Biological Variation Estimates for Plasma Copeptin and Clinical Implications.

BACKGROUND: Plasma copeptin measurement is useful for the differential diagnoses of polyuria-polydipsia syndrome. It has also been proposed as a prognostic marker for cardiovascular diseases. However, limited information is available about the within- (CVI) and between-subject (CVG) biological variation (BV). This study presents BV estimates for copeptin in healthy individuals. METHODS: Samples were collected weekly from 41 healthy subjects over 5 weeks and analyzed using the BRAHMS Copeptin proAVP KRYPTOR assay after at least 8 h of food and fluid abstinence. Outlier detection, variance homogeneity, and trend analysis were performed followed by CV-ANOVA for BV and analytical variation (CVA) estimation with 95% confidence intervals. Reference change values (RCVs), index of individuality (II), and analytical performance specification (APS) were also calculated. RESULTS: The analysis included 178 results from 20 males and 202 values from 21 females. Copeptin concentrations were significantly higher in males than in females (mean 8.5 vs 5.2 pmol/L, P < 0.0001). CVI estimates were 18.0% (95% CI, 15.4%-21.6%) and 19.0% (95% CI, 16.4%-22.6%), for males and females, respectively; RCVs were -35% (decreasing value) and 54% (increasing value). There was marked individuality for copeptin. No result exceeded the diagnostic threshold (>21.4 pmol/L) for arginine vasopressin resistance. CONCLUSIONS: The availability of BV data allows for refined APS and associated II, and RCVs applicable as aids in the serial monitoring of patients with specific diseases such as heart failure. The BV estimates are only applicable in subjects who abstained from oral intake due to the rapid and marked effects of fluids on copeptin physiology.

Sex-related differences in within-subject biological variation estimates for 22 essential and non-essential amino acids.

BACKGROUND: Measurement of serum amino acid (AA) concentrations is important in particular for the diagnosis and monitoring of inborn errors of AA metabolism. To ensure optimal clinical interpretation of AAs, reliable biological variation (BV) data are essential. In the present study, we derived BV data for 22 non-essential, conditionally essential, and essential AAs and assessed differences in BV of AAs related to sex. METHODS: Morning blood samples were drawn from 66 subjects (31 males and 35 females) once a week for 10 consecutive weeks. All samples were analyzed in duplicate using liquid chromatography-tandem mass-spectrometry. The data were assessed for outliers, trends, normality and variance homogeneity analysis prior to estimating within-subject (CVI) and between-subject (CVG) BV. RESULTS: CVI estimates ranged from 9.0 % for histidine (male) to 33.0 % for taurine (male). CVI estimates in males and females were significantly different for all AAs except for aspartic acid, citrulline and phenylalanine, in most cases higher in females than in males. Apart from for arginine, CVG estimates in males and females were similar. CONCLUSIONS: In this highly powered BV study, we provide updated BV estimates for 22 AAs and demonstrate that for most AAs, CVI estimates differ between males and females, with implications for interpretation and use of AAs in clinical practice.

Biological variation estimates for serum neurofilament light chain in healthy subjects.

OBJECTIVES: Neurofilament light chain (NfL) is an emerging biomarker of neurodegeneration disorders. Knowledge of the biological variation (BV) can facilitate proper interpretation between serial measurements. Here BV estimates for serum NfL (sNfL) are provided. METHODS: Serum samples were collected weekly from 24 apparently healthy subjects for 10 consecutive weeks and analyzed in duplicate using the Siemens Healthineers sNfL assay on the Atellica® IM Analyzer. Outlier detection, variance homogeneity analyses, and trend analysis were performed followed by CV-ANOVA to determine BV and analytical variation (CVA) estimates with 95%CI and the associated reference change values (RCV) and analytical performance specifications (APS). RESULTS: Despite observed differences in sNfL concentrations between males and females, BV estimates remained consistent across genders. Both within-subject BV (CVI) for males (10.7%, 95%CI; 9.2-12.6) and females (9.1%, 95%CI; 7.8-10.9) and between-subject BV (CVG) for males (26.1%, 95%CI; 18.0-45.6) and females (30.2%, 95%CI; 20.9-53.5) were comparable. An index of individuality value of 0.33 highlights significant individuality, indicating the potential efficacy of personalized reference intervals in patient monitoring. CONCLUSIONS: The established BV estimates for sNfL underscore its potential as a valuable biomarker for monitoring neurodegenerative diseases, offering a foundation for improved decision-making in clinical settings.

Personalized and Population-Based Reference Intervals for 48 Common Clinical Chemistry and Hematology Measurands: A Comparative Study.

BACKGROUND: Personalized reference intervals (prRIs) have the potential to improve individual patient follow-up as compared to population-based reference intervals (popRI). In this study, we estimated popRI and prRIs for 48 clinical chemistry and hematology measurands using samples from the same reference individuals and explored the effect of using group-based and individually based biological variation (BV) estimates to derive prRIs. METHODS: 143 individuals (median age 28 years) were included in the study and had fasting blood samples collected once. From this population, 41 randomly selected subjects had samples collected weekly for 5 weeks. PopRIs were estimated according to Clinical Laboratory Standards Institute EP28 and within-subject BV (CVI) were estimated by CV-ANOVA. Data were assessed for trends and outliers prior to calculation of individual prRIs, based on estimates of (a) within-person BV (CVP), (b) CVI derived in this study, and (c) publically available CVI estimates. RESULTS: For most measurands, the individual prRI ranges were smaller than the popRI range, but overall about half the study participants had a prRI wider than the popRI for 5 or more out of 48 measurands. The dispersion of prRIs based on CVP was wider than that of prRIs based on CVI. CONCLUSION: The prRIs derived in our study varied significantly between different individuals, especially if based on CVP. Our results highlight the limitations of popRIs in interpreting test results of individual patients. If sufficient data from a steady-state situation are available, using prRI based on CVP estimates will provide a RI most specific for an individual patient.

Melatonin in preservation solutions prevents ischemic injury in rat kidneys.

Transplantation is lifesaving and the most effective treatment for end-stage organ failure. The transplantation success depends on the functional preservation of organs prior to transplantation. Currently, the University of Wisconsin (UW) and histidine-tryptophan-ketoglutarate (HTK) are the most commonly used preservation solutions. Despite intensive efforts, the functional preservation of solid organs prior to transplantation is limited to hours. In this study, we modified the UW solution containing components from both the UW and HTK solutions and analyzed their tissue-protective effect against ischemic injury. The composition of the UW solution was changed by reducing hydroxyethyl starch concentration and adding Histidine/Histidine-HCl which is the main component of HTK solution. Additionally, the preservation solutions were supplemented with melatonin and glucosamine. The protective effects of the preservation solutions were assessed by biochemical and microscopical analysis at 2, 10, 24, and 72 h after preserving the rat kidneys with static cold storage. Lactate dehydrogenase (LDH) activity in preservation solutions was measured at 2, 10, 24, and 72. It was not detectable at 2 h of preservation in all groups and 10 h of preservation in modified UW+melatonin (mUW-m) and modified UW+glucosamine (mUW-g) groups. At the 72nd hour, the lowest LDH activity (0.91 IU/g (0.63-1.17)) was measured in the mUW-m group. In comparison to the UW group, histopathological damage score was low in modified UW (mUW), mUW-m, and mUW-g groups at 10, 24, and 72 hours. The mUW-m solution at low temperature was an effective and suitable solution to protect renal tissue for up to 72 h.

Personalized reference intervals: from theory to practice.

Using laboratory test results for diagnosis and monitoring requires a reliable reference to which the results can be compared. Currently, most reference data is derived from the population, and patients in this context are considered members of a population group rather than individuals. However, such reference data has limitations when used as the reference for an individual. A patient's test results preferably should be compared with their own, individualized reference intervals (RI), i.e. a personalized RI (prRI).The prRI is based on the homeostatic model and can be calculated using an individual's previous test results obtained in a steady-state situation and estimates of analytical (CVA) and biological variation (BV). BV used to calculate the prRI can be obtained from the population (within-subject biological variation, CVI) or an individual's own data (within-person biological variation, CVP). Statistically, the prediction interval provides a useful tool to calculate the interval (i.e. prRI) for future observation based on previous measurements. With the development of information technology, the data of millions of patients is stored and processed in medical laboratories, allowing the implementation of personalized laboratory medicine. PrRI for each individual should be made available as part of the laboratory information system and should be continually updated as new test results become available.In this review, we summarize the limitations of population-based RI for the diagnosis and monitoring of disease, provide an outline of the prRI concept and different approaches to its determination, including statistical considerations for deriving prRI, and discuss aspects which must be further investigated prior to implementation of prRI in clinical practice.

Within- and between-subject biological variation data for serum zinc, copper and selenium obtained from 68 apparently healthy Turkish subjects.

OBJECTIVES: Trace elements (TrEL) are nutritionally essential components in maintaining health and preventing diseases. There is a lack of reliable biological variation (BV) data for TrELs, required for the diagnosis and monitoring of TrEL disturbances. In this study, we aimed to provide updated within- and between-subject BV estimates for zinc (Zn), copper (Cu) and selenium (Se). METHODS: Weekly serum samples were drawn from 68 healthy subjects (36 females and 32 males) for 10 weeks and stored at -80 °C prior to analysis. Serum Zn, Cu and Se levels were measured using inductively-coupled plasma mass spectrometry (ICP-MS). Outlier and variance homogeneity analyses were performed followed by CV-ANOVA (Røraas method) to determine BV and analytical variation estimates with 95% CI and the associated reference change values (RCV) for all subjects, males and females. RESULTS: Significant differences in mean concentrations between males and females were observed, with absolute and relative (%) differences for Zn at 0.5 µmol/L (3.5%), Cu 2.0 µmol/L (14.1%) and Se 0.06 µmol/L (6.0%). The within-subject BV (CVI [95% CI]) estimates were 8.8% (8.2-9.3), 7.8% (7.3-8.3) and 7.7% (7.2-8.2) for Zn, Cu and Se, respectively. Within-subject biological variation (CVI) estimates derived for male and female subgroups were similar for all three TrELs. Marked individuality was observed for Cu and Se. CONCLUSIONS: The data of this study provides updated BV estimates for serum Zn, Cu and Se derived from a stringent protocol and state of the art methodologies. Furthermore, Cu and Se display marked individuality, highlighting that population based reference limits should not be used in the monitoring of patients.

Personalized reference intervals - statistical approaches and considerations.

For many measurands, physicians depend on population-based reference intervals (popRI), when assessing laboratory test results. The availability of personalized reference intervals (prRI) may provide a means to improve the interpretation of laboratory test results for an individual. prRI can be calculated using estimates of biological and analytical variation and previous test results obtained in a steady-state situation. In this study, we aim to outline statistical approaches and considerations required when establishing and implementing prRI in clinical practice. Data quality assessment, including analysis for outliers and trends, is required prior to using previous test results to estimate the homeostatic set point. To calculate the prRI limits, two different statistical models based on 'prediction intervals' can be applied. The first model utilizes estimates of 'within-person biological variation' which are based on an individual's own data. This model requires a minimum of five previous test results to generate the prRI. The second model is based on estimates of 'within-subject biological variation', which represents an average estimate for a population and can be found, for most measurands, in the EFLM Biological Variation Database. This model can be applied also when there are lower numbers of previous test results available. The prRI offers physicians the opportunity to improve interpretation of individuals' test results, though studies are required to demonstrate if using prRI leads to better clinical outcomes. We recommend that both popRIs and prRIs are included in laboratory reports to aid in evaluating laboratory test results in the follow-up of patients.

Personalized Reference Intervals in Laboratory Medicine: A New Model Based on Within-Subject Biological Variation.

BACKGROUND: The concept of personalized medicine has received widespread attention in the last decade. However, personalized medicine depends on correct diagnosis and monitoring of patients, for which personalized reference intervals for laboratory tests may be beneficial. In this study, we propose a simple model to generate personalized reference intervals based on historical, previously analyzed results, and data on analytical and within-subject biological variation. METHODS: A model using estimates of analytical and within-subject biological variation and previous test results was developed. We modeled the effect of adding an increasing number of measurement results on the estimation of the personal reference interval. We then used laboratory test results from 784 adult patients (>18 years) considered to be in a steady-state condition to calculate personalized reference intervals for 27 commonly requested clinical chemistry and hematology measurands. RESULTS: Increasing the number of measurements had little impact on the total variation around the true homeostatic set point and using ≥3 previous measurement results delivered robust personalized reference intervals. The personalized reference intervals of the study participants were different from one another and, as expected, located within the common reference interval. However, in general they made up only a small proportion of the population-based reference interval. CONCLUSIONS: Our study shows that, if using results from patients in steady state, only a few previous test results and reliable estimates of within-subject biological variation are required to calculate personalized reference intervals. This may be highly valuable for diagnosing patients as well as for follow-up and treatment.

Proteins associated with neutrophil degranulation are upregulated in nasopharyngeal swabs from SARS-CoV-2 patients.

COVID-19 or severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) appeared throughout the World and currently affected more than 9 million people and caused the death of around 470,000 patients. The novel strain of the coronavirus disease is transmittable at a devastating rate with a high rate of severe hospitalization even more so for the elderly population. Naso-oro-pharyngeal swab samples as the first step towards detecting suspected infection of SARS-CoV-2 provides a non-invasive method for PCR testing at a high confidence rate. Furthermore, proteomics analysis of PCR positive and negative naso-oropharyngeal samples provides information on the molecular level which highlights disease pathology. Samples from 15 PCR positive cases and 15 PCR negative cases were analyzed with nanoLC-MS/MS to identify the differentially expressed proteins. Proteomic analyses identified 207 proteins across the sample set and 17 of them were statistically significant. Protein-protein interaction analyses emphasized pathways like Neutrophil degranulation, Innate Immune System, Antimicrobial Peptides. Neutrophil Elastase (ELANE), Azurocidin (AZU1), Myeloperoxidase (MPO), Myeloblastin (PRTN3), Cathepsin G (CTSG) and Transcobalamine-1 (TCN1) were found to be significantly altered in naso-oropharyngeal samples of SARS-CoV-2 patients. The identified proteins are linked to alteration in the innate immune system specifically via neutrophil degranulation and NETosis.

Institutional experience of newborn screening for inborn metabolism disorders by tandem MS in the Turkish population.

Background The tandem mass spectrometry method in the screening of congenital metabolic disorders is not included in routine national newborn screening programmes in Turkey. To evaluate the distribution of acylcarnitines and amino acid levels in normal newborns, establish acylcarnitine and amino acid cut-off levels and further preliminary results of inherited metabolic disorders inferentially in the Turkish population. Methods Newborn screening tests performed by tandem MS from 2016 to 2018 were retrospectively reviewed. The study group included 17,066 newborns born in our hospitals located in various regions of Turkey. Blood samples were obtained from infants older than 24 h of age. Among the 17,066 newborns, the metabolic screening data of 9,994 full-term newborns (>37 weeks) were employed to obtain the percentile distribution of the normal population. The study group (17,066) was screened for 26 types of inborn error of metabolism. Results Our established cut-offs, were compared with the cut-offs determined by Region for Stork Study and Centers for Disease Control. Among the 26 screened disorders, a total of 12 cases (8 amino acid metabolism disorders, 1 urea cycle defect, 2 organic acidaemias and 1 fatty acid oxidation disorder) were identified. Conclusions Because of the high rate of consanguineous marriages in Turkey, the development of a nationwide screening panel is necessary for early detection and management of potentially treatable inherited metabolic disorders.

An Assessment of HbA1c in Diabetes Mellitus and Pre-diabetes Diagnosis: a Multi-centered Data Mining Study.

HbA1c test has been widely used to evaluate glycemic control in patients with diabetes. However, there are controversial results regarding the value of HbA1c in the diagnosis of diabetes mellitus (DM). The present study investigates the diagnostic effectiveness of HbA1c in a large patient group. The oral glucose tolerance test and HbA1c results of 6551 patients (4704 healthy, 1345 pre-diabetes, 502 DM) in 12 different medical centers in Turkey between 2010 and 2016 were examined to understand the effectiveness of HbA1c in the diagnosis of DM. Different Roche systems were used for measuring HbA1c via the immunoturbidimetric method. The DM ROC curves revealed the diagnostic sensitivity, specificity, and AUC of 74.5%, 87.1%, and 0.866 (CI 95% 0.858-0.875), respectively, for HbA1c (at the cut-off 41 mmol/mol, 5.9%). For HbA1c at the universal diagnostic decision value of 48 mmol/mol (6.5%), the sensitivity and specificity were determined as 32.4% and 99.9%, respectively. The ROC curves for fasting plasma glucose (FPG) revealed the diagnostic sensitivity, specificity, and AUC of 71.3%, 85.3%, and 0.853 (CI 95% 0.844-0.861), respectively. However, the ROC curve results for pre-diabetes (HbA1c at the cut-off value of 39 mmol/mol, 5.7%) revealed the diagnostic sensitivity, specificity, and AUC of 45.7%, 76.4%, and 0.641, respectively. Furthermore, it was shown that the changes in HbA1c values due to gender and age had no clinical effect on the diagnosis. According to our results, it remains challenging to suggest HbA1c measurements can have a significant contribution to the FPG measurements. It was found that the sensitivity is specifically low in the assessment of the pre-diabetes data. Additionally, considering the problems associated with Hb1Ac measurements, further studies conducted in different regions by using different methods are required.

A Simple Method for Quantification of Five Urinary Porphyrins, Porphobilinogen and 5-Aminolevulinic Acid, Using Liquid Chromatography Tandem Mass Spectrometry.

Analysis of porphyrins and 5-aminolevulinic acid (ALA), porphobilinogen (PBG) in physiological liquids is required for diagnosis and follow-up of porphyrias. High performance liquid chromatography (HPLC) and liquid chromatography tandem mass spectrometry (LC-MS) methods with higher specificity and sensitivity have been developed. The major disadvantage of those methods is that they require longer extraction times due to their matrix effects. The present study suggests a simple, fast, sensitive, and specific assay for determination of Coproporphyrin, 5-carboxylporphyrin, 6-carboxylporphyrin, 7-carboxylporphyrin, Uroporphyrin I and ALA, PBG in urine sample by direct injection without sample pre-treatment using LC-MS. For the purposes of the present study LC-MS device was set to multiple reaction monitoring (MRM) and positive ion mode. Porphyrins and ALA, porphobilinogen were characterized by their MS/MS product ion, spectra. ALA, PBG and 5 porphyrins were detected simultaneously. Limit of detection for Coproporphyrin, 5-carboxylporphyrin, 6-carboxylporphyrin, 7-carboxylporphyrin, Uroporphyrin I were 2 nmol/L, where it was 5 µmol/L for ALA and 2 µmol/L for porphobilinogen. The present study suggests that the present method is very effective compared to many other available methods for it does not require pre-treatment, provides simultaneous results of ALA, PBG and 5 porphyrins quantitatively in a shorter span of time, and has suitable sensitivity and selectivity. LC-MS technique was used clinically for the determination of urine porphyrin levels.

Sigma metric revisited: True known mistakes.

Six Sigma methodology has been used successfully in industry since the mid-1980s. Unfortunately, the same success has not been achieved in laboratory medicine. In this case, although the multidisciplinary structure of laboratory medicine is an important factor, the concept and statistical principles of Six Sigma have not been transferred correctly from industry to laboratory medicine. Furthermore, the performance of instruments and methods used in laboratory medicine is calculated by a modified equation that produces a value lower than the actual level. This causes unnecessary, increasing pressure on manufacturers in the market. We concluded that accurate implementation of the sigma metric in laboratory medicine is essential to protect both manufacturers by calculating the actual performance level of instruments, and patients by calculating the actual error rates.

Exposure to Perchlorate in Lactating Women and Its Associations With Newborn Thyroid Stimulating Hormone.

Background: Perchlorate, thiocyanate, and nitrate can block iodide transport at the sodium iodide symporter (NIS) and this can subsequently lead to decreased thyroid hormone production and hypothyroidism. NIS inhibitor exposure has been shown to reduce iodide uptake and thyroid hormone levels; therefore we hypothesized that maternal NIS inhibitor exposure will influence both maternal and newborn thyroid function. Methods: Spot urine samples were collected from 185 lactating mothers and evaluated for perchlorate, thiocyanate, and nitrate concentrations. Blood and colostrum samples were collected from the same participants in the first 48 h after delivery. Thyroid hormones and thyroid-related antibodies (TSH, fT3, fT4, anti-TPO, anti-Tg) were analyzed in maternal blood and perchlorate was analyzed in colostrum. Also, spot blood samples were collected from newborns (n = 185) between 48 and 72 postpartum hours for TSH measurement. Correlation analysis was performed to assess the effect of NIS inhibitors on thyroid hormone levels of lactating mothers and their newborns in their first 48 postpartum hours. Results: The medians of maternal urinary perchlorate (4.00 µg/g creatinine), maternal urinary thiocyanate (403 µg/g creatinine), and maternal urinary nitrate (49,117 µg/g creatinine) were determined. Higher concentrations of all three urinary NIS inhibitors (µg/g creatinine) at their 75th percentile levels were significantly correlated with newborn TSH (r = 0.21, p < 0.001). Median colostrum perchlorate level concentration of all 185 participants was 2.30 µg/L. Colostrum perchlorate was not significantly correlated with newborn TSH (p > 0.05); however, there was a significant correlation between colostrum perchlorate level and maternal TSH (r = 0.21, p < 0.01). Similarly, there was a significant positive association between colostrum perchlorate and maternal urinary creatinine adjusted perchlorate (r = 0.32, p < 0.001). Conclusion: NIS inhibitors are ubiquitous in lactating women in Turkey and are associated with increased TSH levels in newborns, thus signifying for the first time that co-exposure to maternal NIS inhibitors can have a negative effect on the newborn thyroid function.

The EuBIVAS: Within- and Between-Subject Biological Variation Data for Electrolytes, Lipids, Urea, Uric Acid, Total Protein, Total Bilirubin, Direct Bilirubin, and Glucose.

BACKGROUND: The European Federation of Clinical Chemistry and Laboratory Medicine European Biological Variation Study (EuBIVAS) has been established to deliver rigorously determined data describing biological variation (BV) of clinically important measurands. Here, EuBIVAS-based BV estimates of serum electrolytes, lipids, urea, uric acid, total protein, total bilirubin, direct bilirubin, and glucose, as well as their associated analytical performance specifications (APSs), are presented. METHOD: Samples were drawn from 91 healthy individuals (38 male, 53 female; age range, 21-69 years) for 10 consecutive weeks at 6 European laboratories. Samples were stored at -80 °C before duplicate analysis of all samples on an ADVIA 2400 (Siemens Healthineers). Outlier and homogeneity analyses were performed, followed by CV-ANOVA on trend-corrected data, when relevant, to determine BV estimates with CIs. RESULTS: The within-subject BV (CVI) estimates of all measurands, except for urea and LDL cholesterol, were lower than estimates available in an online BV database, with differences being most pronounced for HDL cholesterol, glucose, and direct bilirubin. Significant differences in CVI for men and women/women <50 years of age were evident for uric acid, triglycerides, and urea. The CVA obtained for sodium and magnesium exceeded the EuBIVAS-based APS for imprecision. CONCLUSIONS: The EuBIVAS, which is fully compliant with the recently published Biological Variation Data Critical Appraisal Checklist, has produced well-characterized, high-quality BV estimates utilizing a stringent experimental protocol. These new reference data deliver revised and more exacting APS and reference change values for commonly used clinically important measurands, thus having direct relevance to diagnostics manufacturers, service providers, clinical users, and ultimately patients.

Within-subject and between-subject biological variation estimates of 21 hematological parameters in 30 healthy subjects.

BACKGROUND: The complete blood count (CBC) is used to evaluate health status in the contexts of various clinical situations such as anemia, infection, inflammation, trauma, malignancies, etc. To ensure safe clinical application of the CBC, reliable biological variation (BV) data are required. The study aim was to define the BVs of CBC parameters employing a strict protocol. METHODS: Blood samples, drawn from 30 healthy subjects (17 females, 13 males) once weekly for 10 weeks, were analyzed using a Sysmex XN 3000 instrument. The data were assessed for normality, trends, outliers and variance homogeneity prior to coefficient of variation (CV)-analysis of variance (ANOVA). Sex-stratified within-subject (CVI) and between-subjects (CVG) BV estimates were determined for 21 CBC parameters. RESULTS: For leukocyte parameters, with the exception of lymphocytes and basophils, significant differences were found between female/male CVI estimates. The mean values of all erythrocyte-, reticulocyte- and platelet parameters differed significantly between the sexes, except for mean corpuscular hemoglobin concentration, mean corpuscular volume and platelet numbers. Most CVI and CVG estimates appear to be lower than those previously published. CONCLUSIONS: Our study, based on a rigorous protocol, provides updated and more stringent BV estimates for CBC parameters. Sex stratification of data is necessary when exploring the significance of changes in consecutive results and when setting analytical performance specifications.