A new approach for the determination of reference intervals from hospital-based data

Calculation of reference intervals for the concentrations of α-tocopherol and retinol in serum using indirect data-mining procedures

BACKGROUND

Establishing adequate reference intervals (RIs) for vitamins A and E is essential for diagnosing and preventing deficiencies. Due to the current boom in data mining and its easy applicability, more laboratories are establishing RIs using indirect methods. Our study aims to obtain RIs using four indirect data-mining procedures (Bhattacharya, Hoffmann, Kosmic, and RefineR) for vitamins A and E.

MATERIAL AND METHODS

8943 individuals were collected to establish the RIs. After using different data cleaning steps and checking whether these data should be divided according to age and gender based on multiple linear regression and variance component analyses, indirect RIs were calculated using specific Excel spreadsheets or R-packages software.

RESULTS

A total of 2004 records were eligible. For vitamin A, the RIs obtained were (1.11 - 2.68) µmol/L, (1.13 - 2.70) µmol/L, (1.13 - 2.71) µmol/L, and (1.17 - 2.66) µmol/L using the Bhattacharya, Hoffmann, Kosmic and RefineR approaches, respectively. For vitamin E, these intervals were (17.3 - 49.9) µmol/L (Bhattacharya), (17.3 - 48.9) µmol/L (Hoffmann), (19.6 - 50.3) µmol/L (Kosmic), and (19.4 - 50.9) µmol/L (RefineR). In all cases, the RIs were comparable.

CONCLUSIONS

Suitable RIs for vitamins A and E were calculated using four indirect methods that are suitable and adapted to our population's demographic characteristics.

Development of next-generation reference interval models to establish reference intervals based on medical data: current status, algorithms and future consideration

Evidence derived from laboratory medicine plays a pivotal role in the diagnosis, treatment monitoring, and prognosis of various diseases. Reference intervals (RIs) are indispensable tools for assessing test results. The accuracy of clinical decision-making relies directly on the appropriateness of RIs. With the increase in real-world studies and advances in computational power, there has been increased interest in establishing RIs using big data. This approach has demonstrated cost-effectiveness and applicability across diverse scenarios, thereby enhancing the overall suitability of the RI to a certain extent. However, challenges persist when tests results are influenced by age and sex. Reliance on a single RI or a grouping of RIs based on age and sex can lead to erroneous interpretation of results with significant implications for clinical decision-making. To address this issue, the development of next generation of reference interval models has arisen at an historic moment. Such models establish a curve relationship to derive continuously changing reference intervals for test results across different age and sex categories. By automatically selecting appropriate RIs based on the age and sex of patients during result interpretation, this approach facilitates clinical decision-making and enhances disease diagnosis/treatment as well as health management practices. Development of next-generation reference interval models use direct or indirect sampling techniques to select reference individuals and then employed curve fitting methods such as splines, polynomial regression and others to establish continuous models. In light of these studies, several observations can be made: Firstly, to date, limited interest has been shown in developing next-generation reference interval models, with only a few models currently available. Secondly, there are a wide range of methods and algorithms for constructing such models, and their diversity may lead to confusion. Thirdly, the process of constructing next-generation reference interval models can be complex, particularly when employing indirect sampling techniques. At present, normative documents pertaining to the development of next-generation reference interval models are lacking. In summary, this review aims to provide an overview of the current state of development of next-generation reference interval models by defining them, highlighting inherent advantages, and addressing existing challenges. It also describes the process, advanced algorithms for model building, the tools required and the diagnosis and validation of models. Additionally, a discussion on the prospects of utilizing big data for developing next-generation reference interval models is presented. The ultimate objective is to equip clinical laboratories with the theoretical framework and practical tools necessary for developing and optimizing next-generation reference interval models to establish next-generation reference intervals while enhancing the use of medical data resources to facilitate precision medicine.

Indirect estimation of pediatric reference interval via density graph deep embedded clustering

Establishing reference intervals (RIs) for pediatric patients is crucial in clinical decision-making, and there is a critical gap of pediatric RIs in China. However, the direct sampling technique for establishing RIs is resource-intensive and ethically challenging. Indirect estimation methods, such as unsupervised clustering algorithms, have emerged as potential alternatives for predicting reference intervals. This study introduces deep graph clustering methods into indirect estimation of pediatric reference intervals. Specifically, we propose a Density Graph Deep Embedded Clustering (DGDEC) algorithm, which incorporates a density feature extractor to enhance sample representation and provides additional perspectives for distinguishing different levels of health status among populations. Additionally, we construct an adjacency matrix by computing the similarity between samples after feature enhancement. The DGDEC algorithm leverages the adjacency matrix to capture the interrelationships between patients and divides patients into different groups, thereby estimating reference intervals for the potential healthy population. The experimental results demonstrate that when compared to other indirect estimation techniques, our method ensures the predicted pediatric reference intervals in different age and gender groups are closer to the true values while maintaining good generalization performance. Additionally, through ablation experiments, our study confirms that the similarity between patients and the multi-scale density features of samples can effectively describe the potential health status of patients.

Establishment of a reference interval for total carbon dioxide using indirect methods in Chinese populations living in high-altitude areas: A retrospective real-world analysis

BACKGROUND

Hypoxia leads to different concentrations of the bicarbonate buffer system in Tibetan people. Indirect methods were used to establish the reference interval (RI) for total carbon dioxide (tCO2) based on big data from the adult population of Tibet, a high-altitude area in Western China.

METHODS

Anonymous tCO2 test data (n = 442,714) were collected from the People's Hospital of the Tibet Autonomous Region from January 2018, to December 2021. Multiple linear regression and variance component analyses were performed to assess the effects of sex, age, and race on tCO2 levels. Indirect methods, including Hoffmann, Bhattacharya, expectation maximization (EM), kosmic and refineR, were used to calculate the total RI and ethnicity-partitioned RI.

RESULTS

A total of 230,821 real-world tCO2 test results were eligible. Sex, age, and race were significantly associated with the tCO2 levels. The total and ethnically-partitioned RIs estimated using the five indirect methods were comparable. The total RI of tCO2 was 14-24 mmol/L (calculated using Hoffmann and refineR) and 15-24 mmol/L (Bhattacharya, EM and kosmic). For Han nationality, the RIs were 14-25 mmol/L (calculated using Hoffmann and Bhattacharya), 16-23 mmol/L (EM), 15-24 mmol/L (kosmic), and 14.2-24.5 mmol/L (refineR). For the Tibetan population, the RIs were 14-24 mmol/L (calculated using Hoffmann and refineR), 15-24 mmol/L (Bhattacharya and kosmic), and 15-23 mmol/L (EM). The established RIs were significantly lower than those living at lower altitudes area (22-29 mmol/L) that was provided by the manufacturer.

CONCLUSION

The tCO2 RI of the populations living on the Tibetan Plateau was significantly lower than those at the lower altitudes. The RIs established using indirect methods are suitable for clinical applications in Tibet.

Reference intervals: past, present, and future

Clinical laboratory test results alone are of little value in diagnosing, treating, and monitoring health conditions; as such, a clinically actionable cutoff or reference interval is required to provide context for result interpretation. Healthcare practitioners base their diagnoses, follow-up treatments, and subsequent testing on these reference points. However, they may not be aware of inherent limitations related to the definition and derivation of reference intervals. Laboratorians are responsible for providing the reference intervals they report with results. Yet, the establishment and verification of reference intervals using conventional direct methods are complicated by resource constraints or unique patient demographics. To facilitate standardized reference interval best practices, multiple global scientific societies are actively drafting guidelines and seeking funding to promote these initiatives. Numerous national and international multicenter collaborations demonstrate the ability to leverage combined resources to conduct large reference interval studies by direct methods. However, not all demographics are equally accessible. Novel indirect methods are attractive solutions that utilize computational methods to define reference distributions and reference intervals from mixed data sets of pathologic and non-pathologic patient test results. In an effort to make reference intervals more accurate and personalized, individual-based reference intervals are shown to be more useful than population-based reference intervals in detecting clinically significant analyte changes in a patient that might otherwise go unrecognized when using wider, population-based reference intervals. Additionally, continuous reference intervals can provide more accurate ranges as compared to age-based partitions for individuals that are near the ends of the age partition. The advantages and disadvantages of different reference interval approaches as well as the advancement of non-conventional reference interval studies are discussed in this review.

Current status and challenges in establishing reference intervals based on real-world data

Reference intervals (RIs) are the cornerstone for evaluation of test results in clinical practice and are invaluable in judging patient health and making clinical decisions. Establishing RIs based on clinical laboratory data is a branch of real-world data mining research. Compared to the traditional direct method, this indirect approach is highly practical, widely applicable, and low-cost. Improving the accuracy of RIs requires not only the collection of sufficient data and the use of correct statistical methods, but also proper stratification of heterogeneous subpopulations. This includes the establishment of age-specific RIs and taking into account other characteristics of reference individuals. Although there are many studies on establishing RIs by indirect methods, it is still very difficult for laboratories to select appropriate statistical methods due to the lack of formal guidelines. This review describes the application of real-world data and an approach for establishing indirect reference intervals (iRIs). We summarize the processes for establishing iRIs using real-world data and analyze the principle and applicable scope of the indirect method model in detail. Moreover, we compare different methods for constructing growth curves to establish age-specific RIs, in hopes of providing laboratories with a reference for establishing specific iRIs and giving new insight into clinical laboratory RI research. (201 words).

Utilization of five data mining algorithms combined with simplified preprocessing to establish reference intervals of thyroid-related hormones for non-elderly adults

BACKGROUND

Despite the extensive research on data mining algorithms, there is still a lack of a standard protocol to evaluate the performance of the existing algorithms. Therefore, the study aims to provide a novel procedure that combines data mining algorithms and simplified preprocessing to establish reference intervals (RIs), with the performance of five algorithms assessed objectively as well.

METHODS

Two data sets were derived from the population undergoing a physical examination. Hoffmann, Bhattacharya, Expectation Maximum (EM), kosmic, and refineR algorithms combined with two-step data preprocessing respectively were implemented in the Test data set to establish RIs for thyroid-related hormones. Algorithm-calculated RIs were compared with the standard RIs calculated from the Reference data set in which reference individuals were selected following strict inclusion and exclusion criteria. Objective assessment of the methods is implemented by the bias ratio (BR) matrix.

RESULTS

RIs of thyroid-related hormones are established. There is a high consistency between TSH RIs established by the EM algorithm and the standard TSH RIs (BR = 0.063), although EM algorithms seems to perform poor on other hormones. RIs calculated by Hoffmann, Bhattacharya, and refineR methods for free and total triiodo-thyronine, free and total thyroxine respectively are close and match the standard RIs.

CONCLUSION

An effective approach for objectively evaluating the performance of the algorithm based on the BR matrix is established. EM algorithm combined with simplified preprocessing can handle data with significant skewness, but its performance is limited in other scenarios. The other four algorithms perform well for data with Gaussian or near-Gaussian distribution. Using the appropriate algorithm based on the data distribution characteristics is recommended.

Chinese pediatric and adolescent reference intervals of vitamin E based on real-world physical examination data

OBJECTIVES

To establish the reference interval (RI) of vitamin E for Chinese children and adolescents.

MATERIALS AND METHODS

Serum tocopherol samples were examined using high performance liquid chromatography in third-party clinical laboratory institutions. Using real-world data from multi-center clinical laboratory institutions in China, the distribution parameters of vitamin E levels were described and the RI was calculated using three algorithms.

RESULTS

A total of 756,766 cases were included in the analysis, including 435,561 males and 321,205 females. The median of vitamin E in infants younger than 4 years of age initially increased but subsequently decreased; while its levels in children between 4 and 11 years of age remained relatively stable despite progressing in age (approximately 7.4-7.8 mg/L). After the start of puberty, the difference, relative to sex, gradually became apparent, and the median vitamin E levels in females was higher than in males. The differences of vitamin E levels between different regions and samples in different seasons had no clinical significance. The RI of vitamin E for children aged 0-18 years in China was 4.5-11.1 mg/L based on expectation-maximization algorithm. The RI established by the Hoffmann method was 4.6-12.8 mg/L.

CONCLUSION

The age- and sex-specific RIs of vitamin E were established by an indirect approach. The RIs established by EM algorithms could be used as an alternative to establish RIs based on real-world data.

Value Ranges and Clinical Comparisons of Serum DHEA-S, IL-6, and TNF-α in Western Lowland Gorillas

Simple Summary

Biomarkers are molecules found in the body that can indicate current physiological functioning and are frequently used to monitor health and diagnose disease. These biomarkers, such as hormones and immune markers, can provide valuable information on the health and welfare of animals. Knowledge on the normal levels of these biomarkers in various species is a crucial step for monitoring health and understanding disease. In this paper, we report assays and value ranges of biomarkers rarely measured in western lowland gorillas in human care. We also compare concentrations of each biomarker between clinical and non-clinical samples. The levels of the two immune biomarkers were higher in clinical samples, but the levels of the neuroendocrine biomarker were not significantly different between clinical and non-clinical samples. These data contribute toward eventually establishing reference ranges for these biomarkers and help improve our understanding of health and welfare in zoo-housed animals.

Abstract

Physiological data can provide valuable information about the health and welfare of animals. Unfortunately, few validated assays and a lack of information on species-typical levels of circulating biomarkers for wildlife make the measurement, interpretation, and practical application of such data difficult. We validated commercially available kits and calculated reference intervals (herein called “value ranges”) for dehydroepiandrosterone-sulfate (DHEA-S), interleukin-6 (IL-6), and tumor necrosis factor-alpha (TNF-α) in a sample of zoo-housed western lowland gorillas due to the roles these biomarkers play in stress and immune responses. For each biomarker, we present species-specific value ranges for a sample of gorillas in human care (n = 57). DHEA-S did not vary significantly by sex or age, while IL-6 was higher in males and older gorillas and TNF-α was higher in females but not associated with age. We also compared non-clinical with clinical samples (n = 21) to explore whether these biomarkers reflect changes in health status. There was no significant difference between clinical and non-clinical samples for DHEA-S, but both IL-6 and TNF-α were significantly higher in gorillas showing clinical symptoms or prior to death. Additional work is needed to improve our understanding of normal versus clinical variation in these biomarkers, and we encourage continued efforts to identify and validate additional biomarkers that can be used to inform assessments of health and welfare in wildlife.

An indirect approach for reference intervals establishment of immunoglobulin A, G and M: the combination of laboratory database and statistics

Immunoglobulins are affected by sex, age and region, so it is necessary to establish suitable reference intervals (RIs) for clinical diagnosis. Various statistical methods were used to calculate RIs, but there has been a lack of comparison among the methods. Research based on immunoglobulin RIs establishment with various methods would provide a methodological basis for further research. A total of 16,525 individuals were enrolled in the study. Individuals were selected in the medical examination center of First Hospital of Jilin University from 2014 to 2020. The lambda-mu-sigma (LMS) method was performed to evaluate the dynamic changes in analytes. RIs were calculated by parametric, non-parametric, Hoffman method and Bhattacharya method. Sex and age partitions were found for immunoglobulins G and immunoglobulin M. The levels of IgM showed no difference with age in males, but showed differences after 50 years of age in females. Circulating immunoglobulin A concentrations showed an increasing trend with age, and immunoglobulin M showed a fluctuating trend with age. Obvious difference (>5%) was commonly found among the four methods, however, the RIs established by the four methods all passed the verification with a high passing rate. Sex and age differences should be considered for immunoglobulins G and immunoglobulin M in clinical practice. The feasibility of the four indirect methods was proven, which would provides a methodological reference for further studies and benefit the application of clinical data.

Derivation of sex and age-specific reference intervals for clinical chemistry analytes in healthy Ghanaian adults

OBJECTVIES

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).

METHODS

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.

RESULTS

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.

CONCLUSIONS

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.

Comparison of reference distributions acquired by direct and indirect sampling techniques: exemplified with the Pediatric Reference Interval in China (PRINCE) study

Background

Our study aimed to compare the reference distributions of serum creatinine and urea obtained by direct sampling technique and two indirect sampling techniques including the Gaussian Mixture Model (GMM) and the Self-Organizing Map (SOM) clustering based on clinical laboratory records, so that the feasibility as well as the potential limitations of indirect sampling techniques could be clarified.

Methods

The direct sampling technique was used in the Pediatric Reference Interval in China (PRINCE) study, in which 15,150 healthy volunteers aged 0 to 19 years were recruited from 11 provinces across China from January 2017 to December 2018. The indirect sampling techniques were used in the Laboratory Information System (LIS) database of Beijing Children’s Hospital, in which 164,710 outpatients were included for partitioning of potential healthy individuals by GMM or SOM from January to December 2016. The reference distributions of creatinine and urea that were established by the PRINCE study and the LIS database were compared.

Results

The density curves of creatinine and urea based on the PRINCE data and the GMM and SOM partitioned LIS data showed a large overlap. However, deviations were found in reference intervals among the three populations.

Conclusions

Both GMM and SOM can identify potential healthy individuals from the LIS data. The performance of GMM is consistent and stable. However, GMM relies on Gaussian fitting, and thus is not suitable for skewed data. SOM is applicable for high-dimensional data, and is adaptable to data distribution. But it is susceptible to sample size and outlier detection strategy.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12874-022-01596-8.

Establishment of Reference Interval and Aging Model of Homocysteine Using Real-World Data

Objective

The level of Homocysteine (Hcy) in males is generally higher than that of females, but the same reference interval (RI) is often used in clinical practice. This study aims to establish a sex-specific RI of Hcy using five data mining algorithms and compare these results. Furthermore, age-related continuous RI was established in order to show the relationship between Hcy concentration distribution and age.

Methods

A total of 20,801 individuals were included in the study and Tukey method was used to identify outliers in subgroups by sex and age. Multiple linear regression and standard deviation ratio (SDR) was used to determine whether the RI for Hcy needs to be divided by sex and age. Five algorithms including Hoffmann, Bhattacharya, expectation maximization (EM), kosmic and refineR were utilized to establish the RI of Hcy. Generalized Additive Models for Location Scale and Shape (GAMLSS) algorithm was used to determine the aging model of Hcy and calculate the age-related continuous RI.

Results

RI of Hcy needed to be partitioned by sex (SDR = 0.735 > 0.375). RIs established by Hoffmann, Bhattacharya, EM (for females) and kosmic are all within the 95% CI of reference limits established by refine R. The Sex-specific aging model of Hcy showed that the upper limits of the RI of Hcy declined with age beginning at age of 18 and began to rise approximately after age of 40 for females and increased with age for males.

Conclusion

The RI of Hcy needs to be partitioned by sex. The RIs established by the five data mining algorithms showed good consistency. The dynamic sex and age-specific model of Hcy showed the pattern of Hcy concentration with age and provide more personalized tools for clinical decisions.

A novel method to standardise serum IgA measurements shows an increased prevalence of IgA deficiency in young children with recurrent respiratory tract infections

Objectives

While physicians are often confronted with immunoglobulin A (IgA) deficiency in children with recurrent infections, the clinical relevance of this finding is unclear. Large‐scale studies examining the significance of IgA deficiency in children are hampered by differences in techniques for measuring IgA and the physiological increase of IgA with age. Both result in a variety of reference values used for diagnosing IgA deficiency. We propose a new laboratory‐independent method to accurately compare IgA measurements in children of varying ages.

Methods

We present a method to standardise IgA values for age and laboratory differences. We applied this method to a multicentre case–control study of children under the age of seven suffering from recurrent respiratory tract infections (rRTI, cases) and children who had IgA measured as part of coeliac disease screening (controls). We defined IgA deficiency as serum IgA measurements < 2.5% for age‐specific reference values.

Results

We developed reference values for IgA for seven age groups and five different laboratory assays. Using these reference values, IgA measurements from 417 cases and 224 controls were standardised to compare groups. In children aged 2 years and older, IgA deficiency was observed in 2.9% (7/242) of cases and 0% (0/189) of controls (P = 0.02).

Conclusion

We present a method to compare IgA values in cohorts that vary in age and laboratory assay. This way, we showed that IgA deficiency was more prevalent in children with rRTI compared with controls. This implicates that IgA deficiency may be a clinically relevant condition, even in young children.

Establishment of reference intervals of complete blood count for twin pregnancy

BACKGROUND

Twin pregnancy poses a high risk, and its incidence has increased in recent years. Establishment of reference intervals of complete blood count (CBC) for women with twin pregnancies during pregnancy may aid in the prognosis of adverse outcomes.

METHODS

The incidence of complications and the intensity associated with adverse outcomes were analyzed in 1153 cases of twin pregnancy. A total of 253 cases in the twin pregnancy reference cohort were screened from all candidates after complications and adverse pregnancy outcomes were excluded. Complete blood count data were collected during the mid- and late-term of pregnancy and analyzed using SPSS to establish the reference intervals for peripheral blood in twin pregnancy.

RESULTS

Premature rupture of the membrane and pelvic inflammatory disease were highly positively correlated with adverse outcomes, with OR values of 3.31 and 3.81, respectively. Within the interval population with normal outcomes, red blood cell (RBC), hemoglobin (HGB), hematocrit (HCT), and platelet (PLT) values were lower in twin-pregnant women during gestation than in healthy nulligravida women, but the levels of white blood cells (WBC), neutrophils (NEU), and the NEU% increased, especially in the mid-term. The reference intervals of late-term pregnancy were validated using 20 twin pregnancies samples, and then utilized to determine the distinctive CBC characteristics in preterm birth (PTB) pregnancy. Absolute WBC and NEU values increased in PTB pregnancy based on our established reference intervals, which suggests that these may might be prognostic indicators of this adverse outcome.

CONCLUSION

Establishing the reference interval of blood cell-related indicators of normal twin pregnancy is helpful for the monitoring and prognosis of gestation.

Establishment of reference intervals of ten commonly used clinical chemistry analytes: a real-world study in China

Aim: This real-world study was aimed at establishing reference intervals (RIs) of ten commonly used clinical chemistry analytes (total cholesterol, triglycerides, Apo A1, Apo B, creatine kinase (CK), CK isoenzyme MB, glucose, alkaline phosphatase, γ-glutamyltransferase and blood urea nitrogen) in an apparently healthy population in China. Materials & methods: A total of 17,356 healthy participants aged 18-79 years who underwent check-up at MJ Health Check-up Center were included. The establishment of RIs was performed according to the Clinical and Laboratory Standards Institute EP28-A3c guideline. Roche Cobas c701 automatic analyzer (Roche Diagnostics, Mannheim, Germany) was employed to measure the concentrations of analytes. Results: Total cholesterol, triglycerides, Apo B, CK, alkaline phosphatase, glucose, γ-glutamyltransferase and blood urea nitrogen required gender and age-specific partitioning. Conclusion: The RIs established in this study were parallel to current national standards and previous RIs established in Chinese population. Real-world studies may play an important and practical role in the determination of RIs in the future.

Reference ranges for clinical electrophysiology of vision

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.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10633-021-09831-1.

Review of potentials and limitations of indirect approaches for estimating reference limits/intervals of quantitative procedures in laboratory medicine

Reference intervals (RIs) can be determined by direct and indirect procedures. Both approaches identify a reference population from which the RIs are defined. The crucial difference between direct and indirect methods is that direct methods select particular individuals after individual anamnesis and medical examination have confirmed the absence of pathological conditions. These individuals form a reference subpopulation. Indirect methods select a reference subpopulation in which the individuals are not identified. They isolate a reference population from a mixed population of patients with pathological and non-pathological conditions by statistical reasoning.

At present, the direct procedure internationally recommended is the “gold standard”. It has, however, the disadvantage of high expenses which cannot easily be afforded by most medical laboratories. Therefore, laboratories adopt RIs established by direct methods from external sources requiring a high responsibility for transference problems which are usually neglected by most laboratories. These difficulties can be overcome by indirect procedures which can easily be performed by most laboratories without causing economic problems.

The present review focuses on indirect approaches. Various procedures are presented with their benefits and limitations. Preliminary simulation studies indicate that more recently developed concepts are superior to older approaches.

Separating disease and health for indirect reference intervals

The indirect approach to defining reference intervals operates ‘a posteriori’, on stored laboratory data. It relies on being able to separate healthy and diseased populations using one or both of clinical techniques or statistical techniques. These techniques are also fundamental in a priori, direct reference interval approaches. The clinical techniques rely on using clinical data that is stored either in the electronic health record or within the laboratory database, to exclude patients with possible disease. It depends on the investigators understanding of the data and the pathological impacts on tests. The statistical technique relies on identifying a dominant, apparently healthy, typically Gaussian distribution, which is unaffected by the overlapping populations with higher (or lower) results. It depends on having large databases to give confidence in the extrapolation of the narrow portion of overall distribution representing unaffected individuals. The statistical issues involved can be complex, and can result in unintended bias, particularly when the impacts of disease and the physiological variations in the data are under appreciated.

The establishment of neuron-specific enolase reference interval for the healthy population in southwest China

To investigate and establish a reference interval (RI) of neuron-specific enolase (NSE) in southwest China's healthy population by using the laboratory information system database. A total of 86957 periodic health examination individuals of the medical examination center in West China Hospital from 2016 to 2018 were included in the study. We used the Box-Cox conversion combined with the Tukey method to normalize the data and eliminate the outliers, and the normal distribution method and the nonparametric method to estimate the 95% distribution RI. The NSE 95% distribution RI we established in healthy populations in southwest China through normal distribution and nonparametric method were 0-19.64 ng/ml and 0-20.46 ng/ml, respectively. The obtained RIs verification conformed to the standard and was significantly different from the reagent instruction(P < 0.05). The RI established by the nonparametric method was superior to the RI of the normal distribution method and reagent instruction(P < 0.05). We initially established an NSE RI that was suitable for the healthy southwest China population. The Box-Cox conversion combined with the Tukey method and nonparametric method is a reliable and straightforward indirect method for reference interval acquisition, which is suitable for the promotion and application of clinical laboratory.

Determination of age- and sex-specific 99th percentiles for high-sensitive troponin T from patients: an analytical imprecision- and partitioning-based approach

BACKGROUND

Detection of acute myocardial infarction (AMI) is mainly based on a rise of cardiac troponin with at least one value above the 99th percentile upper reference limit (99th URL). However, circulating high-sensitive cardiac troponin T (hs-cTnT) concentrations depend on age, sex and renal function. Using an analytical imprecision-based approach, we aimed to determine age- and sex-specific hs-cTnT 99th URLs for patients without chronic kidney disease (CKD).

METHODS

A 3.8-year retrospective analysis of a hospital laboratory database allowed the selection of adult patients with concomitant plasma hs-cTnT (<300 ng/L) and creatinine concentrations, both assayed twice within 72 h with at least 3 h between measurements. Absence of AMI was assumed when the variation between serial hs-cTnT values was below the adjusted-analytical change limit calculated according to the inverse polynomial regression of analytical imprecision. Specific URLs were determined using Clinical and Laboratory Standards Institute (CLSI) methods, and partitioning was tested using the proportion method, after adjustment for unequal prevalences.

RESULTS

After outlier removal (men: 8.7%; women: 6.6%), 1414 men and 1082 women with estimated glomerular filtration rate (eGFR) ≥60 mL/min/1.73 m2 were assumed as non-AMI. Partitioning into age groups of 18-50, 51-70 and 71-98 years, the hs-cTnT 99th URLs adjusted on French prevalence were 18, 33, 66 and 16, 30, 84 ng/L for men and women, respectively. Age-partitioning was clearly required. However, sex-partitioning was not justified for subjects aged 18-50 and 51-70 years for whom a common hs-cTnT 99th URLs of about 17 and 31 ng/L could be used.

CONCLUSIONS

Based on a laboratory approach, this study supports the need for age-specific hs-cTnT 99th URLs.

Reference percentiles for paired arterial and venous umbilical cord blood gases: An indirect nonparametric approach

BACKGROUND

Reference intervals for arterial and venous umbilical cord blood gas (UCBG) parameters are scarce, are mainly focused on pH, pO2, pCO2 and base deficit, and are usually assessed using parametric tests, despite a generally skewed data distribution. Here, the purpose is to determine reference percentiles for nine parameters of concomitant arterial and venous UCBG (CAV-UCBG) from neonates at birth, using nonparametric tests.

METHODS

Results of CAV-UCBG, assayed over a 4.5-year period, were extracted from a hospital laboratory database for pH, pCO2, pO2, oxygen saturation, concentration of total oxygen, total carbon dioxide, hydrogen carbonate, total haemoglobin, and acid-base excess. Exclusion criteria were: a venous-arterial pH difference <0.02, an arterial-venous pCO2 <0.7 kPa, and a venous pCO2 <2.9 kPa. Nonparametric bivariate kernel density estimations were used for the selection of plots within the 95% percentile surface of the pCO2-to-pH relationship (NBKDE-95P). Outliers from skewed data were removed using an adjusted-Tukey method, and percentiles were calculated according to the CLSI EP28-A3 nonparametric method.

RESULTS

Overall, 31% (5033/16164) of CAV-UCBG were discarded using the three exclusion criteria. Then, 6% (670/11131) of CAV-UCBG were excluded from the NBKDE-95P, and 0.1 to 3.5% outliers were subsequently removed. Depending on the parameter, the 2.5th and 97.5th percentiles from the whole group were similar or slightly narrower compared to reference intervals from other studies, while those from female and male neonates did not differ substantially.

CONCLUSIONS

Using an indirect nonparametric approach, this study proposes new percentiles for parameters from concomitant arterial and venous umbilical cord blood gases.

Widespread Incorrect Implementation of the Hoffmann Method, the Correct Approach, and Modern Alternatives

Objectives

The Hoffmann method is a procedure for reference interval estimation using routine clinical results. Many authors incorrectly prepare Hoffmann plots on a linear rather than normal probability scale. We explore the consequences.

Methods

This was investigated algebraically, by random number simulations (45 simulations, n = 100,000 each) and using clinical data sets. Strategies compared were: Hoffmann's method as originally and incorrectly implemented, Bhattacharya's method, and maximum likelihood (ML). All R source code and data sets are provided.

Results

As the proportion of healthy individuals approaches 1, the incorrect approach generates reference interval estimates of approximately μH ± 1.19 σH delineating the central 77% of the healthy subpopulation, not the central 95%. Inappropriately narrow reference interval estimates were seen on random simulations and clinical data sets. ML methods performed best.

Conclusions

The erroneous variant Hoffmann method should not be used. ML methods outperform others and are not restricted by Gaussian assumptions.

Indirect Reference Intervals: Harnessing the Power of Stored Laboratory Data

Reference intervals are relied upon by clinicians when interpreting their patients' test results. Therefore, laboratorians directly contribute to patient care when they report accurate reference intervals. The traditional approach to establishing reference intervals is to perform a study on healthy volunteers. However, the practical aspects of the staff time and cost required to perform these studies make this approach difficult for clinical laboratories to routinely use. Indirect methods for deriving reference intervals, which utilise patient results stored in the laboratory's database, provide an alternative approach that is quick and inexpensive to perform. Additionally, because large amounts of patient data can be used, the approach can provide more detailed reference interval information when multiple partitions are required, such as with different age-groups. However, if the indirect approach is to be used to derive accurate reference intervals, several considerations need to be addressed. The laboratorian must assess whether the assay and patient population were stable over the study period, whether data 'clean-up' steps should be used prior to data analysis and, often, how the distribution of values from healthy individuals should be modelled. The assumptions and potential pitfalls of the particular indirect technique chosen for data analysis also need to be considered. A comprehensive understanding of all aspects of the indirect approach to establishing reference intervals allows the laboratorian to harness the power of the data stored in their laboratory database and ensure the reference intervals they report are accurate.

Indirect methods for reference interval determination - review and recommendations

Reference intervals are a vital part of the information supplied by clinical laboratories to support interpretation of numerical pathology results such as are produced in clinical chemistry and hematology laboratories. The traditional method for establishing reference intervals, known as the direct approach, is based on collecting samples from members of a preselected reference population, making the measurements and then determining the intervals. An alternative approach is to perform analysis of results generated as part of routine pathology testing and using appropriate statistical techniques to determine reference intervals. This is known as the indirect approach. This paper from a working group of the International Federation of Clinical Chemistry (IFCC) Committee on Reference Intervals and Decision Limits (C-RIDL) aims to summarize current thinking on indirect approaches to reference intervals. The indirect approach has some major potential advantages compared with direct methods. The processes are faster, cheaper and do not involve patient inconvenience, discomfort or the risks associated with generating new patient health information. Indirect methods also use the same preanalytical and analytical techniques used for patient management and can provide very large numbers for assessment. Limitations to the indirect methods include possible effects of diseased subpopulations on the derived interval. The IFCC C-RIDL aims to encourage the use of indirect methods to establish and verify reference intervals, to promote publication of such intervals with clear explanation of the process used and also to support the development of improved statistical techniques for these studies.

Reference Intervals of and Relationships among Essential Trace Elements in Whole Blood of Children Aged 0-14 years

BACKGROUND

Essential trace elements are vital to human health. In this study, our aim was to establish reference intervals of and to evaluate relationships among Ca, Fe, Cu, Mg, and Zn for children.

METHODS

We collected blood samples of 3210 children aged 0-14 years from Lu'an, China, and concentrations of the above elements were determined by atomizer absorption spectrophotometer. A nonparametric method was used to establish the reference intervals.

RESULTS

Gender-related differences in concentrations were not statistically significant for the elements, except for Fe. There were strong positive and negative correlations between age and Fe (R = 0.305, P < 0.001), Zn (R = 0.573, P < 0.001); and age and Ca (R = -0.372, P < 0.001), Cu (R = -0.127, P < 0.001), respectively. Correlations between Ca-Mg (r = 0.222~0.384, P < 0.001), Fe-Mg (r = 0.495~0.614, P < 0.001), and Fe-Zn (r = 0.239~0.471, P < 0.001) were the strongest compared with others. In multivariable linear regression, after adjusted for confounding factors, the associations between Zn-Fe and Mg-Fe were the strongest with per concentration quintile increase of Fe caused Zn and Mg increasing by 4.19% (β = 0.041; 95% CI: 0.037, 0.045; P < 0.001) and 3.87% (β = 0.038; 95% CI: 0.036, 0.040; P < 0.001), respectively.

CONCLUSIONS

Gender- and age-based reference intervals of Ca, Fe, Cu, Mg, and Zn for children were established, and correlations between them were quite complex. More works are needed to illuminate these relationships and their impacts on children's health.

A reference interval study for common biochemical analytes in Eastern Turkey: a comparison of a reference population with laboratory data mining

Introduction

The aim of this study was to define the reference intervals (RIs) in a Turkish population living in Northeast Turkey (Erzurum) for 34 analytes using direct and indirect methods. In the present study, the regional RIs obtained were compared with other RI studies, primarily the nationwide study performed in Turkey.

Materials and methods

For the direct method, 435 blood samples were collected from a healthy group of females (N = 218) and males (N = 217) aged between 18 and 65 years. The sera were analysed in Ataturk University hospital laboratory using Roche reagents and analysers for 34 analytes. The data from 1,366,948 records were used to calculate the indirect RIs using a modified Bhattacharya method.

Results

Significant gender-related differences were observed for 17 analytes. There were also some apparent differences between RIs derived from indirect and direct methods particularly in some analytes (e.g. gamma-glutamyltransferase, creatine kinase, LDL-cholesterol and iron). The RIs derived with the direct method for some, but not all, of the analytes were generally comparable with the RIs reported in the nationwide study and other previous studies in Turkey.There were large differences between RIs derived by the direct method and the expected values shown in the kit insert (e.g. aspartate aminotransferase, total-cholesterol, HDL-cholesterol, and vitamin B12).

Conclusions

These data provide region-specific RIs for 34 analytes determined by the direct and indirect methods. The observed differences in RIs between previous studies could be related to nutritional status and environmental factors.

Reference intervals: current status, recent developments and future considerations

Reliable and accurate reference intervals (RIs) for laboratory analyses are an integral part of the process of correct interpretation of clinical laboratory test results. RIs given in laboratory reports have an important role in aiding the clinician in interpreting test results in reference to values for healthy populations. Since the 1980s, the International Federation of Clinical Chemistry (IFCC) has been proactive in establishing recommendations to clarify the true significance of the term 'RIs, to select the appropriate reference population and statistically analyse the data. The C28-A3 guideline published by the Clinical and Laboratory Standards Institute (CLSI) and IFCC is still the most widely-used source of reference in this area. In recent years, protocols additional to the Guideline have been published by the IFCC, Committee on Reference Intervals and Decision Limits (C-RIDL), including all details of multicenter studies on RIs to meet the requirements in this area. Multicentric RIs studies are the most important development in the area of RIs. Recently, the C-RIDL has performed many multicentric studies to obtain common RIs. Confusion of RIs and clinical decision limits (CDLs) remains an issue and pediatric and geriatric age groups are a significant problem. For future studies of RIs, the genetic effect would seem to be the most challenging area. 
The aim of the review is to present the current theory and practice of RIs, with special emphasis given to multicenter RIs studies, RIs studies for pediatric and geriatric age groups, clinical decision limits and partitioning by genetic effects on RIs.

Reference intervals in avian and exotic hematology

Historically, reference intervals (RI) have come from many sources and been generated by several methods and sample sizes. As RI generation has matured in human laboratory medicine, important guidelines have been adopted in veterinary medicine. Although meeting the goals of these guidelines may be difficult, especially with avian and exotic species, sets of 20 to 40 samples can be used with proper statistical calculations, and other viable alternatives have been examined. The adoption and knowledge of these different methods are important to make a positive move forward in RI generation for special species.

Derivation of pediatric within-individual biological variation by indirect sampling method: an LMS approach

OBJECTIVES

Pediatric within-individual biological variation (CVi) is a challenge to derive by direct sampling due to clinical, logistical, and ethical barriers.

METHODS

Laboratory results of 22 basic biochemistry tests performed on 9,356 children who visited primary care physicians more than once over a year were obtained from a large laboratory network in Australia. The CVi were calculated as (CVT (2) - CVa (2))(0.5), where CVT was the coefficient of variation between repeat measurements and CVa was the analytical imprecision. Smoothed 50th centile (median) CVi charts were derived using the LMS ChartMaker Light software (Medical Research Council, Cambridge, England) with L, M, and S parameters fixed at 3.0, 3.0, and 3.0 equivalent degrees of freedom, respectively.

RESULTS

In general, the median CVi trends for this pediatric cohort remained relatively stable with increasing age. Only aspartate aminotransferase, globulin, phosphate, urea, and creatinine had differences between the highest and lowest median CVi of more than 30%. The differences between the child and adult CVi were relatively small. Nearly all the analytes had child to adult CVi ratios of 1.0 ± 0.5.

CONCLUSIONS

The median CVi derived from patients with only two repeat biochemistry measurements may be considered reasonable estimates of CVi among children seeking treatment at primary care settings. The LMS approach allowed visualization of the continuous trends of CVi with age and extended the pediatric CVi estimation to younger than 4 years.

Reference intervals of several renal and hepatic function parameters for apparently healthy adults from Eastern China

BACKGROUND

Biochemical substances relating to renal and hepatic function are influenced not only by individual factors such as gender, lifestyle, and age but also by ecological factors, such as altitude, climate, and ethnic background. The purpose of the present study was to establish reference intervals for 16 biochemical substances relating to renal and hepatic function in healthy Chinese adults.

METHODS

A total of 2,405 apparently healthy individuals (18-77 years of age) were chosen as reference individuals in the present study. The 16 biochemical substances relating to renal and hepatic function were analyzed using a HITACHI RL7600 analyzer. The reference intervals were established using nonparametric methods to estimate the 2.5 and 97.5 percentiles of the distribution as the lower and the upper limits, respectively.

RESULTS

Age- and gender-appropriate reference intervals were established for some biochemical substances relating to renal and hepatic function in healthy Chinese adults.

CONCLUSION

The reference intervals established in this study can provide a useful clinical tool for the assessment of the kidney and liver damage. In addition, the established reference intervals can be adopted in other clinical laboratories after further validation.

The theory of reference values: an unfinished symphony

The history of the theory of reference values can be written as an unfinished symphony. The first movement, allegro con fuoco, played from 1960 to 1980: a mix of themes devoted to the study of biological variability (intra-, inter-individual, short- and long-term), preanalytical conditions, standardization of analytical methods, quality control, statistical tools for deriving reference limits, all of them complex variations developed on a central melody: the new concept of reference values that would replace the notion of normality whose definition was unclear. Additional contributions (multivariate reference values, use of reference limits from broad sets of patient data, drug interferences) conclude the movement on the variability of laboratory tests. The second movement, adagio, from 1980 to 2000, slowly develops and implements initial works. International and national recommendations were published by the IFCC-LM (International Federation of Clinical Chemistry and Laboratory Medicine) and scientific societies [French (SFBC), Spanish (SEQC), Scandinavian societies…]. Reference values are now topics of many textbooks and of several congresses, workshops, and round tables that are organized all over the world. Nowadays, reference values are part of current practice in all clinical laboratories, but not without difficulties, particularly for some laboratories to produce their own reference values and the unsuitability of the concept with respect to new technologies such as HPLC, GCMS, and PCR assays. Clinicians through consensus groups and practice guidelines have introduced their own tools, the decision limits, likelihood ratios and Reference Change Value (RCV), creating confusion among laboratorians and clinicians in substituting reference values and decision limits in laboratory reports. The rapid development of personalized medicine will eventually call for the use of individual reference values. The beginning of the second millennium is played allegro ma non-troppo from 2000 to 2012: the theory of reference values is back into fashion. The need to revise the concept is emerging. The manufacturers make a friendly pressure to facilitate the integration of Reference Intervals (RIs) in their technical documentation. Laboratorians are anxiously awaiting the solutions for what to do. The IFCC-LM creates Reference Intervals and Decision Limits Committee (C-RIDL) in 2005. Simultaneously, a joint working group IFCC-CLSI is created on the same topic. In 2008 the initial recommendations of IFCC-LM are revised and new guidelines are published by the Clinical and Laboratory Standards Institute (CLSI C28-A3). Fundamentals of the theory of reference values are not changed, but new avenues are explored: RIs transference, multicenter reference intervals, and a robust method for deriving RIs from small number of subjects. Concomitantly, other statistical methods are published such as bootstraps calculation and partitioning procedures. An alternative to recruiting healthy subjects proposes the use of biobanks conditional to the availability of controlled preanalytical conditions and of bioclinical data. The scope is also widening to include veterinary biology! During the early 2000s, several groups proposed the concept of 'Universal RIs' or 'Global RIs'. Still controversial, their applications await further investigations. The fourth movement, finale: beyond the methodological issues (statistical and analytical essentially), important questions remain unanswered. Do RIs intervene appropriately in medical decision-making? Are RIs really useful to the clinicians? Are evidence-based decision limits more appropriate? It should be appreciated that many laboratory tests represent a continuum that weakens the relevance of RIs. In addition, the boundaries between healthy and pathological states are shady areas influenced by many biological factors. In such a case the use of a single threshold is questionable. Wherever it will apply, individual reference values and reference change values have their place. A variation on an old theme! It is strange that in the period of personalized medicine (that is more stratified medicine), the concept of reference values which is based on stratification of homogeneous subgroups of healthy people could not be discussed and developed in conjunction with the stratification of sick patients. That is our message for the celebration of the 50th anniversary of Clinical Chemistry and Laboratory Medicine. Prospects are broad, enthusiasm is not lacking: much remains to be done, good luck for the new generations!

Total protein measurement in canine cerebrospinal fluid: agreement between a turbidimetric assay and 2 dye-binding methods and determination of reference intervals using an indirect a posteriori method

BACKGROUND

In veterinary clinical laboratories, qualitative tests for total protein measurement in canine cerebrospinal fluid (CSF) have been replaced by quantitative methods, which can be divided into dye-binding assays and turbidimetric methods. There is a lack of validation data and reference intervals (RIs) for these assays.

OBJECTIVES

The aim of the present study was to assess agreement between the turbidimetric benzethonium chloride method and 2 dye-binding methods (Pyrogallol Red-Molybdate method [PRM], Coomassie Brilliant Blue [CBB] technique) for measurement of total protein concentration in canine CSF. Furthermore, RIs were determined for all 3 methods using an indirect a posteriori method.

METHODS

For assay comparison, a total of 118 canine CSF specimens were analyzed. For RIs calculation, clinical records of 401 canine patients with normal CSF analysis were studied and classified according to their final diagnosis in pathologic and nonpathologic values.

RESULTS

The turbidimetric assay showed excellent agreement with the PRM assay (mean bias 0.003 g/L [-0.26-0.27]). The CBB method generally showed higher total protein values than the turbidimetric assay and the PRM assay (mean bias -0.14 g/L for turbidimetric and PRM assay). From 90 of 401 canine patients, nonparametric reference intervals (2.5%, 97.5% quantile) were calculated (turbidimetric assay and PRM method: 0.08-0.35 g/L (90% CI: 0.07-0.08/0.33-0.39); CBB method: 0.17-0.55 g/L (90% CI: 0.16-0.18/0.52-0.61). Total protein concentration in canine CSF specimens remained stable for up to 6 months of storage at -80°C.

CONCLUSIONS

Due to variations among methods, RIs for total protein concentration in canine CSF have to be calculated for each method. The a posteriori method of RIs calculation described here should encourage other veterinary laboratories to establish RIs that are laboratory-specific.

Use of an indirect sampling method to produce reference intervals for hematologic and biochemical analyses in psittaciform species

As with other animal species, comprehensive reference intervals (RI) for psittaciform species are rare and plagued by common issues, including sparse information regarding methods used to analyze specimens, low sample sizes, and improper statistical analyses. The purpose of this study was to examine the use of an indirect sampling method of RI generation from several years of data collected from specimens of multiple psittaciform species submitted to a veterinary diagnostic laboratory. These data were unselected for health status. A previously published method for indirect RI generation was applied to data collected for routine hematologic and biochemical analyses. Seven species groups were examined, and sample size ranged from 346 to 2358. Results showed that RI varied by species and appeared to represent a broader range than expected compared with other RI and traditional clinical expectations for core health assessments, such as total white blood cell count and white blood cell differential results. Some biochemical results reflected more narrow ranges, and a few were consistent with other published ranges. The intervals were likely influenced by changes related to stress and underlying disease. The results of the current study reflect the imprecision of this method related to data obtained from the population served by this laboratory. Overall, this method is not suitable for the production of comprehensive RI, although it may provide rough estimates for some limited analyses until traditional RI can be generated.

Robust reference intervals for liver function test (LFT) analytes in newborns and infants

Background

Reference intervals (RIs) are ranges of upper and lower limits of a given analyte which are used for a laboratory test to determine whether a disease is present or absent or to know if the patient is at risk for future disease states. In Ethiopia, a country with highly diversified population groups and geographical sites, there are no established RIs to metabolic analytes including the liver function test (LFT) analytes for the pediatric population though it has been known that liver function assessment in this population is vital as a result of varied vulnerability to both endogenous and xenobiotic substances.

Methods

A cross sectional study was conducted in Tikur Anbessa Specialized Hospital (TASH) and Teklehaymanot Health Center (THC) from November 2010 to April 2011. 117 cord blood (from newborns) and venous blood samples (from infants) were collected and analyzed using HumaStar 300. All pre-analytical, analytical and post-analytical aspects were thoroughly controlled. A robust, CLSI/ IFCC recommended, method was used for the determination of upper and lower end points covering 95% of the reference values of each analyte with respective 90% CIs using MedCalc® software.

Results

Combined RIs for newborns and infants were established for albumin, AST, ALP, direct bilirubin and total bilirubin to be 3.88-5.82 g/dl, 16.1-55.4U/l, 130-831U/l, <0.41 mg/dl and <1.37 mg/dl respectively. But, separated RIs were indicated for ALT and GGT as 1.2-23.1U/l and 6.94-24.8U/l ALT; and 30.6-160.7U/L and 10–28.2U/l GGT for newborns and infants respectively. Some maternal and infantile factors were identified to affect the values of analytes.

Conclusion

Almost all analytes were different from previously reported values for other target population of similar age group, kit insert values and adult values. So, interpretation of values of these analytes in newborns and infants of Ethiopian population sounds better to be performed by using such RIs taking the effect of some maternal and infantile factors in to account.

Indirect reference intervals of plasma and serum thyrotropin (TSH) concentrations from intra-laboratory data bases from several German and Italian medical centres

BACKGROUND

The dogma of establishing intra-laboratory reference limits (RLs) and their periodic review cannot be fulfilled by most laboratories due to the expenses involved. Thus, most laboratories adopt external sources for their RLs, often neglecting the problems of transferability. This is particularly problematic for analytes with a large diversity of existing RLs, as for example thyrotropin (TSH). Several attempts were taken to derive RLs from the large data pools stored in modern laboratory information systems. These attempts were further developed to a more sophisticated indirect procedure. The new approach can be considered a combined concept because it pre-excludes some subjects by direct criteria a-posterior. In the current study, the applicability of the new concept for modern protein bindings assays was examined for estimating RLs of serum and plasma TSH with data sets from several German and Italian laboratories.

METHODS

A smoothed kernel density function was estimated for the distribution of the total mixed data of the sample group (combined data of non-diseased and diseased subjects). It was assumed that the "central" part of the distribution of all data represents the non-diseased ("healthy") population. The central part was defined by truncation points using an optimisation method, and was used to estimate a Gaussian distribution of the values of presumably non-diseased subjects after Box-Cox transformation of the empirical data. This distribution was now considered as the distribution of the non-diseased subgroup. The percentiles of this parametrical distribution were calculated to obtain RLs.

RESULTS

RLs determined by the indirect combined decomposition technique led to similar RLs as found by several recent study reports using a direct method according to international recommendations. Furthermore, the RLs obtained from 13 laboratories in two different European regions reflected the well-known differences of various analytical procedures. Stratification for gender and age was necessary in contrast to earlier reports. With increasing age, an increase of the upper RL and the reference range was observed. Hospitalisation also affected the RLs. Common RLs appeared acceptable only within the same analytical systems. Some laboratories used RLs which were not appropriate for the population served.

CONCLUSIONS

The proposed strategy of combining exclusion criteria with a resolution technique led to retrospective RLs from intra-laboratory data pools for TSH which were comparable with directly determined RLs. Differences between laboratories were due primarily to the well-known bias of the different analytical procedures and to the status of the population.

Reference Value Advisor: a new freeware set of macroinstructions to calculate reference intervals with Microsoft Excel

International recommendations for determination of reference intervals have been recently updated, especially for small reference sample groups, and use of the robust method and Box-Cox transformation is now recommended. Unfortunately, these methods are not included in most software programs used for data analysis by clinical laboratories. We have created a set of macroinstructions, named Reference Value Advisor, for use in Microsoft Excel to calculate reference limits applying different methods. For any series of data, Reference Value Advisor calculates reference limits (with 90% confidence intervals [CI]) using a nonparametric method when n≥40 and by parametric and robust methods from native and Box-Cox transformed values; tests normality of distributions using the Anderson-Darling test and outliers using Tukey and Dixon-Reed tests; displays the distribution of values in dot plots and histograms and constructs Q-Q plots for visual inspection of normality; and provides minimal guidelines in the form of comments based on international recommendations. The critical steps in determination of reference intervals are correct selection of as many reference individuals as possible and analysis of specimens in controlled preanalytical and analytical conditions. Computing tools cannot compensate for flaws in selection and size of the reference sample group and handling and analysis of samples. However, if those steps are performed properly, Reference Value Advisor, available as freeware at http://www.biostat.envt.fr/spip/spip.php?article63, permits rapid assessment and comparison of results calculated using different methods, including currently unavailable methods. This allows for selection of the most appropriate method, especially as the program provides the CI of limits. It should be useful in veterinary clinical pathology when only small reference sample groups are available.

Steroid assays in paediatric endocrinology

Most steroid disorders of the adrenal cortex come to clinical attention in childhood and in order to investigate these problems, there are many challenges to the laboratory which need to be appreciated to a certain extent by clinicians. The analysis of sex steroids in biological fluids from neonates, over adrenarche and puberty present challenges of specificities and concentrations often in small sample sizes. Different reference ranges are also needed for interpretations. For around 40 years, quantitative assays for the steroids and their regulatory peptide hormones have been possible using immunoassay techniques. Problems are recognised and this review aims to summarise the benefits and failings of immunoassays and introduce where tandem mass spectrometry is anticipated to meet the clinical needs for steroid analysis in paediatric endocrine investigations. It is important to keep a dialogue between clinicians and the laboratory, especially when any laboratory result does not make sense in the clinical investigation.