistical treatment.Results: Of 37 reports dealing specifically with serum creatinine reference values, only 1 report with pediatric data and 5 reports with adult data met these criteria. The primary reason for exclusion of most papers was an inadequate demonstration of measurement traceability. Based on the data of the selected studies, we have collated recommended reference intervals for white adults and children.Conclusion: Laboratories using methods producing traceable results to IDMS can apply the selected reference intervals for serum creatinine in evaluating white individuals.

New facts have recently enhanced interest in the topic of reference intervals. In particular, the International Organization for Standardization standard 15189, requesting that ‘biological reference intervals shall be periodically reviewed’, and the directive of the European Union on in vitro diagnostic medical devices asking manufacturers to provide detailed information on reference intervals, have renewed interest in the subject. This review presents an update on the topic, discussing the theoretical aspects and the most critical issues. The basic approach to the definition of reference intervals proposed in the original International Federation of Clinical Chemistry documents still remain valid. The use of data mining to obtain reference data from existing databases has severe limitations. New statistical approaches to discard outliers and to compute reference limits have been recommended. On the other hand, perspectives opened by the improvement in standardization through the implementation of the concept of traceability suggest new models to define ‘common’ reference intervals that can be transferred and adopted by different clinical laboratories in order to decrease the proliferation of different reference intervals not always justified by differences in population characteristics or in analytical methodology.

This paper, prepared by the EFLM Task and Finish Group on Allocation of laboratory tests to different models for performance specifications (TFG-DM), is dealing with criteria for allocating measurands to the different models for analytical performance specifications (APS) recognized in the 1st EFLM Strategic Conference Consensus Statement. Model 1, based on the effect of APS on clinical outcome, is the model of choice for measurands that have a central role in the decision-making of a specific disease or clinical situation and where cut-off/decision limits are established for either diagnosing, screening or monitoring. Total cholesterol, glucose, HbA_1c, serum albumin and cardiac troponins represent practical examples. Model 2 is based on components of biological variation and should be applied to measurands that do not have a central role in a specific disease or clinical situation, but where the concentration of the measurand is in a steady state. This is best achieved for measurands under strict homeostatic control in order to preserve their concentrations in the body fluid of interest, but it can also be applied to other measurands that are in a steady state in biological fluids. In this case, it is expected that the “noise” produced by the measurement procedure will not significantly alter the signal provided by the concentration of the measurand. This model especially applies to electrolytes and minerals in blood plasma (sodium, potassium, chloride, bicarbonate, calcium, magnesium, inorganic phosphate) and to creatinine, cystatin C, uric acid and total protein in plasma. Model 3, based on state-of-the-art of the measurement, should be used for all the measurands that cannot be included in models 1 or 2.

This paper is the ninth in a series dealing with reference procedures for the measurement of catalytic activity concentrations of enzymes at 37 °C and the certification of reference preparations. Other parts deal with: Part 1. The concept of reference procedures for the measurement of catalytic activity concentrations of enzymes; Part 2. Reference procedure for the measurement of catalytic concentration of creatine kinase; Part 3. Reference procedure for the measurement of catalytic concentration of lactate dehydrogenase; Part 4. Reference procedure for the measurement of catalytic concentration of alanine aminotransferase; Part 5. Reference procedure for the measurement of catalytic concentration of aspartate aminotransferase; Part 6. Reference procedure for the measurement of catalytic concentration of γ-glutamyltransferase; Part 7. Certification of four reference materials for the determination of enzymatic activity of γ-glutamyltransferase, lactate dehydrogenase, alanine aminotransferase and creatine kinase at 37 °C; Part 8. Reference procedure for the measurement of catalytic concentration of α-amylase. The procedure described here is derived from the previously described 30 °C IFCC reference method. Differences are tabulated and commented on in Appendix 1.

Background: The reference intervals for hemoglobin A_1c (Hb A_1c) in pregnant women without diabetes are not well defined, and few examples of reference intervals established by networks of different laboratories are available. Methods: Five Italian Diabetic Care Units were involved in the study. Data were collected from 445 pregnant women without diabetes, selected on the basis of glucose challenge test results, and from 384 nonpregnant control women. The Hb A_1c measurements were performed with HPLC systems aligned to the Diabetes Control and Complications Trial. Plasma glucose measurements were also performed locally. Both Hb A_1c and glucose measurements were harmonized by running appropriate external quality assessment schemes. The reference intervals were calculated in terms of nonparametric 2.5th to 97.5th percentiles with 0.90 confidence intervals. Results: The Hb A_1c measurements were reproducible (CV = 2.0%) and accurate [mean (SE) difference from the target values, −0.10 (0.06)%]. Glucose measurements were also reproducible (mean CV = 3.2%) and accurate [difference from the target values, −0.01 (0.04) mmol/L]. To calculate common reference intervals, we merged the data collected in the different centers. The Hb A_1c reference intervals were 4.0%–5.5% for pregnant nondiabetic women and 4.8%–6.2% for nonpregnant controls. Conclusions: Healthy pregnant women have lower Hb A_1c concentrations than nonpregnant women. The reference intervals for Hb A_1c in pregnant women should therefore be lower than those currently in use.