Influence of haemolysis on blood biochemistry profiles in cattle

Although haemolysis is the most common source of preanalytical error in clinical laboratories, its influence on cattle biochemistry remains poorly understood. The effect of haemolysis and its clinical relevance were investigated in 70 samples in which haemolysis was artificially induced (by spiking with increasing amounts of haemolysate, yielding 0.0%, 0.2%, 0.5%, 1.0%, 2.5%, 5.0% and 10% haemolysis degree (HD)), focusing on key parameters for bovine metabolic health assessment, including albumin, alkaline phosphatase (ALP), aspartate aminotransferase (AST), blood urea nitrogen (BUN), calcium (Ca), cholesterol, creatinine, creatine kinase (CK), gamma-glutamyl transferase (GGT), globulins, magnesium (Mg), phosphorus (P), total bilirubin (TBIL) and total proteins (TP). Preanalytical haemolysis significantly affected most (8 of 14) of the biochemical parameters analysed, leading to significant increases in concentrations of albumin (starting at 5% HD), cholesterol (at 5% HD) and P (at 10% HD) and to significant decreases in Ca (at 2.5% HD), creatinine (at 5% HD), globulins (at 10% HD), TBIL (at 2.5% HD) and TP (at 10% HD). Comparison of the present and previous data indicated that, for each parameter, the HD required to produce significant bias and the clinical relevance of over- and underestimation are variable and appear to depend on the analytical technique used. Therefore, different laboratories should evaluate the influence of haemolysis in their analytical results and provide advice to clinicians accordingly. Affected parameters should be interpreted together with clinical signs and other analytical data to minimize misinterpretations (false or masked variations). Finally, due to the significant impact on numerous parameters and the limited potential for correction, we recommend rejection of samples with >10% HD.

Delta checks

Delta check is an electronic error detection tool. It compares the difference in sequential results within a patient against a predefined limit, and when exceeded, the delta check rule is considered triggered. The patient results should be withheld for review and troubleshooting before releasing to the clinical team for patient management. Delta check was initially developed as a tool to detect wrong-blood-in-tube (sample misidentification) errors. It is now applied to detect errors more broadly within the total testing process. Recent advancements in the theoretical understanding of delta check has allowed for more precise application of this tool to achieve the desired clinical performance and operational set up. In this Chapter, we review the different pre-implementation considerations, the foundation concepts of delta check, the process of setting up key delta check parameters, performance verification and troubleshooting of a delta check flag.

An Objective Approach to Deriving the Clinical Performance of Autoverification Limits

This study describes an objective approach to deriving the clinical performance of autoverification rules to inform laboratory practice when implementing them. Anonymized historical laboratory data for 12 biochemistry measurands were collected and Box-Cox-transformed to approximate a Gaussian distribution. The historical laboratory data were assumed to be error-free. Using the probability theory, the clinical specificity of a set of autoverification limits can be derived by calculating the percentile values of the overall distribution of a measurand. The 5th and 95th percentile values of the laboratory data were calculated to achieve a 90% clinical specificity. Next, a predefined tolerable total error adopted from the Royal College of Pathologists of Australasia Quality Assurance Program was applied to the extracted data before subjecting to Box-Cox transformation. Using a standard normal distribution, the clinical sensitivity can be derived from the probability of the Z-value to the right of the autoverification limit for a one-tailed probability and multiplied by two for a two-tailed probability. The clinical sensitivity showed an inverse relationship with between-subject biological variation. The laboratory can set and assess the clinical performance of its autoverification rules that conforms to its desired risk profile.

Preanalytical errors in a satellite stat laboratory: A Six Sigma analysis of seven years' data

BACKGROUND

There have been few reports regarding the frequency and types of preanalytical errors in stat laboratories, in particular those occurring in the satellite laboratory setting. The impact of this error type on laboratory performance in this environment is largely unknown. We assessed the performance of a stat laboratory serving a population of predominantly elderly patients with suspected or established diagnoses of cancer using Six Sigma methodology and compared the results to previous work on this subject.

METHODS

We performed an observational retrospective study using data from the period 2013-2020. The clinical setting was a satellite laboratory supporting an outpatient medical clinic. The type and frequency of each type of preanalytical error were compiled and were used to derive the quarterly error rate. Overall and quarterly performance were calculated using Six Sigma methodology.

RESULTS

During the study period 1314 preanalytical errors were identified from 247,271 laboratory tests (0.5% of total test volume). There was a steady decrease in the error rate over the course of the study period, ranging from 1.4% in 2013 to 0.14% in 2020, despite a 290% increase in quarterly test volume during this period. The most common error types encountered were order error, hemolysis, collection error, and lab accident.

CONCLUSION

1) The overall performance of a satellite laboratory with a stat testing menu is comparable to hospital-based laboratory stat testing. 2) The most frequent error types encountered in satellite laboratory stat testing differ from those found in hospital-based laboratories. 3) There was an overall improvement in laboratory performance based on Six Sigma methodology.

Characterization of analytical errors in thromboelastography interpretation

Introduction

Interpretation of Thromboelastography (TEG) curve involves correlating patient's clinical profile with TEG parameters and the tracing, keeping in mind the potential sources of errors, and hence requires expertise. We aimed to analyse the analytical errors in TEG interpretation due to paucity of literature in this regard.

Material and methods

The retrospective study was conducted in an apex trauma center in North India. Five months of data was reviewed by two laboratory physicians, with differences resolved by consensus. Cases with pre-analytical errors, missing data and TEG runs lasting <10 ​min were excluded. The analytical errors were classified into: preventable, potentially preventable, non-preventable, and non-preventable but care could have been improved.

Results

Out of 440 TEG tracings reviewed, 70 were excluded. An analytical error was present in 60/370 (16.2%) tracings. There were six types analytical errors, of which, tracings of severe hypocoagulable states showing k-time ​= ​0 (33.3%) was the commonest, followed by tracings with spikes at irregular intervals (30%). Of all the analytical errors, 29/60 (48.2%) were preventable and 5/60 (8.3%) were potentially preventable.

Conclusion

Analytical variables that lead to errors in TEG interpretation were identified in about one-sixth of the cases and almost half of them were preventable. Awareness about the common errors amongst clinicians and laboratory physicians is critical to prevent treatment delay and safeguard patient safety.

Relationship between biological variation and delta check rules performance

OBJECTIVES

The performance of delta check rules has been considered to be dependent on the biological variation characteristics of the analyte of interest. The assumed relationships have not been formally studied. The mathematical relationship between biological variation and delta check rules is explored in this study.

DESIGN AND METHODS

From the mathematical model for absolute difference delta check, the threshold for specificity and sensitivity are observed to be normalized differently. For specificity, the threshold is normalized by the within-subject biological variation (expressed as a coefficient of variation, CV_i), whereas for sensitivity the threshold is normalized by the between-subject biological variation (expressed as a coefficient of variation, CV_g). This highlights the different roles the two biological variations play in affecting the absolute difference distribution for correct and switched patient samples. Analogous to absolute difference delta checks, for relative difference delta checks, the expressions for specificity and sensitivity are scaled by CV_i and CV_g, respectively. However, the expressions are independent of μ_g(the average of the population).

RESULTS

A comparison between the mathematical model and empirical/ historical laboratory data obtained from patients was conducted for both absolute and relative difference delta checks. In general it was found that the specificity obtained from the historical laboratory data was less than the model predicted values, while on the other hand, good correspondence was obtained between the experimental sensitivity and predicted sensitivity.

CONCLUSIONS

The difference in within-subject biological variation in different patients may contribute to the observed discrepancy in predicted and empirical delta check performance.

Better get moving on laboratory quality assurance

PURPOSE

With recent advances in laboratory hematology automation, emphasis is now on quality assurance processes as they are indispensable for generating reliable and accurate test results. It is therefore imperative to acquire efficient measures for recognizing laboratory malfunctions and errors to improve patient safety. The paper aims to discuss these issues.

DESIGN/METHODOLOGY/APPROACH

Moving algorithm is a quality control process that monitors analyzer performance from historical records through a continuous process, which does not require additional expenditure, and can serve as an additional support to the laboratory quality control program.

FINDINGS

The authors describe an important quality assurance tool, which can be easily applied in any laboratory setting, especially in cost-constrained areas where running commercial controls throughout every shift may not be a feasible option.

ORIGINALITY/VALUE

The authors focus on clinical laboratory quality control measures for providing reliable test results. The moving average appears to be a reasonable and applicable choice for vigilantly monitoring each result.

Approach to the interpretation of unexpected laboratory results arising in the care of patients with inborn errors of metabolism (IEM)

Endocrinologists may encounter abnormal results in routine laboratory tests while caring for patients with inborn errors of metabolism. This article provides a framework for understanding these abnormalities as: a) part of the pathophysiology of the exceptional disease, b) exceptional laboratory errors related to the exceptional disease, or c) routine laboratory errors to which any patient sample is susceptible.

The effectiveness of cooling conditions on temperature of canine EDTA whole blood samples

Background

Preanalytic factors such as time and temperature can have significant effects on laboratory test results. For example, ammonium concentration will increase 31% in blood samples stored at room temperature for 30 min before centrifugation. To reduce preanalytic error, blood samples may be placed in precooled tubes and chilled on ice or in ice water baths; however, the effectiveness of these modalities in cooling blood samples has not been formally evaluated. The purpose of this study was to evaluate the effectiveness of various cooling modalities on reducing temperature of EDTA whole blood samples.

Methods

Pooled samples of canine EDTA whole blood were divided into two aliquots. Saline was added to one aliquot to produce a packed cell volume (PCV) of 40% and to the second aliquot to produce a PCV of 20% (simulated anemia). Thirty samples from each aliquot were warmed to 37.7 °C and cooled in 2 ml allotments under one of three conditions: in ice, in ice after transfer to a precooled tube, or in an ice water bath. Temperature of each sample was recorded at one minute intervals for 15 min.

Results

Within treatment conditions, sample PCV had no significant effect on cooling. Cooling in ice water was significantly faster than cooling in ice only or transferring the sample to a precooled tube and cooling it on ice. Mean temperature of samples cooled in ice water was significantly lower at 15 min than mean temperatures of those cooled in ice, whether or not the tube was precooled. By 4 min, samples cooled in an ice water bath had reached mean temperatures less than 4 °C (refrigeration temperature), while samples cooled in other conditions remained above 4.0 °C for at least 11 min. For samples with a PCV of 40%, precooling the tube had no significant effect on rate of cooling on ice. For samples with a PCV of 20%, transfer to a precooled tube resulted in a significantly faster rate of cooling than direct placement of the warmed tube onto ice.

Discussion

Canine EDTA whole blood samples cool most rapidly and to a greater degree when placed in an ice-water bath rather than in ice. Samples stored on ice water can rapidly drop below normal refrigeration temperatures; this should be taken into consideration when using this cooling modality.

How accurately and consistently do laboratories measure workplace concentrations of respirable crystalline silica?

Permissible exposure limits (PELs) for respirable crystalline silica (RCS) have recently been reduced from 0.10 to 0.05 mg/m³. This raises an important question: do current laboratory practices and standards for assessing RCS concentrations permit reliable discrimination between workplaces that are in compliance and workplaces that are not? To find out, this paper examines recent laboratory performance in quantifying RCS amounts on filters sent to them to assess their proficiency. A key finding is that accredited laboratories do not reliably (e.g., with 95% confidence) estimate RCS quantities to within a factor of 2. Thus, laboratory findings indicating that RCS levels are above or below a PEL provide little confidence that this is true. The current accreditation standard only requires laboratories to achieve estimates within three standard deviations of the correct (reference) value at least two thirds of the time, rather than a more usual standard such as within 25% of the correct value at least 95% of the time. Laboratory practices may improve as the new PEL is implemented, but they are presently essentially powerless to discriminate among RCS levels over most of the range of values that have been tested, leaving employers and regulators without a reliable means to ascertain when workplace RCS levels are above or below the PEL.

The quality and scope of information provided by medical laboratories to patients before laboratory testing: Survey of the Working Group for Patient Preparation of the Croatian Society of Medical Biochemistry and Laboratory Medicine

INTRODUCTION

The aim of this work was to evaluate to what extent the scope and content of information provided to patients is standardized across medical biochemistry laboratories in Croatia.

MATERIALS AND METHODS

Two on-line self-report surveys were sent out: Survey A regarding attitudes on importance of patient preparation and Survey B on the contents of patient preparation instructions.

RESULTS

13/118 laboratories (11%) do not provide written instructions to patients on how to prepare for laboratory testing, and 36 (40%) do not include information about water intake in their instructions. Only half of laboratories provide instructions for prostate-specific antigen (53.8%), female sex hormones (53.7%) and therapeutic drug monitoring (TDM) (52.5%). Inadequate information about fasting status (55.0%) and 24 hour urine collection (77.9%) were frequent errors with high severity and were associated with the greatest potential to cause patient harm.

CONCLUSIONS

Laboratory professionals in Croatia have a positive attitude towards the importance of patient preparation for laboratory testing. However, the information for laboratory testing is not standardized and frequently lacks guidance for tests related to TDM, coagulation and endocrinology. This study highlights the need for standardized, updated and evidence-based recommendations for patient preparation in order to minimize the risk for patients.

Quality impact on diagnostic blood specimen collection using a new device to relieve venipuncture pain

A new device called Buzzy(®) has been recently presented that combines a cooling ice pack and a vibrating motor in order to relieve the venipuncture pain. The aim of this study was to evaluate the impact of Buzzy(®) use during diagnostic blood specimen collection by venipuncture for routine immunochemistry tests. Blood was collected from 100 volunteers by a single, expert phlebotomist. A vein was located on the left forearm without applying tourniquet, in order to prevent any interference from venous stasis, and blood samples were collected using a 20-G straight needle directly into 5 mL vacuum tubes with clot activator and gel separator. In sequence, external cold and vibration by Buzzy(®) was applied on the right forearm-5 cm above the chosen puncture site-for 1 min before venipuncture and continued until the end of the same procedure already done in the left forearm. The panel of tests included the following: glucose, total cholesterol, HDL-cholesterol, triglycerides, total protein, albumin, c-reactive protein, urea, creatinine, uric acid, alkaline phosphatase, amylase, AST, ALT, g-glutamyltransferase, lactate dehydrogenase, creatine kinase, total bilirubin, phosphorus, calcium, magnesium, iron, sodium, potassium, chloride, lipase, cortisol, insulin, thyroid-stimulating hormone, total triiodothyronine, free triiodothyronine, total thyroxine, free thyroxine and haemolysis index. Clinically significant differences between samples were found only for: total protein, albumin and transferrin. The Buzzy(®) can be used during diagnostic blood specimens collection by venipuncture for the majority of the routine immunochemistry tests. We only suggest avoiding this device during blood collection when protein, albumin and transferrin determinations should be performed.