Optimization of hemolysis, icterus and lipemia interference thresholds for 35 clinical chemistry assays.

OBJECTIVES: Interference of chemistry assays by hemolysis, icterus and lipemia (HIL) was investigated on the Abbott Alinity c system. We sought to empirically establish optimized HIL index thresholds for the purposes of reporting HIL interference in a hospital laboratory and advising clinicians on the interpretation of laboratory results in the presence of hemolysis, icterus or lipemia. METHODS: HIL index values measured by spectrophotometry were compared with concentrations of hemoglobin, bilirubin and Intralipid. HIL interference of 35 Abbott Alinity chemistry assays was subsequently investigated by pairwise comparison of test results in pooled serum or plasma with those in test preparations spiked with hemolysate, bilirubin or Intralipid. Data generated from the interference experiments were critically assessed according to assay-specific acceptance criteria adapted from multiple sources, and optimized thresholds for HIL indices were established. RESULTS: Correlations between HIL index values and their corresponding concentrations of hemoglobin, bilirubin and Intralipid were, in general, very good within the ranges of interferent concentrations tested. Hemolysis significantly affected 12 of 35 assays, whereas bilirubin and Intralipid interfered with four and three assays, respectively. Both the direction and magnitude of Intralipid interference with the direct bilirubin assay were dependent on the concentrations of the analyte. CONCLUSIONS: HIL interference of the Abbott Alinity clinical chemistry assays investigated in this study was not uncommon. At present, there are no universally accepted criteria for defining significant assay interference for clinical practice. In establishing acceptance criteria for defining assay interference, each assay should be assessed according to both analytical criteria and clinical relevance.

Reporting unit size and measurement uncertainty: current Australian practice in clinical chemistry and haematology.

In this study we aimed to compare the reporting unit size used by Australian laboratories for routine chemistry and haematology tests to the unit size used by learned authorities and in standard laboratory textbooks and to the justified unit size based on measurement uncertainty (MU) estimates from quality assurance program data. MU was determined from Royal College of Pathologists of Australasia (RCPA) - Australasian Association of Clinical Biochemists (AACB) and RCPA Haematology Quality Assurance Program survey reports. The reporting unit size implicitly suggested in authoritative textbooks, the RCPA Manual, and the General Serum Chemistry program itself was noted. We also used published data on Australian laboratory practices.The best performing laboratories could justify their chemistry unit size for 55% of analytes while comparable figures for the 50% and 90% laboratories were 14% and 8%, respectively. Reporting unit size was justifiable for all laboratories for red cell count, >50% for haemoglobin but only the top 10% for haematocrit. Few, if any, could justify their mean cell volume (MCV) and mean cell haemoglobin concentration (MCHC) reporting unit sizes.The reporting unit size used by many laboratories is not justified by present analytical performance. Using MU estimates to determine the reporting interval for quantitative laboratory results ensures reporting practices match local analytical performance and recognises the inherent error of the measurement process.

The relationship between measurement uncertainty and reporting interval.

BACKGROUND: Measurement uncertainty (MU) estimates can be used by clinicians in result interpretation for diagnosis and monitoring and by laboratories in assessing assay fitness for use and analytical troubleshooting. However, MU is not routinely used to assess the appropriateness of the analyte reporting interval. We describe the relationship between MU and the analyte reporting interval. METHODS AND RESULTS: The reporting interval R is the smallest unit of measurement chosen for clinical reporting. When choosing the appropriate value for R, it is necessary that the reference change values and expanded MU values can be meaningfully calculated. Expanded MU provides the tighter criterion for defining an upper limit for R. This limit can be determined as R ≤ k·SDa/1.9, where SDa is the analytical standard deviation and k is the coverage factor (usually 2). CONCLUSION: Using MU estimates to determine the reporting interval for quantitative laboratory results ensures that reporting practices match local analytical performance and recognizes the inherent error of the measurement process.

Correcting laboratory results for the effects of interferences: an approach incorporating uncertainty of measurement.

BACKGROUND: Results of numerical pathology tests may be subject to interference and many laboratories identify such interferences and withhold results or issue warnings if clinically erroneous results may be issued. Some laboratories choose to correct for the effect of interferences, with the uncertainty of the correction noted as a limitation in this process. We investigate the effect of correcting for the effect of interferences on the ability to release results within defined error goals using the effect of in-vitro haemolysis on serum potassium measurement as an example. METHODS: A model was developed to determine the uncertainty of a result corrected for the effect of an interferent with a linear relationship between concentration and effect. The model was used to assess the effect of correction on the results which could be released within specified accuracy criteria. RESULTS: Using the effects of haemolysis on potassium results as an example, the maximum amount of haemolysis in a sample that would change the result by > 0.5 mmol/L, with a frequency of 5%, was increased from approximately 1100 mg/L (no correction) to 8000 mg/L (with correction). CONCLUSIONS: With modelling of the factors related to the uncertainties of results in the presence of interferences, it is possible to release results in the presence of significantly higher concentrations of interferences after correction than without correction. Correction of a result for a known bias and allowance for the uncertainty of the correction can be considered consistent with the guide to the expression of uncertainty in measurement (GUM).

Reference interval studies: what is the maximum number of samples recommended?

BACKGROUND: Little attention has been paid to the maximum number of specimens for reference interval calculation, i.e., the number of specimens beyond which there is no further benefit in reference interval calculation. We present a model for the estimation of the maximum number of specimens for reference interval studies based on setting the 90% confidence interval of the reference limits to be equal to the analyte reporting interval. METHODS: Equations describing the bounds on the upper and lower 90% confidence intervals for logarithmically transformed and untransformed data were derived and applied to determine the maximum number of specimens required to calculate a reference interval for 12 common chemistry and hematology analytes. RESULTS: Maximum sample sizes ranged from 126 to 18,171 and depended on the standard deviation of the population, any transformation involved and on the chosen reporting interval. CONCLUSIONS: This paper demonstrates the importance of the influence of reporting interval on reference intervals. Using this technique can reduce the cost of determining a reference interval by identifying the maximum number of specimens required.

Differences in serum potassium concentrations between Chinese, Indians and Malays.

BACKGROUND: It has been suggested that potassium concentrations may vary between different geographical regions, possibly reflecting ethnic differences in potassium status. This study compared the serum potassium concentrations of three Asian ethnicities in a single geographical location. METHODS: Details of simultaneous serum potassium, creatinine, cholesterol, triglyceride and serum index measurements for samples from polyclinics and health screening were extracted for multivariable linear regression. Haemolysed and duplicate patient samples were excluded. Separate analysis was performed based on measurement platform (Roche or Beckman-Coulter) and patient location. RESULTS: Eighty-five thousand nine hundred and ninety-seven records met the inclusion criteria. When controlled for age, gender, serum creatinine, cholesterol and triglyceride, the average serum potassium concentration in Indians was 0.13-0.16 mmol/L higher than in Malays, who in turn had average serum potassium concentrations 0.05-0.06 mmol/L higher than Chinese when controlled for age, gender, serum creatinine, cholesterol and triglyceride concentrations. For patients undergoing health screening, the average serum potassium concentration in Indians and Malays was 0.12 mmol/L higher than in Chinese. CONCLUSIONS: Chinese individuals have lower average serum potassium concentrations than Indians and Malays. This may have clinical implications in relation to the high occurrence of thyrotoxic hypokalaemic paralysis and the aetiology of sudden unexplained death syndrome (SUDS) in Asians.

Circannual variation in glycohemoglobin in Singapore.

BACKGROUND: Glycohemoglobin is routinely used for the monitoring of glycemic control in patients with diabetes mellitus. The yearly pattern of glycohemoglobin was examined in a tropical country to assess the effect of festivities without the confounding effect of seasonal variation in temperature and climate. METHODS: Details of all outpatient HbA1c measurements with identified ethnicity over 3 y were examined with respect to date of sampling and compared to the dates of public holidays. RESULTS: There were 40267 records available. There was a circannual pattern with a peak in February/March, a minor peak in July/August and a nadir in November/December with an amplitude of 0.5%. Date of sampling was a significant factor in predicting HbA1c>8.0% despite controlling for race, sex and age. Odds ratios (vs. Quarter 4) were: Quarter 1 1.34 (1.26-1.43); Quarter 2 1.10 (1.03-1.17); Quarter 3 1.11 (1.04-1.19). There was a positive correlation between the number of festive days in the preceding 3 months and the monthly mean HbA1c value. Malay and Indian patients had significantly higher HbA1c values than Chinese. CONCLUSIONS: There is a circannual pattern of HbA1c values in adult outpatients in Singapore, reflecting the celebration of holidays in the preceding 3 months. Clinicians seeking to improve glycemic control should remember the effect of festive occasions.

Immunoglobulin G paraprotein cross-reactivity with immunoglobulin M measurement.

We report a case of IgG paraprotein cross-reactivity with IgM measurement in a patient with IgGkappa multiple myeloma and associated IgA and IgM immune paresis. IgM measurements using a Beckman-Coulter Synchron LX IgM reagent initially gave unmeasurably low IgM concentrations (<0.3 g/L) but IgM quantitation using later batches of reagent gave IgM concentrations of 13-42 g/L. Immunofixation confirmed the continued presence of the IgGkappa paraprotein band with suppression of IgA and IgM and analysis on the Behring BN2 and Beckman-Coulter Immage instruments showed IgM concentrations of <0.2 g/L. Immunofixation using the Synchron LX IgM reagent as antiserum confirmed binding of the Synchron LX IgM antiserum to the IgGkappa paraprotein. This case highlights the importance of checking all unexpected immunoglobulin measurements with previous results and immunofixation findings to avoid mistakes.