Clinical laboratory reference intervals in pediatrics: The CALIPER initiative

2009 ◽  
Vol 42 (16-17) ◽  
pp. 1589-1595 ◽  
Author(s):  
Benjamin Jung ◽  
Khosrow Adeli
Keyword(s):  
Clinical Laboratory ◽  
Reference Intervals ◽  
Laboratory Reference

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.

scholarly journals Clinical laboratory reference values in adults in Kisumu County, Western Kenya; hematology, chemistry and CD4

PLoS ONE ◽  
2021 ◽  
Vol 16 (3) ◽  
pp. e0249259
Author(s):  
Valentine Sing’oei ◽  
Jew Ochola ◽  
John Owuoth ◽  
June Otieno ◽  
Eric Rono ◽  
...  
Keyword(s):  
Clinical Trials ◽  
T Cell ◽  
Cell Count ◽  
Reference Values ◽  
Clinical Laboratory ◽  
Reference Intervals ◽  
Cd4 T Cell ◽  
Specific Reference ◽  
Laboratory Reference ◽  
Cd4 T Cell Count

Background Clinical laboratory reference intervals (RIs) are essential for diagnosing and managing patients in routine clinical care as well as establishing eligibility criteria and defining adverse events in clinical trials, but may vary by age, gender, genetics, nutrition and geographic location. It is, therefore, critical to establish region-specific reference values in order to inform clinical decision-making. Methods We analyzed data from a prospective observational HIV incidence cohort study in Kombewa, Kenya. Study participants were healthy males and females, aged 18–35 years, without HIV. Median and 95% reference values (2.5th percentile to 97.5th percentile) were calculated for laboratory parameters including hematology, chemistry studies, and CD4 T cell count. Standard Deviation Ratios (SDR) and Bias Ratios (BR) are presented as measures of effect magnitude. Findings were compared with those from the United States and other Kenyan studies. Results A total of 299 participants were analyzed with a median age of 24 years (interquartile range: 21–28). Ratio of males to females was 0.9:1. Hemoglobin range (2.5th—97.5th percentiles) was 12.0–17.9 g/dL and 9.5–15.3 g/dL in men and women respectively. In the cohort, MCV range was 59-95fL, WBC 3.7–9.2×103/μL, and platelet 154–401×103/μL. Chemistry values were higher in males; the creatinine RI was 59–103 μmol/L in males vs. 46–76 μmol/L in females (BRUL>.3); and the alanine transferase range was 8.8–45.3 U/L in males vs. 7.5–36.8 U/L in females (SDR>.3). The overall CD4 T cell count RI was 491–1381 cells/μL. Some parameters including hemoglobin, neutrophil, creatinine and ALT varied with that from prior studies in Kenya and the US. Conclusion This study not only provides clinical reference intervals for a population in Kisumu County but also highlights the variations in comparable settings, accentuating the requirement for region-specific reference values to improve patient care, scientific validity, and quality of clinical trials in Africa.

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 Comparing Ethnicity-Specific Reference Intervals for Clinical Laboratory Tests from EHR Data

2018 ◽  
Vol 3 (3) ◽  
pp. 366-377 ◽  
Author(s):  
Nadav Rappoport ◽  
Hyojung Paik ◽  
Boris Oskotsky ◽  
Ruth Tor ◽  
Elad Ziv ◽  
...  
Keyword(s):  
Race And Ethnicity ◽  
Laboratory Tests ◽  
Clinical Laboratory ◽  
Local Population ◽  
Reference Intervals ◽  
Medical Decision ◽  
Specific Reference ◽  
Healthy Individuals ◽  
Electronic Health Record Data ◽  
Novel Approach

Abstract Background The results of clinical laboratory tests are an essential component of medical decision-making. To guide interpretation, test results are returned with reference intervals defined by the range in which the central 95% of values occur in healthy individuals. Clinical laboratories often set their own reference intervals to accommodate variation in local population and instrumentation. For some tests, reference intervals change as a function of sex, age, and self-identified race and ethnicity. Methods In this work, we develop a novel approach, which leverages electronic health record data, to identify healthy individuals and tests for differences in laboratory test values between populations. Results We found that the distributions of &gt;50% of laboratory tests with currently fixed reference intervals differ among self-identified racial and ethnic groups (SIREs) in healthy individuals. Conclusions Our results confirm the known SIRE-specific differences in creatinine and suggest that more research needs to be done to determine the clinical implications of using one-size-fits-all reference intervals for other tests with SIRE-specific distributions.

Response to the editor: Limitations of the Hoffmann method for establishing reference intervals using clinical laboratory data

2019 ◽  
Vol 70 ◽  
pp. 51
Author(s):  
Ying Zhang ◽  
Weibo Ma ◽  
Guocheng Wang ◽  
Yaqi Lv ◽  
Yaguang Peng ◽  
...  
Keyword(s):  
Clinical Laboratory ◽  
Laboratory Data ◽  
Reference Intervals

scholarly journals Reference Intervals (RIs) of Lipid Parameters for Nepalese Population

2018 ◽  
Vol 6 (4) ◽  
pp. 366-372
Author(s):  
R.V. Mahato ◽  
R.K. Singh ◽  
A. M. Dutta ◽  
K. Ichihara ◽  
M. Lamsal
Keyword(s):  
Total Cholesterol ◽  
Reference Values ◽  
Clinical Laboratory ◽  
Local Population ◽  
Density Lipoprotein ◽  
Physical Exertion ◽  
Hdl Cholesterol ◽  
Reference Interval ◽  
Reference Intervals ◽  
Lipoprotein Cholesterol

Introduction: Reference interval (RIs) is the range of values provided by laboratory scientists in a convenient and practical form to support clinician in interpreting observed values for diagnosis, treatment and monitoring of a disease. Laboratories in Nepal uses RIs, provided in the kit inserts by the manufacturers or from the scientific literature, established for western/European population. It is well known that population across the globe differs physiologically, genetically; race, ethnically, lifestyle, food habits and diet which have great impact on the reference values. Thus, it is inappropriate to use RIs that do not represent the local population. This approach highlights for establishing reference values in Nepalese population using the IFCC-CRIDL guidelines published in (C28-A3). Objectives: The objective of this study is to analyze blood lipids concentration in apparently healthy Nepalese population to set up reference values for total cholesterol (TC), triglycerides (TG), High Density Lipoprotein-cholesterol (HDL-C) and Low Density Lipoprotein-cholesterol (LDL-C) and compare with the internationally recommended values. Methods: Reference individuals selected from healthy volunteers according to the IFCC/C-RIDL protocol in (C28 –A3). Volunteers were requested to avoid excessive physical exertion/exercise/excessive eating and drinking and fast overnight for 10-12 hour. Blood samples were collected from 120 subjects from each five centers of the country between 7:00-10:00 am, serum were separated and refrigerated at -20 in a cryo-vials. Finally, 617 samples were transported to Yamaguchi University, Graduate School of Medicine, Ube, Japan for analysis in dry Ice and 30 parameters were measured by fully automated biochemistry analyzer, Beckman Coulter (BC480) in the clinical laboratory. Results: A reference interval for each parameter was calculated from the 95% reference intervals ranging from 2.5% and 97.5% percentiles and, arithmetic mean + 2 SD were also calculated. The 95% reference range for total cholesterol (2.53-6.14), triglyceride was(0.42-3.32),for HDL Cholesterol was (0.28-1.46), for LDL was(1.05-4.00) and for VLDL was (0.054-0.92) for Nepalese population. Conclusion: Nepalese clinicians can take into consideration of reference lipid values of this study for diagnosis, treatment and monitoring of disease. Int. J. Appl. Sci. Biotechnol. Vol 6(4): 366-372

A multi-stage Gaussian transformation algorithm for clinical laboratory data.

1982 ◽  
Vol 28 (8) ◽  
pp. 1735-1741 ◽  
Author(s):  
J C Boyd ◽  
D A Lacher
Keyword(s):  
Mean Squared Error ◽  
Clinical Laboratory ◽  
Statistical Tests ◽  
Random Noise ◽  
Laboratory Data ◽  
Reference Interval ◽  
Reference Intervals ◽  
Distributed Data ◽  
Multi Stage ◽  
Positive Coefficients

Abstract We have developed a multi-stage computer algorithm to transform non-normally distributed data to a normal distribution. This transformation is of value for calculation of laboratory reference intervals and for normalization of clinical laboratory variates before applying statistical procedures in which underlying data normality is assumed. The algorithm is able to normalize most laboratory data distributions with either negative or positive coefficients of skewness or kurtosis. Stepwise, a logarithmic transform removes asymmetry (skewness), then a Z-score transform and power function transform remove residual peakedness or flatness (kurtosis). Powerful statistical tests of data normality in the procedure help the user evaluate both the necessity for and the success of the data transformation. Erroneous assessments of data normality caused by rounded laboratory test values have been minimized by introducing computer-generated random noise into the data values. Reference interval endpoints that were estimated parametrically (mean +/- 2 SD) by using successfully transformed data were found to have a smaller root-mean-squared error than those estimated by the non-parametric percentile technique.

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