Recommendations for detection and management of unsuitable samples in clinical laboratories

Preanalytical Variables in Hemostasis Testing

Hemostasis testing performed in clinical laboratories are critical for assessing hemorrhagic and thrombotic disorders. The assays performed can be used to provide the information required for diagnosis, risk assessment, efficacy of therapy, and therapeutic monitoring. As such, hemostasis tests should be performed to the highest level of quality, including the standardization, implementation, and monitoring of all phases of the testing, which include the preanalytical, analytical, and post-analytical phases. It is well established that the preanalytical phase is the most critical component of the testing process, being the hands-on activities, including patient preparation for blood collection, as well as the actual blood collection, including sample identification and the post-collection handling to include sample transportation, processing, and storage of samples when testing is not performed immediately. The purpose of this article is to provide an update to the previous edition of coagulation testing-related preanalytical variables (PAV) and, when properly addressed and performed, can reduce the most common causes of errors in the hemostasis laboratory.

Factors influencing the high rejection rates of HIV 1/2 serology samples at Charlotte Maxeke Johannesburg Academic Hospital and the cost implications

Background

HIV enzyme-linked immunosorbent assay (ELISA) is one of the most requested test sets within Virology and forms an essential part of patient management. Assessment of the rejection criteria is a key quality indicator, crucial for improving laboratory services and efficiency to ensure accurate and reliable results.

Objectives

The aim of this study was to identify the factors that influence the HIV 1/2 serology rejection rates (RR) at Charlotte Maxeke Johannesburg Academic Hospital and to evaluate the associated costs.

Methods

A retrospective study was conducted (June to December 2019) to identify the RR and rejection criteria of HIV serology samples throughout the total testing process. Descriptive analysis using percentages and frequencies was used to analyse the RR by phase, health establishment, ward and healthcare professional. A cost analysis incorporating minor and major costs was modelled in each phase of testing, and the total cost of rejections was calculated.

Results

A total of 6678 tests were received, and 738 were rejected (RR = 11.1%). The pre-analytical phase contributed significantly to the overall RR, with the requirement of a separate sample (57.44%) the most common reason for rejection. The total cost per rejected test was $2.47, which amounted to a total rejection cost of $197.55, of which $158.18 was caused by the pre-analytical rejection criteria.

Conclusion

High RR of HIV tests were noted, resulting in significant cost wastage. Identification and analysis of rejections must be implemented across all laboratories to improve the efficiency of testing, provide a cost-saving benefit and maintain high laboratory standards.

Research status and prospects of biomarkers for nasopharyngeal carcinoma in the era of high‑throughput omics (Review)

As a malignant tumor type, nasopharyngeal carcinoma (NPC) is characterized by distinct geographical, ethnic and genetic differences; presenting a major threat to human health in many countries, especially in Southern China. At present, no accurate and effective methods are available for the early diagnosis, efficacious evaluation or prognosis prediction for NPC. As such, a large number of patients have locoregionally advanced NPC at the time of initial diagnosis. Many patients show toxic reactions to overtreatment and have risks of cancer recurrence and distant metastasis owing to insufficient treatment. To solve these clinical problems, high‑throughput '‑omics' technologies are being used to screen and identify specific molecular biomarkers for NPC. Because of the lack of comprehensive descriptions regarding NPC biomarkers, the present study summarized the research progress that has been made in recent years to discover NPC biomarkers, highlighting the existing problems that require exploration. In view of the lack of authoritative reports at present, study design factors that affect the screening of biomarkers are also discussed here and prospects for future research are proposed to provide references for follow‑up studies of NPC biomarkers.

Mass spectrometric sample identification with indicator compounds introduced via labeled sample tubes

Objectives

The risk of sample confusion continues to be a challenge for the pre-analytical part of the overall testing process. We here describe a novel system to track samples based on a chemical code labeling of test tubes with unique combinations of indicator compounds, which are naturally not present in specimens of human origin. As part of the sample vessel filling, the liquid specimens are permanently labeled with the compound code that can be tracked back to the primary tube.

Methods

As a proof of concept we used 10 stable-isotope-labeled derivates of medical drugs as indicator substances to create a combinatory 10-digit binary number ID for individual test tubes, i.e. presence/absence of the respective compound. For this purpose, combinations of indicator compounds were provided in evaporated form in polypropylene tubes prior to filling with anonymized patient whole blood and corresponding plasmas subjected to liquid chromatography tandem-mass spectrometry designed to detect the 10 indicator compounds.

Results

In the blind analysis, we correctly identified 307 different whole blood samples by readout of a 10-digit binary number ID based on the detection of indicator compounds with respect to their presence and number.

Conclusions

We have demonstrated the feasibility of an internal labeling procedure for diagnostic samples with mass spectrometry-based readout of dissolved indicator compound combinations as a binary number ID. With an increasing number of coding compounds (≫10) a vast number of combinations for sample labeling can be realized beyond the proof of concept setting studied herein.

Hemolytic specimens in complete blood cell count: Red cell parameters could be revised by plasma free hemoglobin

Introduction

Hemolysis is the main cause of unqualified clinical samples. In this study, we established a method for detecting and evaluating hemolysis in whole blood test. We used a mathematical formula for correcting the influence of hemolysis on complete blood cell count (CBC) so as to avoid re‐venipuncture and obtain more accurate parameters of red blood cell detection, reduce the burden of patients, and improve the efficiency of diagnosis and treatment.

Methods

Hemolytic samples were selected and then corrected using the new formula. Plasma free hemoglobin (fHB) was used as the criterion to determine the degree of hemolysis; the uncertainty of measurement is acceptable as the limit value of deviation between the measured value and the revised value. Hemolysis simulation analysis in vitro and continuous monitoring of clinical patients were used to verify the correction effect.

Results

A total of 83 clinical samples with hemolysis were collected and analyzed; fHB 1.4 g/L was selected as the unacceptable value for clinical hemolysis detection. In hemolytic samples, the red blood cell parameters corrected by formula are significantly different from those uncorrected and had a good consistency with those before hemolysis.

Conclusion

The results show that the hemolysis phenomenon of CBC has a significant impact on routine blood testing. By using the new formula, the influence of hemolysis on erythrocyte and related parameters can be quickly and easily corrected, thus avoiding venipuncture again for re‐examination, reducing diagnostic errors, and saving medical resources.

Managing hemolyzed samples in clinical laboratories

Hemolysis is conventionally defined as membrane disruption of red blood cells and other blood cells that is accompanied by subsequent release of intracellular components into the serum or plasma. It accounts for over 60% of blood sample rejections in the laboratory and is the most common preanalytical error in laboratory medicine. Hemolysis can occur both in vivo and in vitro. Intravascular hemolysis (in vivo) is always associated with an underlying pathological condition or disease, and thus careful steps should always be taken by the laboratory to exclude in vivo hemolysis with confidence. In vitro hemolysis, on the other hand, is highly preventable. It may occur at all stages of the preanalytical phase (i.e. sample collection, transport, handling and storage), and may lead to clinically relevant, yet spurious, changes in patient results by interfering with laboratory measurements. Hemolysis interference is exerted through several mechanisms: (1) spectrophotometric interference, (2) release of intracellular components, (3) sample dilution and (4) chemical interference. The degree of interference observed depends on the level of hemolysis and also on the assay methodology. Recent evidence shows that preanalytical practices related to detection and management of hemolyzed samples are highly heterogeneous and need to be standardized. The Working Group for Preanalytical Phase (WG-PRE) of the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) has published many recommendations for facilitating standardization and improvement of this important preanalytical issue. Some key EFLM WG-PRE publications related to hemolysis involve: (i) a call for more transparency and some practical recommendations for improving the harmonization of the automatic assessment of serum indices and their clinical usefulness, specifically the hemolysis index (H-index), (ii) recommendations on how to manage local quality assurance of serum or plasma hemolysis/icterus/lipemia-indices (HIL-indices) and (iii) recommendations on how to detect and manage hemolyzed samples in clinical chemistry testing. In this review we provide a comprehensive overview of hemolysis, including its causes and effects on clinical laboratory assays. Furthermore, we list and discuss the most recent recommendations aimed at managing hemolyzed samples in everyday practice. Given the high prevalence of hemolyzed blood samples, the associated costs, the great heterogeneity in how hemolysis is handled across healthcare settings, countries and continents, and increasing patient cross-border mobility, standardization and quality improvement processes aimed at combatting this important preanalytical problem are clearly warranted.

Blood sample quality

Several lines of evidence now confirm that the vast majority of errors in laboratory medicine occur in the extra-analytical phases of the total testing processing, especially in the preanalytical phase. Most importantly, the collection of unsuitable specimens for testing (either due to inappropriate volume or quality) is by far the most frequent source of all laboratory errors, thus calling for urgent strategies for improving blood sample quality and managing data potentially generated measuring unsuitable specimens. A comprehensive overview of scientific literature leads us to conclude that hemolyzed samples are the most frequent cause of specimen non-conformity in clinical laboratories (40-70%), followed by insufficient or inappropriate sample volume (10-20%), biological samples collected in the wrong container (5-15%) and undue clotting (5-10%). Less frequent causes of impaired sample quality include contamination by infusion fluids (i.e. most often saline or glucose solutions), cross-contamination of blood tubes additives, inappropriate sample storage conditions or repeated freezing-thawing cycles. Therefore, this article is aimed to summarize the current evidence about the most frequent types of unsuitable blood samples, along with tentative recommendations on how to prevent or manage these preanalytical non-conformities.

Practical recommendations for managing hemolyzed samples in clinical chemistry testing

We suggest here a pragmatic approach for managing results of clinical chemistry testing in hemolyzed samples collected from adults/older children, attempting to balance the need to produce quality laboratory data with clinical urgency of releasing test results. Automatic measurement of the hemolysis index (H-index) in serum or plasma is highly advisable, whilst low-quality assessment of this test remains less good than a visual inspection. Regarding its practical use, when the H-index value does not generate an analytically significant bias, results can be released, whilst when the value is associated with analyte variation in a range between analytically and clinically significant bias (i.e. variation does not exceed the reference change value [RCV]), results of hemolysis-sensitive tests can be released in association with a comment describing the direction in which data are potentially altered, suggesting the need to collect another sample. When the H-index is associated with analyte variation exceeding clinically significant bias (i.e. variation exceeds the RCV), results of hemolysis-sensitive tests should be suppressed and replaced with a comment that biased results cannot be released because the sample is preanalytically compromised and advising the recollection of another sample. If H-index values reach an even higher critical cut-off (i.e. H-index corresponding to a cell-free hemoglobin concentration ≥10 g/L), all laboratory data may be unreliable and should hence be suppressed and replaced with a comment that all data cannot be released because the sample is grossly hemolyzed, also suggesting the recollection of another sample. Due to inaccuracy and imprecision, the use of corrective formulas for adjusting data of hemolysis-sensitive tests is discouraged.

Influence of hemolysis on clinical chemistry parameters determined with Beckman Coulter tests - detection of clinically significant interference

The aim of this study was to examine the influence of hemolysis on 25 clinical chemistry parameters and to compare the resulting bias with clinically significant differences and the manufacturer's specifications. Using freeze-thawing of the treated blood aliquot of each subject (N = 17), four hemolysis levels were prepared with hemolysis index (HI) and hemoglobin concentration as follows: (+)=0.5-0.99 g/L, (2+)=1-1.99 g/L, (3+)=2-2.99 g/L and (4+)=3-4.99 g/L. All analytes were tested on the Beckman Coulter AU480 analyzer using proprietary reagents. It was considered that the interference was detected if the 95% confidence interval for mean differences (%) between hemolyzed and non-hemolyzed samples did not include zero. Clinically significant interference was judged against reference change value (RCV). Hemolysis interference was detected for: alpha-amylase, alkaline phosphatase (ALP), aspartate aminotransferase (AST), total and conjugated bilirubin, creatine kinase (CK), CK-MB, ɣ-glutamyltransferase (GGT), iron, lactate dehydrogenase (LD), magnesium, potassium, total protein and uric acid at HI=(1+); alanine aminotransferase (ALT) and phosphate at HI=(2+); urea at HI=(3+); albumin and cholinesterase at HI=(4+). Even at the greatest hemolysis degree, HI=(4+), no interference was detected for calcium, chloride, creatinine, C-reactive protein (CRP), glucose and sodium. Clinically significant difference was exceeded for LD at HI=(1+); CK-MB at HI=(2+); AST and potassium at HI=(3+); total bilirubin at HI=(4+). The presented results did not support the manufacturer's claim for CK and GGT. Establishing HI thresholds for reporting or suppressing test results is the responsibility of each laboratory, taking into account the manufacturer's data, but also its own investigations.

Errors in the Extra-Analytical Phases of Clinical Chemistry Laboratory Testing

The total testing process consists of various phases from the pre-preanalytical to the post-postanalytical phase, the so-called brain-to-brain loop. With improvements in analytical techniques and efficient quality control programmes, most laboratory errors now occur in the extra-analytical phases. There has been recent interest in these errors with numerous publications highlighting their effect on service delivery, patient care and cost. This interest has led to the formation of various working groups whose mission is to develop standardized quality indicators which can be used to measure the performance of service of these phases. This will eventually lead to the development of external quality assessment schemes to monitor these phases in agreement with ISO15189:2012 recommendations. This review focuses on potential errors in the extra-analytical phases of clinical chemistry laboratory testing, some of the studies performed to assess the severity and impact of these errors and processes that are in place to address these errors. The aim of this review is to highlight the importance of these errors for the requesting clinician.

Control of (pre)-analytical aspects in immunoassay measurements of metabolic hormones in rodents

The measurement of circulating hormones by immunoassay remains a cornerstone in preclinical endocrine research. For scientists conducting and interpreting immunoassay measurements of rodent samples, the paramount aim usually is to obtain reliable and meaningful measurement data in order to draw conclusions on biological processes. However, the biological variability between samples is not the only variable affecting the readout of an immunoassay measurement and a considerable amount of unwanted or unintended variability can be quickly introduced during the pre-analytical and analytical phase. This review aims to increase the awareness for the factors 'pre-analytical' and 'analytical' variability particularly in the context of immunoassay measurement of circulating metabolic hormones in rodent samples. In addition, guidance is provided how to gain control over these variables and how to avoid common pitfalls associated with sample collection, processing, storage and measurement. Furthermore, recommendations are given on how to perform a basic validation of novel single and multiplex immunoassays for the measurement of metabolic hormones in rodents. Finally, practical examples from immunoassay measurements of plasma insulin in mice address the factors 'sampling site and inhalation anesthesia' as frequent sources of introducing an unwanted variability during the pre-analytical phase. The knowledge about the influence of both types of variability on the immunoassay measurement of circulating hormones as well as strategies to control these variables are crucial, on the one hand, for planning and realization of metabolic rodent studies and, on the other hand, for the generation and interpretation of meaningful immunoassay data from rodent samples.

Nurses' knowledge on phlebotomy in tertiary hospitals in China: a cross-sectional multicentric survey

Introduction

In China, phlebotomy practice is mostly executed by nurses instead of phlebotomists. Our hypothesis was that these nurses may lack of knowledge on phlebotomy, especially factors influencing quality of blood samples. This study aims to assess the overall nurses’ knowledge on phlebotomy to provide reference for improving blood sampling practice in China.

Materials and methods

A survey was conducted involving nurses from 4 regions and 13 hospitals in China. A phlebotomy knowledge questionnaire was designed based on the Clinical and Laboratory Standards Institute H3-A6 guidelines, combining with the situations in China. Descriptive analysis and binary logistic regression analysis were used to analyze the knowledge level and its influencing factors.

Results

A total of 3400 questionnaires were distributed and 3077 valid questionnaires were returned, with an effective return rate of 90.5%. The correct rates of patient identification, hand sanitization, patient assessment, tube mixing time, needle disposing location and tube labelling were greater than 90%. However, the correct rates of order of draw (15.5%), definition of an inversion (22.5%), time to release tourniquet (18.5%) and time to change tube (28.5%) were relatively low. Binary logistic regression analysis showed that the correct rates of the aforementioned four questions were mainly related to the regional distribution of the hospitals (P < 0.001).

Conclusions

The knowledge level on phlebotomy among Chinese nurses was found unsatisfactory in some areas. An education program on phlebotomy should be developed for Chinese nurses to improve the consistency among different regions and to enhance nurse’s knowledge level on phlebotomy.

Patient and Sample Identification. Out of the Maze?

Patient and sample misidentification may cause significant harm or discomfort to the patients, especially when incorrect data is used for performing specific healthcare activities. It is hence obvious that efficient and quality care can only start from accurate patient identification. There are many opportunities for misidentification in healthcare and laboratory medicine, including homonymy, incorrect patient registration, reliance on wrong patient data, mistakes in order entry, collection of biological specimens from wrong patients, inappropriate sample labeling and inaccurate entry or erroneous transmission of test results through the laboratory information system. Many ongoing efforts are made to prevent this important healthcare problem, entailing streamlined strategies for identifying patients throughout the healthcare industry by means of traditional and innovative identifiers, as well as using technologic tools that may enhance both the quality and efficiency of blood tubes labeling. The aim of this article is to provide an overview about the liability of identification errors in healthcare, thus providing a pragmatic approach for diverging the so-called patient identification crisis.

Blood venous sample collection: Recommendations overview and a checklist to improve quality

The extra-analytical phases of the total testing process have substantial impact on managed care, as well as an inherent high risk of vulnerability to errors which is often greater than that of the analytical phase. The collection of biological samples is a crucial preanalytical activity. Problems or errors occurring shortly before, or soon after, this preanalytical step may impair sample quality and characteristics, or else modify the final results of testing. The standardization of fasting requirements, rest, patient position and psychological state of the patient are therefore crucial for mitigating the impact of preanalytical variability. Moreover, the quality of materials used for collecting specimens, along with their compatibility, can guarantee sample quality and persistence of chemical and physical characteristics of the analytes over time, so safeguarding the reliability of testing. Appropriate techniques and sampling procedures are effective to prevent problems such as hemolysis, undue clotting in the blood tube, draw of insufficient sample volume and modification of analyte concentration. An accurate identification of both patient and blood samples is a key priority as for other healthcare activities. Good laboratory practice and appropriate training of operators, by specifically targeting collection of biological samples, blood in particular, may greatly improve this issue, thus lowering the risk of errors and their adverse clinical consequences. The implementation of a simple and rapid check-list, including verification of blood collection devices, patient preparation and sampling techniques, was found to be effective for enhancing sample quality and reducing some preanalytical errors associated with these procedures. The use of this tool, along with implementation of objective and standardized systems for detecting non-conformities related to unsuitable samples, can be helpful for standardizing preanalytical activities and improving the quality of laboratory diagnostics, ultimately helping to reaffirm a "preanalytical" culture founded on knowledge and real risk perception.

Pre-analytic variability in cardiovascular biomarker testing

The impact of laboratory medicine on clinical cardiology has dramatically increased over the years and a lot of cardiovascular biomarkers have been recently proposed. In order to avoid clinical mistakes, physicians should be well aware of all the aspects, which could affect the quality of laboratory results, remembering that pre-analytic variability is an often overlooked significant source of bias, determining the vast majority of laboratory errors. This review addresses the determinants of pre-analitycal variability in cardiovascular biomarker testing, focusing on the most widespread biomarkers, which are cardiac troponins and natriuretic peptides.

Specimen rejection in laboratory medicine: Necessary for patient safety?

INTRODUCTION

The emergency laboratory in Hacettepe University Hospitals receives specimens from emergency departments (EDs), inpatient services and intensive care units (ICUs). The samples are accepted according to the rejection criteria of the laboratory. In this study, we aimed to evaluate the sample rejection ratios according to the types of pre-preanalytical errors and collection areas.

MATERIALS AND METHODS

The samples sent to the emergency laboratory were recorded during 12 months between January to December, 2013 in which 453,171 samples were received and 27,067 specimens were rejected.

RESULTS

Rejection ratios was 2.5% for biochemistry tests, 3.2% for complete blood count (CBC), 9.8% for blood gases, 9.2% for urine analysis, 13.3% for coagulation tests, 12.8% for therapeutic drug monitoring, 3.5% for cardiac markers and 12% for hormone tests. The most frequent rejection reasons were fibrin clots (28%) and inadequate volume (9%) for biochemical tests. Clotted samples (35%) and inadequate volume (13%) were the major causes for coagulation tests, blood gas analyses and CBC. The ratio of rejected specimens was higher in the EDs (40%) compared to ICUs (30%) and inpatient services (28%). The highest rejection ratio was observed in neurology ICU (14%) among the ICUs and internal medicine inpatient service (10%) within inpatient clinics.

CONCLUSIONS

We detected an overall specimen rejection rate of 6% in emergency laboratory. By documentation of rejected samples and periodic training of healthcare personnel, we expect to decrease sample rejection ratios below 2%, improve total quality management of the emergency laboratory and promote patient safety.

Systematic Assessment of the Hemolysis Index: Pros and Cons

Preanalytical quality is as important as the analytical and postanalytical quality in laboratory diagnostics. After decades of visual inspection to establish whether or not a diagnostic sample may be suitable for testing, automated assessment of hemolysis index (HI) has now become available in a large number of laboratory analyzers. Although most national and international guidelines support systematic assessment of sample quality via HI, there is widespread perception that this indication has not been thoughtfully acknowledged. Potential explanations include concern of increased specimen rejection rate, poor harmonization of analytical techniques, lack of standardized units of measure, differences in instrument-specific cutoff, negative impact on throughput, organization and laboratory economics, and lack of a reliable quality control system. Many of these concerns have been addressed. Evidence now supports automated HI in improving quality and patient safety. These will be discussed.

Sample stability for complete blood cell count using the Sysmex XN haematological analyser

BACKGROUND

Sample stability is a crucial aspect for the quality of results of a haematology laboratory. This study was conducted to investigate the reliability of haematological testing using Sysmex XN in samples stored for up to 24 h at different temperatures.

MATERIALS AND METHODS

Haematological tests were performed on whole blood samples collected from 16 ostensibly healthy outpatients immediately after collection and 3 h, 6 h or 24 h afterwards, with triple aliquots kept at room temperature, 4 °C or 37 °C.

RESULTS

No meaningful bias was observed after 3 h under different storage conditions, except for red blood cell distribution width (RDW) and platelet count (impedance technique, PLT-I) at 37 °C. After 6 h, meaningful bias was observed for mean corpuscular haemoglobin (MCH) and mean corpuscular volume (MCV) at room temperature, red blood cell (RBC) count, mean corpuscular haemoglobin concentration (MCHC), MCH, MCV and PLT-I at 4 °C, and RBC, RDW, MCHC, MCH and PLT-I at 37 °C. After 24 h, a meaningful bias was observed for MCHC, MCV, platelet count (fluorescent technique, PLT-F) and mean platelet volume (MPV) at room temperature, MCHC, MCV, PLT-I and MPV at 4 °C, and all parameters except RBC count and MPV at 37 °C.

DISCUSSION

Great caution should be observed when analysing results of haematological tests conducted more than 3 h after sample collection.

Ten years of preanalytical monitoring and control: Synthetic Balanced Score Card Indicator

Introduction

Preanalytical control and monitoring continue to be an important issue for clinical laboratory professionals. The aim of the study was to evaluate a monitoring system of preanalytical errors regarding not suitable samples for analysis, based on different indicators; to compare such indicators in different phlebotomy centres; and finally to evaluate a single synthetic preanalytical indicator that may be included in the balanced scorecard management system (BSC).

Materials and methods

We collected individual and global preanalytical errors in haematology, coagulation, chemistry, and urine samples analysis. We also analyzed a synthetic indicator that represents the sum of all types of preanalytical errors, expressed in a sigma level. We studied the evolution of those indicators over time and compared indicator results by way of the comparison of proportions and Chi-square.

Results

There was a decrease in the number of errors along the years (P < 0.001). This pattern was confirmed in primary care patients, inpatients and outpatients. In blood samples, fewer errors occurred in outpatients, followed by inpatients.

Conclusion

We present a practical and effective methodology to monitor unsuitable sample preanalytical errors. The synthetic indicator results summarize overall preanalytical sample errors, and can be used as part of BSC management system.

Contamination of lithium heparin blood by K2-ethylenediaminetetraacetic acid (EDTA): an experimental evaluation

Introduction:

The contamination of serum or lithium heparin blood with ethylenediaminetetraacetic acid (EDTA) salts may affect accuracy of some critical analytes and jeopardize patient safety. The aim of this study was to evaluate the effect of lithium heparin sample contamination with different amounts of K₂EDTA.

Materials and methods:

Fifteen volunteers were enrolled among the laboratory staff. Two lithium heparin tubes and one K₂EDTA tube were collected from each subject. The lithium-heparin tubes of each subject were pooled and divided in 5 aliquots. The whole blood of K₂EDTA tube was then added in scalar amount to autologous heparinised aliquots, to obtained different degrees of K₂EDTA blood volume contamination (0%; 5%; 13%; 29%; 43%). The following clinical chemistry parameters were then measured in centrifuged aliquots: alanine aminotranspherase (ALT), bilirubin (total), calcium, chloride, creatinine, iron, lactate dehydrogenase (LD), lipase, magnesium, phosphate, potassium, sodium.

Results:

A significant variation starting from 5% K₂EDTA contamination was observed for calcium, chloride, iron, LD, magnesium (all decreased) and potassium (increased). The variation of phosphate and sodium (both increased) was significant after 13% and 29% K₂EDTA contamination, respectively. The values of ALT, bilirubin, creatinine and lipase remained unchanged up to 43% K₂EDTA contamination. When variations were compared with desirable quality specifications, the bias was significant for calcium, chloride, LD, magnesium and potassium (from 5% K₂EDTA contamination), sodium, phosphate and iron (from 29% K₂EDTA contamination).

Conclusions:

The concentration of calcium, magnesium, potassium, chloride and LD appears to be dramatically biased by even modest K₂EDTA contamination (i.e., 5%). The values of iron, phosphate, and sodium are still reliable up to 29% K₂EDTA contamination, whereas ALT, bilirubin, creatinine and lipase appear overall less vulnerable towards K₂EDTA contamination.

Prevention of hemolysis in blood samples collected from intravenous catheters

OBJECTIVES

Samples drawn through intravenous catheters are frequently hemolyzed. We planned a prospective, randomized study to establish whether hemolysis in samples drawn from intravenous catheters may be reduced using S-Monovette® tubes collected by manual aspiration as compared with standard vacuum tubes.

DESIGN AND METHODS

We studied 52 consecutive patients admitted to the ED. Blood was drawn through a 20-gauge intravenous catheter. A 5.0mL, Becton Dickinson Vacutainer® SST II Plus serum tube was collected and discarded. In the odd group of patients (i.e., n. 1, 3, 5, etc.), a second SST II tube was drawn with vacuum ("BD-V"), followed by a 5.5mL S-Monovette® serum tube collected with manual aspiration ("SD-A") and an identical S-Monovette collected by vacuum ("SD-V"). In the pair group of patients (i.e., n. 2, 4, 6, etc.), the sequence was modified to "SD-A", "SD-V" and "BD-V". Serum was separated and tested for lactate dehydrogenase (LDH), potassium and cell-free hemoglobin.

RESULTS

The mean concentration of potassium (+2.7% in BD-V and +1.7% in SD-V, respectively), LDH (+15% in BD-V and +7% in SD-V, respectively) and cell-free hemoglobin was significantly increased when samples were collected with vacuum tubes as compared with manual aspiration. No significant differences were observed between SD-V and BD-V. The frequency of hemolyzed samples was higher when blood was collected with the vacuum as compared with SD-A (i.e., 2%), but did not differ between BD-V and SD-V (i.e., 29 versus 31%; p=0.70).

CONCLUSION

S-Monovette can be used with vacuum or aspiration collection. This latter approach allows blood drawing with limited shear stress and less likelihood of generating spuriously hemolysis.

The CCLM contribution to improvements in quality and patient safety

Clinical laboratories play an important role in improving patient care. The past decades have seen unbelievable, often unpredictable improvements in analytical performance. Although the seminal concept of the brain-to-brain laboratory loop has been described more than four decades ago, there is now a growing awareness about the importance of extra-analytical aspects in laboratory quality. According to this concept, all phases and activities of the testing cycle should be assessed, monitored and improved in order to decrease the total error rates thereby improving patients’ safety. Clinical Chemistry and Laboratory Medicine (CCLM) not only has followed the shift in perception of quality in the discipline, but has been the catalyst for promoting a large debate on this topic, underlining the value of papers dealing with errors in clinical laboratories and possible remedies, as well as new approaches to the definition of quality in pre-, intra-, and post-analytical steps. The celebration of the 50th anniversary of the CCLM journal offers the opportunity to recall and mention some milestones in the approach to quality and patient safety and to inform our readers, as well as laboratory professionals, clinicians and all the stakeholders of the willingness of the journal to maintain quality issues as central to its interest even in the future.

Mean platelet volume as a diagnostic marker for cardiovascular disease: drawbacks of preanalytical conditions and measuring techniques

After the first description of platelets more than a century ago, the knowledge about their origin and function grew continuously. The development of the impedance method as a completely automated assay allowed integrating mean platelet volume (MPV) measurement as a routine parameter of the complete blood count. This enabled us to focus more on the association of platelet function and size. Since then, many authors described MPV as a marker of platelet reactivity and risk factor for cardiovascular diseases. Hence, the preanalytical variability of this parameter is known from its introduction as standard laboratory value. Unfortunately no preanalytical standards have been implemented. This review shows the high variability in the literature with MPV as a risk factor for cardiovascular disease. After a brief description of the biology of platelets, we provide an in-depth survey of the measurement methods and their drawbacks. Finally, we propose a possible approach to standardization.

Quality Indicators of the Pre-Analytical Phase

Quality indicatorsare tools that allow the quantification of quality in each of the segments of health care in comparison with selected criteria. They can be defined as an objective measure used to assess the critical health care segments such as, for instance, patient safety, effectiveness, impartiality, timeliness, efficiency, etc. In laboratory medicine it is possible to develop quality indicators or the measure of feasibility for any stage of the total testing process. The total process or cycle of investigation has traditionally been separated into three phases, the pre-analytical, analytical and post-analytical phase. Some authors also include a »pre-pre« and a »post-post« analytical phase, in a manner that allows to separate them from the activities of sample collection and transportation (pre-analytical phase) and reporting (post-analytical phase). In the year 2008 the IFCC formed within its Education and Management Division (EMD) a task force calledLaboratory Errors and Patient Safety (WG-LEPS)with the aim of promoting the investigation of errors in laboratory data, collecting data and developing a strategy to improve patient safety. This task force came up with the Model of Quality Indicators (MQI) for the total testing process (TTP) including the pre-, intra- and post-analytical phases of work. The pre-analytical phase includes a set of procedures that are difficult to define because they take place at different locations and at different times. Errors that occur at this stage often become obvious later in the analytical and post-analytical phases. For these reasons the identification of quality indicators is necessary in order to avoid potential errors in all the steps of the pre-analytical phase.

Preanalytical phase--a continuous challenge for laboratory professionals

Preanalytical phase is the most vulnerable part of the total testing process and is considered to be among the greatest challenges to the laboratory professionals. However, preanalytical activities, management of unsuitable specimens and reporting policies are not fully standardized, nor harmonized worldwide. Several standards related to blood sampling and sample transportation and handling are available, but compliance to those guidelines is low, especially outside the laboratory and if blood sampling is done without the direct supervision of the laboratory staff. Furthermore, for some most critical procedures within the preanalytical phase, internationally accepted guidelines and recommendations as well as related quality measures are unfortunately unavailable. There is large heterogeneity in the criteria for sample rejection, the different strategies by which unacceptable samples are managed, processed and test results reported worldwide. Management of unacceptable specimens warrants therefore immediate harmonization. Alongside the challenging and long road of patient safety, preanalytical phase offers room for improvement, and Editors at Biochemia Medica Journal definitely hope to continue providing a respective mean for reporting studies on different preanalytical phase topics. With pleasure and delight we invite potential future authors to submit their articles examining the quality of various preanalytical activities to Biochemia Medica. We will keep nurturing this topic as our prominent feature and by this we hope to be able to deliver valid evidence for some future guidelines and recommendations.

Managing the pre- and post-analytical phases of the total testing process

For many years, the clinical laboratory's focus on analytical quality has resulted in an error rate of 4-5 sigma, which surpasses most other areas in healthcare. However, greater appreciation of the prevalence of errors in the pre- and post-analytical phases and their potential for patient harm has led to increasing requirements for laboratories to take greater responsibility for activities outside their immediate control. Accreditation bodies such as the Joint Commission International (JCI) and the College of American Pathologists (CAP) now require clear and effective procedures for patient/sample identification and communication of critical results. There are a variety of free on-line resources available to aid in managing the extra-analytical phase and the recent publication of quality indicators and proposed performance levels by the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) working group on laboratory errors and patient safety provides particularly useful benchmarking data. Managing the extra-laboratory phase of the total testing cycle is the next challenge for laboratory medicine. By building on its existing quality management expertise, quantitative scientific background and familiarity with information technology, the clinical laboratory is well suited to play a greater role in reducing errors and improving patient safety outside the confines of the laboratory.

Chemistry and haematology sample rejection and clinical impact in a tertiary laboratory in Cape Town

BACKGROUND

Recent publications report that up to 70% of total laboratory errors occur in the pre-analytical phase. Identification of specific problems highlights pre-analytic processes susceptible to errors. The rejection of unsuitable samples can lead to delayed turnaround time and affect patient care.

METHODS

A retrospective audit was conducted investigating the rejection rate of routine blood specimens received at chemistry and haematology laboratories over a 2-week period. The reasons for rejection and potential clinical impact of these rejections were investigated. Thirty patient files were randomly selected and examined to assess the impact of these rejections on clinical care.

RESULTS

A total of 32,910 specimens were received during the study period, of which 481 were rejected, giving a rejection rate of 1.46%. The main reasons for rejection were inappropriate clotting (30%) and inadequate sample volume (22%). Only 51.7% of rejected samples were repeated and the average time for a repeat sample to reach the laboratory was about 5 days (121 h). Of the repeated samples, 5.1% had results within critical values. Examination of patient folders showed that in 40% of cases the rejection of samples had an impact on patient care.

CONCLUSIONS

The evaluation of pre-analytical processes in the laboratory, with regard to sample rejection, allowed one to identify problem areas where improvement is necessary. Rejected samples due to factors out of the laboratory's control had a definite impact on patient care and can thus affect customer satisfaction. Clinicians should be aware of these factors to prevent such rejections.

Influence of using a roller mixer on rejected samples in coagulation tests

INTRODUCTION

The influence of using a roller mixer just after blood collection on the ratio of rejected samples in coagulation tests was investigated retrospectively.

METHODS

Numbers of blood samples collected in centralized units of outpatient clinics for prothrombin time (PT) were 24,050 in group I and 24,500 in group II (H. Aral, unpublished data). In group I, the tubes were inverted manually. In group II, the tubes were left standing on roller mixer with 30 rpm. The ratios of rejected samples of the two groups were compared statistically with ki-square analysis.

RESULTS

Using a roller mixer, rate of rejection decreased from 0.79% (group I) to 0.20% (group II) (P<0.001).

CONCLUSION

We suggested using roller mixer to improve the reliability of coagulation testing. Such standardization in preanalytical phase may be helpful in preventing laboratory errors and obtaining correct test results in coagulation tests.

Preanalytical quality improvement: from dream to reality

Abstract Laboratory diagnostics (i.e., the total testing process) develops conventionally through a virtual loop, originally referred to as "the brain to brain cycle" by George Lundberg. Throughout this complex cycle, there is an inherent possibility that a mistake might occur. According to reliable data, preanalytical errors still account for nearly 60%-70% of all problems occurring in laboratory diagnostics, most of them attributable to mishandling procedures during collection, handling, preparing or storing the specimens. Although most of these would be "intercepted" before inappropriate reactions are taken, in nearly one fifth of the cases they can produce inappropriate investigations and unjustifiable increase in costs, while generating inappropriate clinical decisions and causing some unfortunate circumstances. Several steps have already been undertaken to increase awareness and establish a governance of this frequently overlooked aspect of the total testing process. Standardization and monitoring preanalytical variables is of foremost importance and is associated with the most efficient and well-organized laboratories, resulting in reduced operational costs and increased revenues. As such, this article is aimed at providing readers with significant updates on the total quality management of the preanalytical phase to endeavour further improvement for patient safety throughout this phase of the total testing process.

The prevalence of preanalytical errors in a Croatian ISO 15189 accredited laboratory

BACKGROUND

The preanalytical phase is the most common source of laboratory errors. The goal of this descriptive study was to analyze the prevalence and type of preanalytical errors in relation to the site of sample collection (inpatient vs. outpatient) and the type of laboratory unit (hematology and coagulation vs. biochemistry). For the biochemistry unit, the data were also analyzed relative to the type of the analysis (stat vs. routine).

METHODS

We retrospectively analyzed the sample and test request form error rate for a 1-year period, from January to December 2008.

RESULTS

The frequency of the sample errors differed significantly between the emergency and routine biochemistry unit (0.69% vs. 2.14%; p<0.0001), and between inpatients and outpatients (1.12% vs. 1.36%; p=0.0006). Hemolysis was the most frequent sample error, accounting for 65% of all unsuitable specimens in the emergency biochemistry unit. The total sample error rate did not differ between hematology and coagulation vs. the biochemistry unit. The frequency of test request form errors differed significantly with respect to the sample collection site (p<0.0001), laboratory unit (p<0.0001) and type of the analysis (p<0.0001). Errors in the test request form were least frequent in the outpatient unit (2.98%) and most frequent in the routine biochemistry unit (65.94%).

CONCLUSIONS

Sample and test request form errors in our laboratory are occurring with a frequency comparable to that reported by others. Continuous educational action is needed for all stakeholders involved in laboratory testing to improve the quality of the preanalytical phase of the total testing process.

Medical Errors: Pre-Analytical Issue in Patient Safety

The last few decades have seen a significant decrease in the rates of analytical errors in clinical laboratories, while a growing body of evidence demonstrates that the pre- and post-analytical steps of the total testing process (TTP) are more error-prone than the analytical phase. In particular, most errors are identified in pre-pre-analytic steps outside the walls of the laboratory, and beyond its control. However, in a patient-centred approach to the delivery of health care services, there is the need to investigate, in the total testing process, any possible defect that may have a negative impact on the patient, irrespective of which step is involved and whether the error depends on a laboratory professional (e.g. calibration or testing error) or a non-laboratory operator (e.g. inappropriate test request, error in patient identification and/or blood collection). In the pre-analytic phase, the frequency of patient/specimens misidentification and the presence of possible causes of specimen rejection (haemolysis, clotting, insufficient volume, etc.) represent a valuable risk for patient safety. Preventing errors in the pre-analytical steps requires both technological developments (wristband, barcodes, pre-analytical workstations) and closer relationships with the clinical world to achieve an effective team-working cooperation. The most important lesson we have learned, therefore, is that laboratory errors and injuries to patients can be prevented by redesigning systems that render it difficult for all caregivers and in all steps of the total testing process to make mistakes.

Paraoxonase activity in athletes with depleted iron stores and iron-deficient erythropoiesis

OBJECTIVE

The aim of this study was to evaluate how conditions that precede anaemia (iron store depletion and iron-deficient erythropoiesis) affect human serum paraoxonase PON1 activity.

DESIGN AND METHODS

Based on haemoglobin, transferrin saturation and serum ferritin values 119 athletes were divided into three groups: with iron depletion, with deficient erythropoiesis and controls. The following parameters were measured: paraoxonase activity towards paraoxon (POase) and diazoxon (DZOase), lipid hydroperoxides (LOOH), the pro-oxidant-antioxidant balance (PAB), red blood cells (RBC) and lipid status.

RESULTS

Significant differences were found between athletes with different stages of iron deficiency and controls with respect to PON 1 activity and oxidative stress status parameters (Wilks' Lambda=0.712, F=5.241, p<0.001, η(2)=0.156). There was no significant difference between the PON1 192 Q and R polymorphism distribution in the two groups of athletes with different stages of iron deficiency and controls (χ(2)=1.086; p=0.896). PON1 activity was positively correlated with RBCs, haemoglobin, transferrin saturation (p<0.001) and ferritin (p=0.037) and negatively correlated with LOOH (p=0.044) in all three study groups.

CONCLUSIONS

Deficient erythropoiesis in athletes contributes to impaired PON1 activity. In contrast, iron depletion, regardless of increased oxidative stress, does not affect PON1 activity.

Laboratory reporting of hemostasis assays: the final post-analytical opportunity to reduce errors of clinical diagnosis in hemostasis?

The advent of modern instrumentation, with associated improvements in test performance and reliability, together with appropriate internal quality control (IQC) and external quality assurance (EQA) measures, has led to substantial reductions in analytical errors within hemostasis laboratories. Unfortunately, the reporting of incorrect or inappropriate test results still occurs, perhaps even as frequently as in the past. Many of these cases arise due to a variety of events largely outside the control of the laboratories performing the tests. These events are primarily preanalytical, related to sample collection and processing, but can also include post-analytical events related to the reporting and interpretation of test results. The current report provides an overview of these events, as well as guidance for prevention or minimization. In particular, we propose several strategies for the post-analytical reporting of hemostasis assays, and how this may provide the final opportunity to prevent serious clinical errors in diagnosis. This report should be of interest to both the laboratory scientists working in hemostasis and clinicians that request and attempt to interpret the test results. Laboratory scientists are ultimately responsible for these test results, and there is a duty to provide both accurate and precise results to enable clinicians to manage patients appropriately and to avoid the need to recollect and retest. Also, clinicians will not be in a position to best diagnose and manage their patient unless they gain an appreciation of these issues.

The detection and prevention of errors in laboratory medicine

The last few decades have seen a significant decrease in the rates of analytical errors in clinical laboratories. Evidence demonstrates that pre- and post-analytical steps of the total testing process (TTP) are more error-prone than the analytical phase. Most errors are identified in pre-pre-analytic and post-post-analytic steps outside of the laboratory. In a patient-centred approach to the delivery of health-care services, there is the need to investigate, in the TTP, any possible defect that may have a negative impact on the patient. In the interests of patients, any direct or indirect negative consequence related to a laboratory test must be considered, irrespective of which step is involved and whether the error depends on a laboratory professional (e.g. calibration/testing error) or non-laboratory operator (e.g. inappropriate test request, error in patient identification and/or blood collection). Patient misidentification and problems communicating results, which affect the delivery of diagnostic services, are recognized as the main goals for quality improvement. International initiatives aim at improving these aspects. Grading laboratory errors on the basis of their seriousness should help identify priorities for quality improvement and encourage a focus on corrective/preventive actions. It is important to consider not only the actual patient harm sustained but also the potential worst-case outcome if such an error were to reoccur. The most important lessons we have learned are that system theory also applies to laboratory testing and that errors and injuries can be prevented by redesigning systems that render it difficult for all health-care professionals to make mistakes.

Comparison of visual vs. automated detection of lipemic, icteric and hemolyzed specimens: can we rely on a human eye?

BACKGROUND

Results from hemolyzed, icteric, and lipemic samples may be inaccurate and can lead to medical errors. These preanalytical interferences may be detected using visual or automated assessment. Visual inspection is time consuming, highly subjective and not standardized. Our aim was to assess the comparability of automated spectrophotometric detection and visual inspection of lipemic, icteric and hemolyzed samples.

METHODS

This study was performed on 1727 routine biochemistry serum samples. Automated detection was performed using the Olympus AU2700 analyzer. We assessed: 1) comparability of visual and automated detection of lipemic, icteric and hemolyzed samples, 2) precision of automated detection, and 3) inter-observer variability for visual inspection.

RESULTS

Weighted kappa coefficients for comparability of visual and automated detection were: 0.555, 0.529 and 0.638, for lipemic, icteric and hemolyzed samples, respectively. The precision for automated detection was high for all interferences, with the exception of samples being only slightly lipemic. The best overall agreement between observers was present in assessing lipemia (mean weighted kappa=0.698), whereas the lowest degree of agreement was observed in assessing icterus (mean weighted kappa=0.476).

CONCLUSIONS

Visual inspection of lipemic, icteric and hemolyzed samples is highly unreliable and should be replaced by automated systems that report serum indices.

Modeling complex workflow in molecular diagnostics: design specifications of laboratory software for support of personalized medicine

One of the hurdles to achieving personalized medicine has been implementing the laboratory processes for performing and reporting complex molecular tests. The rapidly changing test rosters and complex analysis platforms in molecular diagnostics have meant that many clinical laboratories still use labor-intensive manual processing and testing without the level of automation seen in high-volume chemistry and hematology testing. We provide here a discussion of design requirements and the results of implementation of a suite of lab management tools that incorporate the many elements required for use of molecular diagnostics in personalized medicine, particularly in cancer. These applications provide the functionality required for sample accessioning and tracking, material generation, and testing that are particular to the evolving needs of individualized molecular diagnostics. On implementation, the applications described here resulted in improvements in the turn-around time for reporting of more complex molecular test sets, and significant changes in the workflow. Therefore, careful mapping of workflow can permit design of software applications that simplify even the complex demands of specialized molecular testing. By incorporating design features for order review, software tools can permit a more personalized approach to sample handling and test selection without compromising efficiency.

Preanalytical mistakes in samples from primary care patients

BACKGROUND

Preanalytical mistakes (PAMs) in samples usually led to rejection upon arrival to the clinical laboratory. However, PAMs might not always be detected and result in clinical problems. Thus, PAMs should be minimized. We detected PAMs in samples from Primary Health Care Centres (PHCC) served by our central laboratory. Thus, the goal of this study was to describe the number and types of PAMs, and to suggest some strategies for improvement.

METHODS

The presence of PAMs, as sample rejection criteria, in samples submitted from PHCC to our laboratory during October and November 2007 was retrospectively analysed.

RESULTS

Overall, 3885 PAMs (7.4%) were detected from 52,669 samples for blood analyses. This included missed samples (n=1763; 45.4% of all PAMs, 3.3% of all samples), haemolysed samples (n=1408; 36.2% and 2.7%, respectively), coagulated samples (n=391; 10% and 0.7%, respectively), incorrect sample volume (n=110; 2.8% and 0.2%, respectively), and others (n=213; 5.5% and 0.4%, respectively). For urine samples (n=18,852), 1567 of the samples were missing (8.3%).

CONCLUSIONS

We found the proportion of PAMs in blood and urine samples to be 3-fold higher than that reported in the literature. Therefore, strategies for improvement directed towards the staff involved, as well as an exhaustive audit of preanalytical process are needed. To attain this goal, we first implemented a continued education programme, financed by our Regional Health Service and focused in Primary Care Nurses.

Governance of preanalytical variability: travelling the right path to the bright side of the moon?

Medical errors can be traditionally clustered into 4 categories, which include errors of diagnosis, errors of treatment, errors of prevention, and an 'other miscellaneous' category. Owing to the volume and complexity of testing, and considering that laboratory error is defined as any defect from ordering tests to reporting results and appropriately interpreting and reacting on these, it is not surprising that mistakes in the total testing process occur with frequency, have connections to all four types of medical errors and represent a serious hazard for patient health. Throughout the laboratory diagnostics, preanalytical problems prevail. Moreover, the positive trends towards reduction of laboratory errors over the past decade, particularly those in the analytical phase, has little involved the preanalytical phase, which actually represents the most critical area to target. In particular, the high frequency of errors still attributable to processes external to the laboratory requires additional efforts for the governance of this mistreated phase of the total testing process, so that we can finally find the right path to progress from the dark to the bright side of the moon. As for any other type of medical errors, the most effective path to improvement is the implementation of a total quality management system, encompassing a multifaceted strategy for process and risk analysis, based on error prevention, detection, and management.