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This study is aimed at establishing reference intervals (RIs) of 40 chemistry and immunochemistry analytes for Ghanaian adults based on internationally harmonized protocol by IFCC Committee on Reference Intervals and Decision Limits (C-RIDL). A total of 501 healthy volunteers aged ≥18 years were recruited from the northern and southern regions of Ghana. Blood samples were analyzed with Beckman-Coulter AU480 and Centaur-XP/Siemen auto-analyzers. Sources of variations of reference values (RVs) were evaluated by multiple regression analysis (MRA). The need for partitioning RVs by sex and age was guided by the SD ratio (SDR). The RI for each analyte was derived using parametric method with application of the latent abnormal values exclusion (LAVE) method. Using SDR≥0.4 as threshold, RVs were partitioned by sex for most enzymes, creatinine, uric acid (UA), bilirubin, immunoglobulin-M. MRA revealed age and body mass index (BMI) as major source of variations of many analytes. LAVE lowered the upper limits of RIs for alanine/aspartate aminotransferase, γ-glutamyl transaminase and lipids. Exclusion of individuals with BMI≥30 further lowered the RIs for lipids and CRP. After standardization based on value-assigned serum panel provided by C-RIDL, Ghanaian RIs were found higher for creatine kinase, amylase, and lower for albumin and urea compared to other collaborating countries. The LAVE effect on many clinical chemistry RIs supports the need for the secondary exclusion for reliable derivation of RIs. The differences in Ghanaian RIs compared to other countries underscore the importance of country specific-RIs for improved clinical decision making. [ABSTRACT FROM AUTHOR]

• Indirect derivation of reference intervals (RIs) from routine data by cutting out the distribution peak is being advocated. • For validation, RIs were derived by four indirect methods using data matched to those used for determining RIs directly. • The shapes of the two datasets showed a variable degree of mismatch in peak locations and skewness. • As a result, RIs by indirect methods showed various patterns of biases from those derived directly. • It is required to make a stricter data-cleaning before applying indirect methods that rely on the central peak. Indirect derivation of reference intervals (RIs) from the laboratory information system (LIS) has been recently pursued. We aimed at evaluating the accuracy of indirectly predicted RIs compared to the RIs established directly from healthy subjects in the nationwide RI study in Turkey, targeting 25 major chemistry analytes. LIS data were retrieved from the laboratory that performed measurements for the direct study. They were cleaned by limiting to outpatients with age 18–65 years, and by allowing only one record per year per patient. Evaluated were four indirect methods of univariate approach: Hoffmann, Bhattacharya, Arzideh, and Wosniok methods. Power transformation of the LIS dataset was performed either using the power (λ) reported by the IFCC global RI study (the first two methods) or using a λ predicted (the last two). Compared to the direct study dataset, the LIS dataset showed a variable degree of alterations in peak location and shape. Consequently, lower-side peak-shifts observed in sodium, albumin, etc. led to lowered RI limits, whereas higher-side peak-shift observed in triglyceride, low-density lipoprotein cholesterol, etc. led to raised RI limits. Overall, 72% (62–81) of the RI limits predicted by indirect methods showed significant biases from direct RIs. However, the biases observed in total cholesterol, lactic dehydrogenase, etc. were attributed to a higher-side age-bias in LIS dataset. After excluding them, the overall proportion of biased RIs was reduced to 47% (38–54). To reduce prediction biases that remained after age adjustment, it is necessary to apply more rigorous data-cleaning before applying indirect methods. [ABSTRACT FROM AUTHOR]

Background: In Ghana, diagnostic laboratories rely on reference intervals (RIs) provided by manufacturers of laboratory analyzers which may not be appropriate. This study aimed to establish RIs for hematological parameters in adult Ghanaian population. Methods: This cross‐sectional study recruited 501 apparently healthy adults from two major urban areas in Ghana based on the protocol by IFCC Committee for Reference Intervals and Decision Limits. Whole blood was tested for complete blood count (CBC) by Sysmex XN‐1000 analyzer, sera were tested for iron and ferritin by Beckman‐Coulter/AU480, for transferrin, vitamin‐B12, and folate was measured by Centaur‐XP/Siemen. Partitioning of reference values by sex and age was guided by "effect size" of between‐subgroup differences defined as standard deviation ratio (SDR) based on ANOVA. RIs were derived using parametric method with application of latent abnormal values exclusion method (LAVE), a multifaceted method of detecting subjects with abnormal results in related parameters. Results: Using SDR ≥ 0.4 as a threshold, RIs were partitioned by sex for platelet, erythrocyte parameters except mean corpuscular constants, and iron markers. Application of LAVE had prominent effect on RIs for majority of erythrocyte and iron parameters. Global comparison of Ghanaian RIs revealed lower‐side shift of RIs for leukocyte and neutrophil counts, female hemoglobin and male platelet count, especially compared to non‐African countries. Conclusion: The LAVE effect on many hematological RIs indicates the need for deliberate secondary exclusion for proper derivation of RIs. Obvious differences in Ghanaian RIs compared to other countries underscore the importance of country‐specific RIs for improved clinical decision‐making. [ABSTRACT FROM AUTHOR]

Objectives To analyze consistency of reference limits and widths of reference intervals (RIs) calculated by six procedures and evaluate a protocol for merging intrainstitutional reference data. Methods The differences between reference limits were compared with "optimal" bias goals. Also, widths of the RIs were compared. RIs were calculated using Mayo-SAS quantile, EP Evaluator, and four International Federation of Clinical Chemistry and Laboratory Medicine methods: parametric and nonparametric (NP) with and without latent abnormal values exclusion (LAVE). Regression parameters from cotested samples were evaluated for harmonizing intrainstitutional reference data. Results Mayo-SAS quintile, LAVE(–)NP, and EP Evaluator generated similar RIs, but these RIs often were wider than RIs from parametric procedures. LAVE procedures generated narrower RIs for nutritional and inflammatory markers. Transformation with regression parameters did not ensure homogeneity of merged data. Conclusions Parametric methods are recommended when inappropriate values cannot be excluded. The nonparametric procedures may generate wider RIs. Data sets larger than 200 are recommended for robust estimates. Caution should be exercised when merging intrainstitutional data. [ABSTRACT FROM AUTHOR]

Background: In 2011, the IFCC Committee on Reference Intervals and Decision Limits (C-RIDL) initiated a worldwide multicenter study on references values facilitating the implementation of country-specific reference intervals (RIs). There has been no well-designed RI study in India. This study aims to derive RIs for 33 major biochemical analytes in carefully selected healthy Indians as defined in C-RIDL protocol. Methods: A total of 512 healthy Indians were recruited. Sera collected from overnight fasting blood samples were measured collectively for the analytes. Multiple regression analysis (MRA) and nested analysis of variance (ANOVA) were used to identify the potential sources of variation (SV) of test results. RI were derived by both parametric and non-parametric methods for comparison. The need for secondary exclusion by latent abnormal values exclusion (LAVE) method was examined. Results: MRA results indicated that both age and BMI were apparent SV for many analytes in both sexes. ANOVA revealed that partition of RIs by gender and age was required for 17 analytes (TC, HDL-C, TG, hsCRP, ALB, AST, ALT, ALP, GGT, TBil, Urea, CRE, UA, Fe, TTR, CK and IgM) and 5 (Glu, ALB, TC, ALP and Urea), respectively. RIs by parametric method were generally narrower than by non-parametric method, reflecting distorted peripheral distributions of test results. The LAVE method had no appreciable effect on RIs possibly due to inconsistency among abnormal values of related analytes. Conclusions: This study has for the first time provided comprehensive RIs information in healthy Indians. The final RIs adopted were those derived by parametric method without LAVE procedure. [ABSTRACT FROM AUTHOR]

Objectives: To analyze consistency of reference limits and widths of reference intervals (RIs) calculated by six procedures and evaluate a protocol for merging intrainstitutional reference data.Methods: The differences between reference limits were compared with "optimal" bias goals. Also, widths of the RIs were compared. RIs were calculated using Mayo-SAS quantile, EP Evaluator, and four International Federation of Clinical Chemistry and Laboratory Medicine methods: parametric and nonparametric (NP) with and without latent abnormal values exclusion (LAVE). Regression parameters from cotested samples were evaluated for harmonizing intrainstitutional reference data.Results: Mayo-SAS quintile, LAVE(-)NP, and EP Evaluator generated similar RIs, but these RIs often were wider than RIs from parametric procedures. LAVE procedures generated narrower RIs for nutritional and inflammatory markers. Transformation with regression parameters did not ensure homogeneity of merged data.Conclusions: Parametric methods are recommended when inappropriate values cannot be excluded. The nonparametric procedures may generate wider RIs. Data sets larger than 200 are recommended for robust estimates. Caution should be exercised when merging intrainstitutional data. [ABSTRACT FROM AUTHOR]

Objectives: Three multicentre studies of reference intervals were conducted recently in Japan. The Committee on Common Reference Intervals of the Japan Society of Clinical Chemistry sought to establish common reference intervals for 40 laboratory tests which were measured in common in the three studies and regarded as well harmonized in Japan.Methods: The study protocols were comparable with recruitment mostly from hospital workers with body mass index ≤28 and no medications. Age and sex distributions were made equal to obtain a final data size of 6345 individuals. Between-subgroup differences were expressed as the SD ratio (between-subgroup SD divided by SD representing the reference interval). Between-study differences were all within acceptable levels, and thus the three datasets were merged.Results: By adopting SD ratio ≥0.50 as a guide, sex-specific reference intervals were necessary for 12 assays. Age-specific reference intervals for females partitioned at age 45 were required for five analytes. The reference intervals derived by the parametric method resulted in appreciable narrowing of the ranges by applying the latent abnormal values exclusion method in 10 items which were closely associated with prevalent disorders among healthy individuals. Sex- and age-related profiles of reference values, derived from individuals with no abnormal results in major tests, showed peculiar patterns specific to each analyte.Conclusion: Common reference intervals for nationwide use were developed for 40 major tests, based on three multicentre studies by advanced statistical methods. Sex- and age-related profiles of reference values are of great relevance not only for interpreting test results, but for applying clinical decision limits specified in various clinical guidelines. [ABSTRACT FROM AUTHOR]