Blood sample contamination by glucose-containing solutions: effects and identification

Design of an algorithm for the detection of intravenous fluid contamination in clinical laboratory samples

OBJECTIVES

Contamination of blood samples from patients receiving intravenous fluids is a common error with potential risk to the patient. Algorithms based on the presence of aberrant results have been described but have the limitation that not all infusion fluids have the same composition. Our objective is to develop an algorithm based on the detection of the dilution observed on the analytes not usually included in infusion fluids.

METHODS

A group of 89 cases was selected from samples flagged as contaminated. Contamination was confirmed by reviewing the clinical history and comparing the results with previous and subsequent samples. A control group with similar characteristics was selected. Eleven common biochemical parameters not usually included in infusion fluids and with low intraindividual variability were selected. The dilution in relation to the immediate previous results was calculated for each analyte and a global indicator, defined as the percentage of analytes with significant dilution, was calculated. ROC curves were used to define the cut-off points.

RESULTS

A cut-off point of 20 % of dilutional effect requiring also a 60 % dilutional ratio achieved a high specificity (95 % CI 91-98 %) with an adequate sensitivity (64 % CI 54-74 %). The Area Under Curve obtained was 0.867 (95 % CI 0.819-0.915).

CONCLUSIONS

Our algorithm based on the global dilutional effect presents a similar sensitivity but greater specificity than the systems based on alarming results. The implementation of this algorithm in the laboratory information systems may facilitate the automated detection of contaminated samples.

Contamination of clinical blood samples with crystalloid solutions: An experimental approach to derive multianalyte delta checks

BACKGROUND

Laboratorians are left unguided by a paucity of literature on how to configure rules for the detection of intravenous (IV) fluid contamination in blood samples. We designed a study to determine the in vitro effect of increasing blood sample contamination from commonly used crystalloid solutions and how these observations can guide the derivation of multianalyte delta checks to detect such pre-analytical error.

METHODS

In this study, we spiked increasing volumes of commonly used IV fluids (normal saline (NS), lactated ringers (LR), and 5% dextrose) into blood samples that were collected from healthy donors. Routine chemistry analytes were measured and compared between neat and contrived samples. From these observations, we derived several permutations of multianalyte delta checks using the basic metabolic panel framework and evaluated rule performance using retrospective data.

RESULTS

The wet chemistry experiments showed that increasing the volume of crystalloid solution contamination significantly changed several analytes. Subsequently derived multianalyte delta check procedures were applied to retrospective data. For all IV fluids tested, smaller magnitudes of analyte change resulted in more samples flagged.

CONCLUSION

Multianalyte delta checks may be an effective method for the detection of IV fluid contamination.

A Comparative Study of Blood Sampling From Venipuncture and Short Peripheral Catheters in Pediatric Inpatients

This prospective, comparative study examined blood test results, hemolysis rates, and patient perceptions related to 2 blood sampling methods in pediatric inpatients (N = 95). Blood specimens were drawn via venipuncture and a short peripheral catheter used for fluid administration. Results revealed no significant differences in potassium and glucose levels. No clinically significant difference in hemoglobin was noted. Hemolysis rates were 4% for venipuncture samples and 15% when drawn from peripheral catheters. One catheter became occluded after a blood draw. Patients/parents rated distress and dissatisfaction with venipuncture as significantly greater compared with short peripheral catheter blood sampling (P < .001).

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.

Blood gas sample spiking with total parenteral nutrition, lipid emulsion, and concentrated dextrose solutions as a model for predicting sample contamination based on glucose result

OBJECTIVE

Evaluate the effects of blood gas sample contamination with total parenteral nutrition (TPN)/lipid emulsion and dextrose 50% (D50) solutions on blood gas and electrolyte measurement; and determine whether glucose concentration can predict blood gas sample contamination with TPN/lipid emulsion or D50.

DESIGN AND METHODS

Residual lithium heparin arterial blood gas samples were spiked with TPN/lipid emulsion (0 to 15%) and D50 solutions (0 to 2.5%). Blood gas (pH, pCO2, pO2), electrolytes (Na+, K+ ionized calcium) and hemoglobin were measured with a Radiometer ABL90. Glucose concentration was measured in separated plasma by Roche Cobas c501. Chart review of neonatal blood gas results with glucose >300 mg/dL (>16.65 mmol/L) over a seven month period was performed to determine whether repeat (within 4 h) blood gas results suggested pre-analytical errors in blood gas results. Results were used to determine whether a glucose threshold could predict contamination resulting in blood gas and electrolyte results with greater than laboratory-defined allowable error.

RESULTS

Samples spiked with 5% or more TPN/lipid emulsion solution or 1% D50 showed glucose concentration >500 mg/dL (>27.75 mmol/L) and produced blood gas (pH, pO₂, pCO₂) results with greater than laboratory-defined allowable error. TPN/lipid emulsion, but not D50, produced greater than allowable error in electrolyte (Na⁺,K⁺,Ca⁺⁺,Hb) results at these concentrations. Based on chart review of 144 neonatal blood gas results with glucose >250 mg/dL received over seven months, four of ten neonatal intensive care unit (NICU) patients with glucose results >500 mg/dL and repeat blood gas results within 4 h had results highly suggestive of pre-analytical error. Only 3 of 36 NICU patients with glucose results 300-500 mg/dL and repeat blood gas results within 4 h had clear pre-analytical errors in blood gas results.

CONCLUSION

Glucose concentration can be used as an indicator of significant blood sample contamination with either TPN/lipid emulsion or D50 solution. NICU blood gas samples with glucose ≥300 mg/dL should be considered potentially contaminated, and samples with glucose >500 mg/dL have a risk for contamination.

Autoverification process improvement by Six Sigma approach: Clinical chemistry & immunoassay

OBJECTIVE

This study examines effectiveness of a project to enhance an autoverification (AV) system through application of Six Sigma (DMAIC) process improvement strategies.

DESIGN AND METHODS

Similar AV systems set up at three sites underwent examination and modification to produce improved systems while monitoring proportions of samples autoverified, the time required for manual review and verification, sample processing time, and examining characteristics of tests not autoverified. This information was used to identify areas for improvement and monitor the impact of changes.

RESULTS

Use of reference range based criteria had the greatest impact on the proportion of tests autoverified. To improve AV process, reference range based criteria was replaced with extreme value limits based on a 99.5% test result interval, delta check criteria were broadened, and new specimen consistency rules were implemented. Decision guidance tools were also developed to assist staff using the AV system. The mean proportion of tests and samples autoverified improved from <62% for samples and <80% for tests, to >90% for samples and >95% for tests across all three sites. The new AV system significantly decreased turn-around time and total sample review time (to about a third), however, time spent for manual review of held samples almost tripled. There was no evidence of compromise to the quality of testing process and <1% of samples held for exceeding delta check or extreme limits required corrective action.

CONCLUSIONS

The Six Sigma (DMAIC) process improvement methodology was successfully applied to AV systems resulting in an increase in overall test and sample AV by >90%, improved turn-around time, reduced time for manual verification, and with no obvious compromise to quality or error detection.

Exogenous sample contamination. Sources and interference

Clinical laboratory medicine is involved in the vast majority of patient care pathways. It has been estimated that pathology results inform 60-70% of critical patient care decisions. The primary goal of the laboratory is to produce precise and accurate results which reflect the true situation in vivo. It is not surprising that interference occurs in laboratory analysis given the complexity of some of the assays used to perform them. Interference is defined as "the effect of a substance upon any step in the determination of the concentration or catalytic activity of the metabolite". Exogenous interferences are defined as those that derive from outside of the body and are therefore not normally found in a specimen and can cause either a positive or negative bias in analytical results. Interferences in analysis can come from various sources and can be classified as endogenous or exogenous. Exogenous substances could be introduced at any point in the sample journey. The laboratory must take responsibility for the quality of results produced. It has a responsibility to have processes in place to identify and minimise the occurrence and effect contamination and interference. To do this well the laboratory needs to work with clinicians and manufacturers. Failure to identify an erroneous result could have an impact on patient care, patient safety and also on hospital budgets. However it is not always easy to recognise interferences. This review summarises the types and sources of exogenous interference and some steps to minimise the impact they have.

The effect of hyperglycemia on blood coagulation: In vitro, observational healthy-volunteer study using rotational thromboelastometry (ROTEM)

We performed a study to investigate whether contamination of hemostasis samples with a glucose-containing solution might generate spurious results in rotational thromboelastometry (ROTEM) tests.Venous blood was taken from 12 healthy volunteers and divided into 4 specimen bottles, which were contaminated with different concentrations (0%, 5%, 10%, and 20%) of glucose solution.Significant lengthening of INTEMCT was observed in the 10% and 20% groups compared with baseline values (7.7% and 9%, P = 0.041 and P = 0.037, respectively). INTEMCFT increased by 20.1% in the 20% group (P = 0.005). INTEMα-angle and INTEMMCF decreased by 3.9% and 2.7%, respectively, in the 20% group (P = 0.010 and P = 0.049, respectively). EXTEMCFT was prolonged significantly, by 10.2%, 15.5%, and 25.6%, in the 5%, 10%, and 20% groups, respectively (P = 0.004, P < 0.001, and P < 0.001, respectively). EXTEMα-angle decreased significantly by 1.9%, 3.2%, and 4.0% in the 5%, 10%, and 20% groups, respectively (P = 0.014, P = 0.001, and P = 0.005, respectively). EXTEMMCF decreased by 3.4% in the 20% group (P = 0.023). FIBTEMMCF decreased by 9.2% and 17.5% in the 10% and 20% groups, respectively (P = 0.019 and P = 0.021, respectively). A significant correlation was observed between standard glucose solution contamination in the specimens and percentage variation of EXTEMCFT, EXTEMMCF, and FIBTEMMCF.To obtain accurate data from the ROTEM test regarding the hemostatic status of patients, specimens with suspected or known contamination should not be analyzed.