Determination of the Optimal Wavelength of the Hemolysis Index Measurement

Many biochemical auto-analyzers have methods that measure the hemolysis index (HI) to quantitatively assess the degree of hemolysis. Past reports on HI are mostly in vitro studies. Therefore, we evaluated the optimal wavelength of HI measurement ex vivo using clinical samples. Four different wavelengths (410/451 nm: HI-1, 451/478 nm: HI-2, 545/596 nm: HI-3 and 571/596 nm: HI-4) were selected for HI measurement, and correlations were examined from the measurement results of 3890 clinical samples. Another set of 9446 clinical samples was used to examine the correlation of HI with lactate dehydrogenase (LDH), aspartate aminotransferase (AST) and potassium (K). Strong correlations were found between HI-4 and HI-1 and between HI-4 and HI-3. HI-1 and HI-2 cannot correctly assess hemolysis for high bilirubin samples, and HI-3 cannot correctly assess hemolysis for high triglyceride samples. LDH, AST and K correlated positively with HI-4 in clinical samples. For every 1-unit increase in HI-4, LDH increased by 19.51 U/L, AST by 1.03 U/L and K by 0.061 mmol/L, comparable to reports of other studies. In clinical samples, HI-4 was less susceptible to bilirubin and chyle and reflected well the changes in LDH, AST and K caused by hemolysis. This suggested that the optimal wavelength for HI measurement is 571 nm.

Definition of icteric interference index for six biochemical analytes

Introduction

Icterus, if not detected, can affect the validity of results delivered by clinical laboratories, leading to erroneous results. This study aims to define bilirubin interference for some biochemical analytes and compare it with the manufacturer's data.

Material and methods

Serum pools prepared with outpatients' samples were spiked with increasing bilirubin concentration (Merck, reference14370, Darmstadt, Germany) up to 513 µmol/L in order to evaluate the bias for the following biochemical analytes: creatinine (CREA), creatine kinase (CK), cholesterol (CHOL), gamma-glutamyltransferase (GGT), high-density lipoprotein cholesterol (HDL), and total protein (TP). For each analyte, six pools of different concentrations were prepared. Measurements were made employing Cobas 8000 analyser c702-502, Roche Diagnostics (Mannheim, Germany). This study employed a study procedure defined by the Spanish Society of Laboratory Medicine.

Results

Obtained bilirubin concentrations producing a negative interference were 103 µmol/L for CHOL, 205 µmol/L for TP and 410 µmol/L for CK, but only for CK values less than 100 U/L. Bilirubin concentrations lower than 513 µmol/L do not produce interference for HDL and GGT. Finally, for the studied bilirubin concentrations, there is no interference for CREA higher than 80 µmol/L.

Conclusion

Icterus interferences have been defined for each analyte, observing differences compared to data provided by the manufacturer. The evidence indicates that each laboratory should evaluate icteric interferences to ensure the high quality of the delivered results, thus benefiting patient care.

Hemolysis Control in the Emergency Department by Interventional Blood Sampling

The hemolysis rate in the emergency department (ED) is higher compared to that in other departments. We propose a new blood sampling technique without repeated venipuncture to reduce hemolysis and compare the hemolysis rate between blood collected by this method and that collected with an intravenous (IV) catheter. This prospective study included a nonconsecutive sample of patients visiting the ED (aged ≥ 18 years) of a tertiary urban university hospital. The intravenous catheterization was performed by three pre-trained nurses. The new blood collection technique involved sample collection without removing the catheter needle, performed immediately before the conventional method (through an IV catheter), without additional venipuncture. Two blood samples were collected from each patient using both the new and conventional methods, and the hemolysis index was evaluated. We compared the hemolysis rate between the two methods. From the 260 patients enrolled in this study, 147 (56.5%) were male, and the mean age was 58.3 years. The hemolysis rate of the new blood collection method was 1.9% (5/260), which was significantly lower than that of the conventional method (7.3%; 19/260) (p = 0.001). The new blood collection method can reduce the hemolysis rate as compared to the conventional blood collection method.

Drugs and Conditions That May Mimic Hemolysis

OBJECTIVES

Visual inspection of posttransfusion plasma for hemolysis is a key laboratory method in the investigation of possible acute hemolytic transfusion reactions (AHTRs). Many substances and physiologic conditions can mimic hemolysis in vitro. Isolated reports describe specific cases of interference, but a comprehensive listing is lacking.

METHODS

Using an illustrative case, we summarize available literature on substances and conditions that may mimic hemolysis in vitro. We further describe other substances and conditions that may discolor plasma but are unlikely to be mistaken for hemolysis on visual inspection.

RESULTS

At least 11 substances and conditions have been reported to discolor plasma, in colors ranging from orange to red to brown, including relatively common therapies (eg, eltrombopag, hydroxocobalamin, iron dextran). Other substances are unlikely to be encountered in everyday practice but may mimic hemolysis in particular patient populations. Additional substances may cause plasma discoloration, ranging from blue to green to white, and are associated with a wide variety of therapies and conditions.

CONCLUSIONS

An awareness of the possible preanalytic confounding factors that may mimic hemolysis can aid in the workup of a suspected AHTR. Review of the medical record, use of ancillary testing, and consideration for nonimmune causes of hemolysis can aid in ruling out AHTR.

Autoverification-Based Algorithms to Detect Preanalytical Errors: Two Examples

The preanalytical phase of testing accounts for the majority of the errors. Software-based quality rules, such as autoverification, can assist in preanalytical error detection; therefore, preventing erroneous results from being reported. Two autoverification rules, turbidity/lipemia, and pseudohypoglycemia/pseudohyperkalemia alarms, are highlighted. Increased sample turbidity may arise from several causes outside of lipemia. Typically, this can be resolved by clarifying the sample with standard centrifugation. Truly lipemic specimens typically require higher centrifugation speeds and greater centrifugation time. At our facility, 96% of direct bilirubin (DBIL), 95% of aspartate transaminase (AST), and 98% of alanine transaminase (ALT) turbidity/lipemia alarms were found to be from sample turbidity versus lipemia. Secondly, a pseudohypoglycemia/pseudohyperkalemia rule was employed for specimens with delayed separation from cellular material. Of the total potassium results >6.0 mmol/L or glucose results <40 mg/dL (2.2 mmol/L), 30% and 50% respectively were noted to have delayed sample separation.

The incidence rate and influence factors of hemolysis, lipemia, icterus in fasting serum biochemistry specimens

Objective

Hemolysis, icterus, and lipemia (HIL) of blood samples have been a concern in hospitals because they reflect pre-analytical processes’ quality control. However, very few studies investigate the influence of patients’ gender, age, and department, as well as sample-related turnaround time, on the incidence rate of HIL in fasting serum biochemistry specimens.

Methods

A retrospective, descriptive study was conducted to investigate the incidence rate of HIL based on the HIL index in 501,612 fasting serum biochemistry specimens from January 2017 to May 2018 in a tertiary university hospital with 4,200 beds in Sichuan, southwest China. A subgroup analysis was conducted to evaluate the differences in the HIL incidence rate by gender, age and department of patients, and turnaround time of specimens.

Results

The incidence rate of hemolysis, lipemia and icterus was 384, 53, and 612 per 10,000 specimens. The male patients had a significantly elevated incidence of hemolysis (4.13% vs. 3.54%), lipemia (0.67% vs. 0.38%), and icterus (6.95% vs. 5.43%) than female patients. Hemolysis, lipemia, and icterus incidence rate were significantly associated with the male sex with an odds ratio (OR) of 1.174 [95% confidence interval (CI), 1.140–1.208], 1.757 (95%CI: 1.623–1.903), and 1.303 (95%CI: 1.273–1.333), respectively, (P<0.05). The hospitalized patients had a higher incidence of hemolysis (4.03% vs. 3.54%), lipemia (0.63% vs. 0.36%), and icterus (7.10% vs. 4.75%) than outpatients (P<0.001). Specimens with relatively longer transfer time and/or detection time had a higher HIL incidence (P<0.001). The Pediatrics had the highest incidence of hemolysis (16.2%) with an adjusted OR (AOR) of 4.93 (95%CI, 4.59–5.29, P<0.001). The Neonatology department had the highest icterus incidence (30.1%) with an AOR of 4.93 (95%CI: 4.59–5.29, P<0.001). The Neonatology department (2.32%) and Gastrointestinal Surgery (2.05%) had the highest lipemia incidence, with an AOR of 1.17 (95%CI: 0.91–1.51) and 4.76 (95%CI: 4.70–5.53), both P-value <0.001. There was an increasing tendency of hemolysis and icterus incidence for children under one year or adults aged more than 40.

Conclusion

Evaluation of HIL incidence rate and HIL-related influence factors in fasting serum biochemistry specimens are impartment to interpret the results more accurately and provide better clinical services to patients.

A survey of practice in the management of haemolysis, icterus and lipaemia in blood specimens in the United Kingdom and Republic of Ireland

BACKGROUND

Haemolysis, icterus and lipaemia (HIL) are common interferants in laboratory medicine, potentially impacting patient care. This survey investigates HIL management in medical laboratories across the UK and Republic of Ireland (ROI).

METHODS

A survey was sent to members of key professional organisations for laboratory medicine in the UK and ROI. Questions related to the detection, monitoring, quality control, and management of HIL.

RESULTS

In total, responses from 124 laboratories were analysed, predominantly from England (52%) and ROI (36%). Most responses were from public hospitals with biochemistry services (90%), serving primary care (91%), inpatients (91%), and outpatients (89%). Most laboratories monitored H (98%), I (88%), and L (96%) using automated indices (93%), alone or in combination with visual inspection.Manufacturer-stated cut-offs were used by 83% and were applied to general chemistries in 79%, and immunoassays in 50%. Where HIL cut-offs are breached, 64% withheld results, while 96% reported interference to users. HIL were defined using numeric scales (70%) and ordinal scales (26%). HIL targets exist in 35% of laboratories, and 54% have attempted to reduce HIL. Internal Quality Control for HIL was lacking in 62% of laboratories, and just 18% of respondents have participated in External Quality Assurance. Laboratories agree manufacturers should: standardise HIL reporting (94%), ensure comparability between platforms (94%), and provide information on HIL cross-reactivity (99%). Respondents (99%) showed interest in evidence-based, standardised HIL cut-offs.

CONCLUSIONS

Most respondents monitor HIL, although the wide variation in practice may differentially affect clinical care. Laboratories seem receptive to education and advice on HIL management.

Determination of clinically acceptable cut-offs for hemolysis index: An application of bootstrap method using real-world data

OBJECTIVES

To assess the impact of hemolysis on laboratory results under local conditions and to verify the hemolysis index cut-off for potassium using real-world data.

METHODS

The statistical bootstrapping method was performed on 54,125 samples collected at the University Hospital of Örebro (USÖ). The results were compared to a method based on stratification of samples according to hemolysis level, and on paired difference testing.

RESULTS

Setting the acceptable allowable limit of error to 10%, the three assessed strategies yielded comparable results with respect to the impact of haemolytic interference on test results for potassium. The suggested cut-offs were 111 mg Hb/dL for the bootstrapping method, between 125-150 mg Hb/dL for the method based on stratification, and around 150 mg/dL for the paired difference testing strategy. The impact of hemolysis on potassium measurement is likely different between primary care patients and inpatients.

CONCLUSIONS

Using the effect of hemolysis on potassium measurement as a model, a novel approach towards finding clinically acceptable limits for analytical interference is presented, that relies on the bootstrapping method and on actual patient data from routine laboratory operation, hence incorporating local population characteristics, equipment and instrumental settings.

What is the best wavelength for the measurement of hemolysis index?

BACKGROUND

Hemolysis is a common problem in the handling of serum specimens. The hemolysis index (HI) provides a warning of hemolysis in auto-analyzers. However, HI has not been standardized, and each laboratory's original method is applied. Especially, the wavelength used for HI measurement is different in each laboratory. Thus, we investigated the warning ability of HI at various wavelengths.

METHODS

We selected 4 wavelength types, and each HI was measured and calculated (410 nm/HI-1, 451 nm/HI-2, 545 nm/HI-3, and 571 nm/HI-4). To compare the 4 HI types, we investigated the influence of 3 interference components using artificially hemolyzed specimens (AHSs). We also investigated both the relationship between HI and hemoglobin concentration (Hb) and that between HI and 31 biochemical test values in AHSs.

RESULTS

In the interference assessment, only HI-4 showed no influence on the 3 interference components. The correlation between Hb and HI-4 was very strong (r_S = 0.9987). A 1-unit increase in HI-4 corresponded to a 14.8-mg/dL increase in Hb.

CONCLUSION

We found the best wavelength for HI to be at or near 571 nm.

Lipemia Interferences in Biochemical Tests, Investigating the Efficacy of Different Removal Methods in comparison with Ultracentrifugation as the Gold Standard

Introduction. As a common interferer in clinical chemistry, lipemic specimens could be a source of significant analytical errors. Ultracentrifugation has been by far the only reliable, but an unavailable and expensive, method to eliminate the lipemic effect. Materials and Methods. Among the daily samples, those with triglyceride >400 mg/dL (4.6 mmol/L) and also turbid were selected, divided into three groups, based on triglyceride concentration, and three pooled serums were made for each group. Then all pooled serums were investigated by using a DIRUI biochemistry analyzer CS-800 for routine chemistry tests in different methods including direct measurement, serum blank, serum dilution, and measurement after ultracentrifugation.

RESULTS

According to our study, there were significant differences before and after ultracentrifugation in all lipemic levels and for all parameters except for alanine aminotransferase (ALT), alkaline phosphatase (ALP), bilirubin, and uric acid. Based on allowable inaccuracy for each parameter, calcium, magnesium, phosphorus, total protein, iron, total iron-binding capacity (TIBC), urea, and chloride are being influenced by all lipemic degree and neither serum dilution nor using serum blank is as effective as ultracentrifuge for elimination. Serum blank was a proper method of lipid removal for the measurement of glucose.

CONCLUSION

Lipemia is a well-known interferer in clinical chemistry. One cannot avoid lipemia, but fortunately, severe lipemia is a rare phenomenon in the laboratory, and for assessment of some analytes in a lower degree of lipemia, use of serum blank eliminates the need for ultracentrifuge.

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.

Visual assessment of hemolysis affects patient safety

BACKGROUND

Manual handling of hemolyzed samples is not standardized and is vulnerable to errors. This study aimed to evaluate laboratory errors due to manual handling of hemolyzed samples and to assess the risk they might have for patient safety.

METHODS

Data were retrospectively obtained from a laboratory information system for 25 emergency tests from hemolyzed samples. Hemolysis (concentration of free hemoglobin >0.5 g/L) was visually assessed by comparison with a color chart. The reference person reestimated the routinely assessed degree of hemolysis to all samples (n=3185) received in the laboratory in a 1-week period. For each test, the correct and incorrect way of handling results was determined. Risk assessment was performed according to ISO 14971 standard with five categories of risk (S1-S5) and error occurrence (O1-O5).

RESULTS

In the studied period, the emergency laboratory received 495 hemolyzed samples (15.5%) with a total of 2518 laboratory test requests (15.5%): 102 (20.6%) of the reports from hemolyzed samples had a comment on hemolysis; 31% of the test results were handled incorrectly (20.7% due to the incorrect release of the test result despite hemolysis interference and 10.3% due to unnecessary suppression), accounting for 4.8% of the total test volume. Tests with the highest combination of risk and occurrence rate were troponin T, potassium and total bilirubin.

CONCLUSIONS

Manual handling of hemolyzed samples may lead to risk of errors in reporting results for troponin T, potassium and total bilirubin, which may have an effect on clinical decision. In addition, unnecessary suppression of the sample results unaffected by hemolysis could affect patient outcome.

Practices for Identifying and Rejecting Hemolyzed Specimens Are Highly Variable in Clinical Laboratories

Context

Hemolysis is an important clinical laboratory quality attribute that influences result reliability.

Objective

To determine hemolysis identification and rejection practices occurring in clinical laboratories.

Design

We used the College of American Pathologists Survey program to distribute a Q-Probes–type questionnaire about hemolysis practices to Chemistry Survey participants.

Results

Of 3495 participants sent the questionnaire, 846 (24%) responded. In 71% of 772 laboratories, the hemolysis rate was less than 3.0%, whereas in 5%, it was 6.0% or greater. A visual scale, an instrument scale, and combination of visual and instrument scales were used to identify hemolysis in 48%, 11%, and 41% of laboratories, respectively. A picture of the hemolysis level was used as an aid to technologists' visual interpretation of hemolysis levels in 40% of laboratories. In 7.0% of laboratories, all hemolyzed specimens were rejected; in 4% of laboratories, no hemolyzed specimens were rejected; and in 88% of laboratories, some specimens were rejected depending on hemolysis levels. Participants used 69 different terms to describe hemolysis scales, with 21 terms used in more than 10 laboratories. Slight and moderate were the terms used most commonly. Of 16 different cutoffs used to reject hemolyzed specimens, moderate was the most common, occurring in 30% of laboratories. For whole blood electrolyte measurements performed in 86 laboratories, 57% did not evaluate the presence of hemolysis, but for those that did, the most common practice in 21 laboratories (24%) was centrifuging and visually determining the presence of hemolysis in all specimens.

Conclusions

Hemolysis practices vary widely. Standard assessment and consistent reporting are the first steps in reducing interlaboratory variability among results.

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.

Harmonization in hemolysis detection and prevention. A working group of the Catalonian Health Institute (ICS) experience

BACKGROUND

Hemolysis is the main cause of non-quality samples in clinical laboratories, producing the highest percentage of rejections in the external assurance programs of preanalytical quality. The objective was to: 1) study the agreement between the detection methods and quantification of hemolysis; 2) establish comparable hemolysis interference limits for a series of tests and analytical methods; and 3) study the preanalytical variables which most influence hemolysis production.

METHODS

Different hemoglobin concentration standards were prepared using the reference method. Agreement was studied between automated methods [hemolytic indexes (HI)] and reference method, as well as the interference according to hemolysis degree in various biochemical tests was measured. Preanalytical variables which could influence hemolysis production were studied: type of extraction, type of tubes, transport time, temperature and centrifugation conditions.

RESULTS

Good agreement was obtained between hemoglobin concentrations measured using the reference method and HI, for the most of studied analyzers, particularly those giving quantitative HI. The hemolysis interference cut-off points obtained for the majority of tests studied (except LDH, K) are dependent on the method/analyzer utilized. Furthermore, discrepancies have been observed between interference limits recommended by the manufacturer. The preanalytical variables which produce a lower percentage of hemolysis rejections were: centrifugation at the extraction site, the use of lower volume tubes and a transport time under 15 min at room temperature.

CONCLUSIONS

The setting of interference limits (cut-off) for each used test/method, and the study of preanalytical variability will assist to the results harmonization for this quality indicator.

Validation of hemolysis index thresholds optimizes detection of clinically significant hemolysis

OBJECTIVES

Automated hemolysis index (HI) measurement has standardized the identification and gradation of sample hemolysis.

METHODS

This study evaluates whether clinically significant changes in the concentration of intracellular analytes occur at manufacturer-recommended automated HI thresholds (HI ≥3, >25 mg/dL hemoglobin).

RESULTS

Adult outpatient results for serum potassium (K+), magnesium (Mg), lactate dehydrogenase (LDH), and aspartate aminotransferase (AST) were analyzed. Mean ± SD analyte concentration and distribution within the reference interval (RI) were calculated for each HI group (1-7). Potassium results with an HI of 4 or more demonstrated clinically significant differences (≥0.5 mmol/L) in mean K+ concentration and RI classification compared with non-hemolyzed samples (HI = 1). LDH and AST showed clinically significant differences (+20%) for an HI of 3 or more. For Mg, only the group with an HI of 7 demonstrated a clinically significant difference (>25%); however, the number was low.

CONCLUSIONS

Mean measured potassium concentrations are not clinically significantly affected by hemolysis at the manufacturer-recommended HI threshold, while AST and LDH are. Aligning reporting of sample hemolysis with clinically significant changes provides clinically meaningful alerts regarding this common pre-analytic error.

The preanalytic phase in veterinary clinical pathology

This article presents the general causes of preanalytic variability with a few examples showing specialists and practitioners that special and improved care should be given to this too often neglected phase. The preanalytic phase of clinical pathology includes all the steps from specimen collection to analysis. It is the phase where most laboratory errors occur in human, and probably also in veterinary clinical pathology. Numerous causes may affect the validity of the results, including technical factors, such as the choice of anticoagulant, the blood vessel sampled, and the duration and conditions of specimen handling. While the latter factors can be defined, influence of biologic and physiologic factors such as feeding and fasting, stress, and biologic and endocrine rhythms can often not be controlled. Nevertheless, as many factors as possible should at least be documented. The importance of the preanalytic phase is often not given the necessary attention, although the validity of the results and consequent clinical decision making and medical management of animal patients would likely be improved if the quality of specimens submitted to the laboratory was optimized.

An enzymatic method to determine γ-hydroxybutyric acid in serum and urine

BACKGROUND

Gamma-hydroxybutyric acid (GHB) has become one of the most dangerous illicit drugs of abuse today. It is used as a recreational and date rape drug because of its depressant effect on the central nervous system, which may cause euphoria, amnesia, respiratory arrest, and coma. There is an urgent need for a simple, easy-to-use assay for GHB determination in urine and blood. In this article, a rapid enzymatic assay adapted to clinical chemistry analyzers for the detection of GHB is presented.

METHODS

The described GHB enzymatic assay is based on a recombinant GHB dehydrogenase. The full validation of the assay was performed on a Konelab 30 analyzer (Thermo Fisher Scientific).

RESULTS

The analytical sensitivity was <1.5 mg/L, whereas the functional sensitivity was 4.5 mg/L in serum and 2.8 mg/L in urine. The total imprecision coefficient of variation (CV) was <9.8% in serum and <7.9% in urine. The within-run imprecision showed a CV of <3.8% in serum and <4.6% in urine. The assay was linear within the range 5-250 mg/L. Mean recoveries were 109% in serum and 105% in urine. No cross-reactivity was observed for tested GHB analogues and precursors. Comparison of GHB-positive samples showed an excellent correlation with ion chromatography, gas chromatography-mass spectrometry, and liquid chromatography associated to tandem mass spectrometry. Except for ethanol, no substantial interference from serum constituents and some drugs was observed.

CONCLUSIONS

This automated GHB assay is fully quantitative and allows the accurate measurement of GHB in serum and urine. It can be used as a rapid screening assay for the determination of GHB in intoxicated or overdosed patients.

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.

Quality of plasma sampled by different methods for multiple blood sampling in mice

For oral glucose tolerance test (OGTT) in mice, multiple blood samples need to be taken within a few hours from conscious mice. Today, a number of essential parameters may be analysed on very small amounts of plasma, thus reducing the number of animals to be used. It is, however, crucial to obtain high-quality plasma or serum in order to avoid increased data variation and thereby increased group sizes. The aim of this study was to find the most valid and reproducible method for withdrawal of blood samples when performing OGTT. Four methods, i.e. amputation of the tail tip, lateral tail incision, puncture of the tail tip and periorbital puncture, were selected for testing at 21 degrees C and 30 degrees C after a pilot study. For each method, four blood samples were drawn from C57BL/6 mice at 30 min intervals. The presence of clots was registered, haemolysis was monitored spectrophotometrically at 430 nm, and it was noted whether it was possible to achieve 30-50 microL blood. Furthermore, a small amount of extra blood was sampled before and after the four samplings for testing of whether the sampling induced a blood glucose change over the 90 min test period. All methods resulted in acceptable amounts of plasma. Clots were observed in a sparse number of samples with no significant differences between the methods. Periorbital puncture did not lead to any haemolysed samples at all, and lateral tail incision resulted in only a few haemolysed samples, while puncture or amputation of the tail tip induced haemolysis in a significant number of samples. All methods, except for puncture of the tail tip, influenced blood glucose. Periorbital puncture resulted in a dramatic increase in blood glucose of up to 3.5 mmol/L indicating that it is stressful. Although lateral tail incision also had some impact on blood glucose, it seems to be the method of choice for OGTT, as it is likely to produce a clot-free non-haemolysed sample, while periorbital sampling, although producing a high quality of sample, induces such a dramatic change in blood glucose that it should not be applied for OGTT in mice.

Correction of factitious hyperkalemia in hemolyzed specimens

BACKGROUND

Hemolysis in pediatric specimens is common due to difficult blood draws and small-bore intravenous catheters. Values of serum K+ become falsely elevated secondary to release of intracellular contents. If a reliable correction factor existed for this factitious elevation, repeat K+ measurements might be avoided.

OBJECTIVE

The aim of the study was to establish a correction factor for factitiously elevated K+, using free plasma hemoglobin (p-Hgb) as a measure of in vitro hemolysis.

METHODS

Twenty whole-blood specimens drawn from healthy adults via a 23-gauge needle were divided into 4 aliquots: (1) no manipulation, (2) mechanical hemolysis via a 27-gauge needle, (3) addition of potassium acetate (KAc), and (4) addition of KAc and mechanical hemolysis. KAc was added to mimic potentially significant hyperkalemia. All specimens had standard K+ and p-Hgb measurements performed.

RESULTS

Nonhemolyzed and hemolyzed K+ ranged from 3.2 to 8.1 mEq/L and 3.5 to 10.0 mEq/L, respectively. A linear relationship existed between the change in K+ and p-Hgb from the nonhemolyzed to hemolyzed specimens. A correction factor for K+ of 0.00319 (95% confidence interval, 0.00290-0.00349) x p-Hgb was obtained.

CONCLUSIONS

A reliable correction factor for factitious hyperkalemia in a clinically relevant range exists. By example, using the above correction factor, one can predict that the delta K+ in a specimen with 500 mg/dL of p-Hgb will be 1.6 mEq/L (range, 1.5-1.7). We suggest that when the lower bound of the predicted delta K+ results in a corrected value within the reference range, a second blood draw is unnecessary.