Are the currently used reference intervals for creatine kinase (CK) reflecting the general population? The Tromsø Study

2012 ◽  
Vol 50 (5) ◽  
Author(s):  
Hallvard Lilleng ◽  
Stein Harald Johnsen ◽  
Tom Wilsgaard ◽  
Svein Ivar Bekkelund
Keyword(s):  
Creatine Kinase ◽  
General Population ◽  
Reference Interval ◽  
Reference Intervals ◽  
Control Analysis ◽  
Age Group ◽  
Background Population ◽  
Norwegian Population ◽  
Reference Limits ◽  
Laboratory Reference

AbstractLaboratory reference intervals are not necessarily reflecting the range in the background population. This study compared creatine kinase (CK) reference intervals calculated from a large sample from a Norwegian population with those elaborated by the Nordic Reference Interval Project (NORIP). It also assessed the pattern of CK-normalization after standardized control analyses.New upper reference limits (URL) CK values were calculated after exclusion of individuals with risk of hyperCKemia and including individuals with incidentally detected hyperCKemia after they had completed a standardized control analysis. After exclusion of 5924 individuals with possible causes of hyperCKemia, CK samples were analyzed in 6904 individuals participating in the 6th survey of The Tromsø Study. URL was defined as the 97.5 percentile.New URL in women was 207 U/L. In men <50 years it was 395 U/L and in men ≥50 years 340 U/L. In individuals with elevated CK, normalization grade after control analysis was inversely correlated to the CK level (p<0.04).URL CK values in women and in men <50 years of age were in accordance with URL CK values given by the NORIP. In men ≥50 years, a higher URL was found and the findings suggest an upward adjustment of URL in this age group.

scholarly journals Division of Myocardial Enzyme Reference Intervals in Population Aged 1 to <18 Years Old Based on Fisher’s Optimal Segmentation Method

2020 ◽  
Vol 2020 ◽  
pp. 1-8 ◽  
Author(s):  
Wenjia Guo ◽  
Qi Zhou ◽  
Yanan Jia ◽  
Jiancheng Xu
Keyword(s):  
Creatine Kinase ◽  
Cardiac Development ◽  
Reference Interval ◽  
Reference Intervals ◽  
Impact Factors ◽  
Segmentation Method ◽  
Splitting Sequence ◽  
Biochemical Analyzer ◽  
Optimal Segmentation ◽  
Ordered Data

Background. Reference interval (RI) research is to make it a concise, effective, and practical diagnostic tool. This study aimed to establish sex- and age-specific RI for myocardial enzyme activity in population aged 1–<18 years old in Changchun, China. Methods. Healthy subjects (n = 6,322, 1–<18 years old) were recruited from communities and schools. Aspartate aminotransferase (AST), lactate dehydrogenase (LDH), creatine kinase (CK), and creatine kinase isoenzyme (CKMB) were measured using an automatic biochemical analyzer. Fisher’s optimal segmentation method was used to partition by including percentiles as impact factors, aiming at minimizing the sum of the squares of the total dispersion into groups as splitting sequence of ordered data. Results. AST decreased gradually and was partitioned as 1, 2∼<10 and 10∼<18 years old. LDH presented disparate descending rate among 1∼<4, 4∼<12, and 12∼<18 years old. CK stood quite stable with the same RI in all ages. CKMB began to differ at 6 years of age sexually and then remained stable during 6∼<14 years old for male while it continued to decline in female. Cardiac development was partitioned as 1∼<6, 6∼<13, and 13∼<18 years old using multiple percentiles from massive data that reflect characteristics of totality as impact factors. Conclusions. Fisher’s optimal segmentation method excelled for multidimensionality, continuity, and loop calculating as dealing with RIs for myocardial enzymes activity and cardiac development process despite limitations. In future, impact of partition on the overall interval should be delved into.

Partitioning biochemical reference data intosubgroups: comparison of existing methods

2004 ◽  
Vol 42 (7) ◽  
Author(s):  
Ari Lahti
Keyword(s):  
Reference Data ◽  
Reference Interval ◽  
Reference Intervals ◽  
New Method ◽  
Poor Correlation ◽  
Specific Reference ◽  
Common Reference ◽  
Reference Limits ◽  
The Common ◽  
The Ideal

AbstractFour existing methods for partitioning biochemical reference data into subgroups are compared. Two of these, the method of Sinton et al. and that of Ichihara and Kawai, are based on a quotient of a difference between the subgroups and the reference interval for the combined distribution. The criterion of Sinton et al. appears rather stringent and could lead to recommendations to apply a common reference interval in many cases where establishment of group-specific reference intervals would be more useful. The method of Ichihara and Kawai is similar to that of Sinton et al., but their criterion, based on a quantity derived from between-group and within-group variances, seems to lead to inconsistent results when applied to some model cases. These two methods have the common weakness of using gross differences between subgroup distributions as an indicator of differences between their reference limits, while distributions with different means can actually have equal reference limits and those with equal means can have different reference limits. The idea of Harris and Boyd to require that the proportions of the subgroup distributions outside the common reference limits be kept reasonably close to the ideal value of 2.5% as a prerequisite for using common reference limits seems to have been a major improvement. The other two methods considered, that of Harris and Boyd and the “new method” follow this idea. The partitioning criteria of Harris and Boyd have previously been shown to provide a poor correlation to those proportions, however, and the weaknesses of their method are summarized in a list of five drawbacks. Different versions of the new method offer improvements to these drawbacks.

scholarly journals Impact of Subgroup Prevalences on Partitioning of Gaussian-distributed Reference Values

2002 ◽  
Vol 48 (11) ◽  
pp. 1987-1999 ◽  
Author(s):  
Ari Lahti ◽  
Per Hyltoft Petersen ◽  
James C Boyd
Keyword(s):  
Reference Interval ◽  
Reference Population ◽  
Reference Intervals ◽  
Source Population ◽  
Distributed Data ◽  
New Model ◽  
Common Reference ◽  
Reference Limits ◽  
Partitioning Problem ◽  
Analytical Expressions

Abstract Background: The aims of this report were to examine how unequal subgroup prevalences in the source population may affect reference interval partitioning decisions and to develop generally applicable guidelines for partitioning gaussian-distributed data. Methods: We recently proposed a new model for partitioning reference intervals when the underlying data distribution is gaussian. This model is based on controlling the proportions of the subgroup distributions that fall outside each of the common reference limits, using the distances between the reference limits of the subgroup distributions as functions to these proportions. We examine the significance of the unequal prevalence effect for the partitioning problem and quantify it for distance partitioning criteria by deriving analytical expressions to express these criteria as a function of the ratio of prevalences. An application example, illustrating various aspects of the importance of the prevalence effect, is also presented. Results: Dramatic shrinkage of the critical distances between reference limits of the subgroups needed for partitioning was observed as the ratio of prevalences, the larger one divided by the smaller one, was increased from unity. Because of this shrinkage, the same critical distances are not valid for all ratios of prevalences, but specific critical distances should be used for each particular value of this ratio. Although proportion criteria used in determining the need for reference interval partitioning are not dependent on the prevalence effect, this effect should be accounted for when these criteria are being applied by adjusting the sample sizes of the subgroups to make them correspond to the ratio of prevalences. Conclusions: The prevalences of subgroups in the reference population should be known and observed in the calculations for every reference interval study, irrespective of whether distance or proportion criteria are being used to determine the need for reference interval partitioning. We present detailed methods to account for the prevalences when applying each of these types of criteria. Analytical expressions for the distance criteria, to be used when high precision is needed, and approximate distances, to be used in practical work, are derived. General guidelines for partitioning gaussian distributed data are presented. Following these guidelines and using the new model, we suggest that partitioning can be performed more reliably than with any of the earlier models because the new model not only offers an improved correspondence between the critical distances and the critical proportions, but also accounts for the prevalence effect.

scholarly journals Reference ranges for clinical electrophysiology of vision

2021 ◽  
Author(s):  
C. Quentin Davis ◽  
Ruth Hamilton
Keyword(s):  
Reference Values ◽  
False Negative ◽  
Reference Interval ◽  
Reference Intervals ◽  
Clinical Electrophysiology ◽  
Reference Ranges ◽  
Physiological Measurement ◽  
Negative Results ◽  
Reference Limits ◽  
Suitable Reference

Abstract Introduction Establishing robust reference intervals for clinical procedures has received much attention from international clinical laboratories, with approved guidelines. Physiological measurement laboratories have given this topic less attention; however, most of the principles are transferable. Methods Herein, we summarise those principles and expand them to cover bilateral measurements and one-tailed reference intervals, which are common issues for those interpreting clinical visual electrophysiology tests such as electroretinograms (ERGs), visual evoked potentials (VEPs) and electrooculograms (EOGs). Results The gold standard process of establishing and defining reference intervals, which are adequately reliable, entails collecting data from a minimum of 120 suitable reference individuals for each partition (e.g. sex, age) and defining limits with nonparametric methods. Parametric techniques may be used under some conditions. A brief outline of methods for defining reference limits from patient data (indirect sampling) is given. Reference intervals established elsewhere, or with older protocols, can be transferred or verified with as few as 40 and 20 suitable reference individuals, respectively. Consideration is given to small numbers of reference subjects, interpretation of serial measurements using subject-based reference values, multidimensional reference regions and age-dependent reference values. Bilateral measurements, despite their correlation, can be used to improve reference intervals although additional care is required in computing the confidence in the reference interval or the reference interval itself when bilateral measurements are only available from some of subjects. Discussion Good quality reference limits minimise false-positive and false-negative results, thereby maximising the clinical utility and patient benefit. Quality indicators include using appropriately sized reference datasets with appropriate numerical handling for reporting; using subject-based reference limits where appropriate; and limiting tests for each patient to only those which are clinically indicated, independent and highly discriminating.

scholarly journals Advances in Pediatric Reference Intervals for Biochemical Markers: Establishment of the Caliper Database in Healthy Children and Adolescents/Napredak U Oblasti Pedijatrijskih Referentnih Intervala Za Biohemijske Markere: Izrada Baze Podataka Caliper Kod Zdrave Dece I Adolescenata

2014 ◽  
Vol 34 (1) ◽  
pp. 23-30 ◽  
Author(s):  
Kimiya Karbasy ◽  
Petra Ariadne ◽  
Stephanie Gaglione ◽  
Michelle Nieuwesteeg ◽  
Khosrow Adeli
Keyword(s):  
Children And Adolescents ◽  
Biochemical Markers ◽  
Clinical Laboratory ◽  
Reference Interval ◽  
Reference Intervals ◽  
Healthy Children ◽  
Medical Practitioners ◽  
Laboratory Test Results ◽  
Laboratory Reference ◽  
And Gender

Summary Clinical laboratory reference intervals provide valuable information to medical practitioners in their interpretation of quantitative laboratory test results, and therefore are critical in the assessment of patient health and in clinical decisionmaking. The reference interval serves as a health-associated benchmark with which to compare an individual test result. Unfortunately, critical gaps currently exist in accurate and upto-date pediatric reference intervals for accurate interpretation of laboratory tests performed in children and adolescents. These critical gaps in the available laboratory reference intervals have the clear potential of contributing to erroneous diagnosis or misdiagnosis of many diseases. To address these important gaps, several initiatives have begun internationally by a number of bodies including the KiGGS initiative in Germany, the Aussie Normals in Australia, the AACC-National Children Study in USA, the NORICHILD Initiative in Scandinavia, and the CALIPER study in Canada. In the present article, we will review the gaps in pediatric reference intervals, challenges in establishing pediatric norms in healthy children and adolescents, and the major contributions of the CALIPER program to closing the gaps in this crucial area of pediatric laboratory medicine. We will also discuss the recently published CALIPER reference interval database (www.caliperdatabase.com) developed to provide comprehensive age and gender specific pediatric reference intervals for a larger number of biochemical markers, based on a large and diverse healthy children cohort. The CALIPER database is based on a multiethnic population examining the influence of ethnicity on laboratory reference intervals. Thus the database has proved to be of global benefit and is being adopted by hospital laboratories worldwide.

Error in laboratory reference limits as shown in a collaborative quality-assurance program.

1986 ◽  
Vol 32 (5) ◽  
pp. 845-849 ◽  
Author(s):  
P J Compton ◽  
M C Stuart ◽  
L Lazarus
Keyword(s):  
Quality Assurance ◽  
Reference Intervals ◽  
Quality Assurance Program ◽  
Diagnostic Quality ◽  
Diagnostic Assays ◽  
Individual Laboratory ◽  
National Quality ◽  
Reference Limits ◽  
Laboratory Reference

Abstract Laboratories participate in collaborative quality-assurance programs to maintain and improve the quality of their diagnostic assays, but little attention has been paid to diagnostic quality in these programs. We used a national quality-assurance program to assess the quality of laboratory reference intervals as exemplified by triiodothyronine, thyroxin, and thyrotropin immunoassays. The limits of the reference intervals used by laboratories bear virtually no relationship to laboratory bias, i.e., whether assays read "high" or "low." Further, correcting assay results from different laboratories for the reference limits used increases rather than decreases interlaboratory scatter. We conclude that the analytical quality of immunoassays now exceeds the quality of the reference limits supplied to clinicians to assist diagnosis, and that nationally or internationally defined reference limits would therefore provide more information at less cost than do individual laboratory reference limits.

Determination of reference intervals for serum magnesium

1990 ◽  
Vol 36 (5) ◽  
pp. 756-758 ◽  
Author(s):  
G O Duncanson ◽  
H G Worth
Keyword(s):  
Alkaline Phosphatase ◽  
Gaussian Distribution ◽  
Parametric Analysis ◽  
Serum Magnesium ◽  
Reference Interval ◽  
Reference Intervals ◽  
Age Related ◽  
Reference Limits ◽  
Males And Females

Abstract Using a discrete analyzer and a dye-binding method, we measured magnesium in 800 patients' samples received for routine analysis. By excluding data from samples for which the calcium and (or) alkaline phosphatase values were outside defined reference limits, we established a reference interval for magnesium. Because the data showed a gaussian distribution, we could use parametric analysis to establish age-related intervals for both males and females.

scholarly journals Age- and Sex-Specific TSH Upper-Limit Reference Intervals in the General French Population: There Is a Need to Adjust Our Actual Practices

2020 ◽  
Vol 9 (3) ◽  
pp. 792 ◽  
Author(s):  
Véronique Raverot ◽  
Maxime Bonjour ◽  
Juliette Abeillon du Payrat ◽  
Pauline Perrin ◽  
Florence Roucher-Boulez ◽  
...  
Keyword(s):  
Reference Values ◽  
Adult Life ◽  
Reference Value ◽  
Daily Practice ◽  
Reference Interval ◽  
Reference Intervals ◽  
Age Group ◽  
Upper Limit ◽  
Tertiary Center ◽  
Age And Sex

It is well known that thyroid dysfunction increases with age. This study is aimed to determine reference intervals, in males and females, suitable for thyroid disease exploration during adult life using routinely collected serum thyrotropin (TSH) data in a tertiary center from 2007 to 2018. Over 11 years, 295,775 TSH levels were measured in a single lab. Among the 156,025 TSH results available for analysis, 90,538 values were from female subjects, 82,019 were from patients aged >60 years and 26,825 were from patients aged >80 years. By using an indirect approach, we determined reference values of TSH adapted to age and sex, and we then evaluated the proportion of patients who would have been reclassified with these reference values. The median TSH ranged from 1.2–1.4 mUI/L during the study period. The upper limit of reference range of TSH increased with age; in females the median to 97.5th percentile values increased continuously from the age of 30 years to the oldest age group. Using new calculated reference values in patients with TSH above the conventional upper-limit reference value (4 mUI/L), the proportion of results reclassified as within the reference interval among patients aged >60 years ranged, according to age group, from 50.5% to 65.1% of females and from 33.0% to 37.7% of males. The use of TSH age-specific and sex-specific upper-limit reference values led to the reclassification of a great number of samples, notably among women. This suggests that age-specific TSH upper-limit reference intervals in daily practice should be used in order to avoid misclassification.

A study on reference interval transference via linear regression

2019 ◽  
Vol 58 (1) ◽  
pp. 116-129
Author(s):  
Runqing Mu ◽  
Ke Yun ◽  
Xiaoou Yu ◽  
Shitong Cheng ◽  
Ming Ma ◽  
...  
Keyword(s):  
Linear Regression ◽  
Least Squares Method ◽  
Reference Interval ◽  
Reference Intervals ◽  
Regression Equation ◽  
Small Samples ◽  
Healthy Individuals ◽  
Test Number ◽  
Reference Limits ◽  
Better Than

Abstract Background Reference intervals (RIs) transference can expand the applicability of established RIs. However, the study on transference methodology is insufficient, and RIs validation based on small samples cannot adequately identify transferred risk under complex situations. This study aimed to find appropriate conditions to ensure the effect of transference. Methods We established the RIs of Roche and Beckman systems for 27 analytes based on 681 healthy individuals. Roche RIs were converted into the Beckman RIs using linear regression (least squares method) which is divided into two methods – Methodref (500 test numbers with relatively narrow data range) and Methodep (80 test numbers with relatively wide data range). Taking the RIs established by Beckman results as standard, we assessed the accuracy, precision and trueness of transferred results under various conditions. Results A total of 29.6% and 48.1% of analytes were consistent between the two systems for the lower and upper reference limits, respectively. The concordance rates between transferred and measured RIs for Methodref were up to 74.1% and 92.6%, which were better than Methodep (44.4% and 59.3%). The CV of transferred reference limits decreased gradually with increasing test number under the same data range. For most analytes, excluding some electrolyte tests, we could obtain accurate results when r > 0.800 and the test number was sufficient regardless of the regression equation types. Conclusions Transferability of RIs is affected by many factors, such as correlation, test number, regression equation type, and quality requirement. To reduce the risk of transference, it is very important to select right method with reasonable conditions.

scholarly journals Calculation of indirect reference intervals of plasma lipase activity of adults from existing laboratory data based on the Reference Limit Estimator integrated in the OPUS::L information system

2021 ◽  
Vol 45 (2) ◽  
pp. 131-134
Author(s):  
Britta Amodeo ◽  
Aline Schindler ◽  
Ulrike Schacht ◽  
Hans Günther Wahl
Keyword(s):  
Information System ◽  
Lipase Activity ◽  
Clinical Chemistry ◽  
Laboratory Data ◽  
Direct Methods ◽  
Reference Interval ◽  
Reference Intervals ◽  
Specific Reference ◽  
Reference Limit ◽  
Reference Limits

Abstract Objectives Most laboratories have difficulties to determine their own reference intervals for the diagnostic evaluation of patient results by direct methods. Therefore, data is often just taken from the literature or package inserts of the analytical tests. Methods The section on Reference Limits of the German Society for Clinical Chemistry and Laboratory Medicine (DGKL) first uploaded the Reference Limit Estimator (RLE) as an R-program with MS Excel-interface on the DGKL home page and now this tool is implemented in the commercial Laboratory Information System OPUS::L (OSM AG Essen, Germany). We used this OPUS::L “Population specific Reference Limits” tool online with our laboratory database. First calculations were done using the example of lipase. Results The manufacturer’s original reference interval for lipase 12–53 U/L (adults) was changed to age dependent upper reference limits of <41 U/L (<20 years), <60 U/L (20–80 years) and <70 U/L (>80 years). Conclusions By means of the OPUS::L “Population specific Reference Limits” tool we were able to establish our laborarotry specific reference interval for plasma lipase activity. The new reference limits helped to solve an old problem of implausible low elevated lipase values.

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