New solutions to old problems: A practical approach to identify samples with intravenous fluid contamination in clinical laboratories

OBJECTIVES

Contamination with intravenous (IV) fluids is a common cause of specimen rejection or erroneous results in hospitalized patients. Identification of contaminated samples can be difficult. Common measures such as failed delta checks may not be adequately sensitive nor specific. This study aimed to determine detection criteria using commonly ordered tests to identify IV fluid contamination and validate the use of these criteria.

METHODS

Confirmed contaminated and non-contaminated samples were used to identify patterns in laboratory results to develop criteria to detect IV fluid contamination. The proposed criteria were implemented at a tertiary care hospital laboratory to assess performance prospectively for 6 months, and applied to retrospective chemistry results from 3 hospitals and 1 community lab to determine feasibility and flagging rates. The algorithm was also tested at an external institution for transferability.

RESULTS

The proposed algorithm had a positive predictive value of 92 %, negative predictive value of 91 % and overall agreement of 92 % when two or more criteria are met (n = 214). The flagging rates were 0.03 % to 0.07 % for hospital and 0.003 % for community laboratories.

CONCLUSIONS

The proposed algorithm identified true contamination with low false flagging rates in tertiary care urban hospital laboratories. Retrospective and prospective analysis suggest the algorithm is suitable for implementation in clinical laboratories to identify samples with possible IV fluid contamination for further investigation.

Evaluation of Laboratory Performance in Consideration with Pre analytical and Post analytical Quality Indicators

Implementation of Quality indicators (QIs) plays an imperative role in improving the total testing process, as it provides a quantitative basis for evaluating the laboratory performance. Besides monitoring of analytical quality specifications, several lines of experimental and clinical evidence have alluded a pivotal role of extra-analytical phases in improving the quality of laboratory services and therefore a relevance of pre- and post-analytical steps have been speculated on the overall quality in the total testing process and consequently on clinical decision-making. This was a retrospective study designed to evaluate and review different extra-analytical quality indicators in NABL accredited clinical biochemistry laboratory at BJ Medical College and Civil Hospital, Ahmedabad, Gujarat in an endeavour to ameliorate the performance of the laboratory. All Clinical Chemistry Laboratory test requests with their respective samples from January 2018 to December 2021 were included in the study. A total of 1,439,011samples were processed, and were evaluated for seven QIs [(% of number of suitable samples not received; QI-8), (% of number of samples received in inappropriate container; QI-9), (% of number of samples hemolysed; QI-10), (% of number of samples with inadequate sample volume; QI 12) (% of number of samples received mismatched; QI 15), (% of number of samples reported after turnaround time; QI 21) and (% of number of samples with critical values informed; QI 22)] based on defined criteria of Quality Specification given by International Federation of Clinical Chemistry. Total number of preanalytical errors was 53,669 (3.72%). Among the preanalytical errors, inadequate sample volume (2.37% of total samples; 63.49% of total pre-analytical errors) was the most common anomaly followed by Not received samples (24.18%) hemolysis (8.26%) mismatched (3.91%) and 0.14% samples were received in Inappropriate container; manifesting that the error frequency was unacceptable for QI 21 and QI 8, acceptable for QI 10, minimally acceptable for QI 15 and optimum for QI QI 9. Furthermore, there was year-wise progressive decline in error rate of inadequate sample volume, hemolysed sample received and mismatched samples. Total number of post analytical errors were 19,002 (1.32%). TAT outlier and critical values communicated were the two QIs evaluated for this phase and results of both QI were within acceptable limits. Quality indicators serve as a tool to monitor process performance and consequently derived error rates warrant active intervention to improve the laboratory services and patient health care. Dissemination of certified documents, regular staff training and evaluation needs to be conducted.

Optimizing d-mannose and glyceraldehyde concentrations as glucose preservatives without clinically affecting biochemical test results

Objectives: The objectives were to evaluate blood additives that combined lithium heparin (LH)-salt with glyceraldehyde (GLY) or d-mannose (MAN) for preserving glucose levels in plasma samples and to simultaneously determine the compatibility of these additives with 14 other biochemical tests.

Methods

Blood samples from 40 subjects, equally divided into healthy and diabetic groups, were collected using five different additives. The three most effective additives, LH/GLY, LH/MAN, and LH/GLY/MAN, were selected for ensuring the best preservation of glucose levels and compatibility with 14 biochemical tests. One-way analysis of variance was used to analyze the mean paired differences of glucose level and biochemical tests. Simultaneously, the clinical criteria from Johns Hopkins Hospital were used to guide the interpretation and set acceptable thresholds for measurements that exceeded the standards.

Results

The combination of 160 mmol/L GLY, 8.4 mmol/L MAN, and LH, maintained glucose levels at approximately 93.4-93.7 % for healthy subjects and 91.3-92.8% for subjects with diabetes mellitus over 8 h. The mean paired differences of glucose levels in preservation were statistically insignificant. The biases in 14 biochemical tests for LH/GLY/MAN and LH/MAN remained within the acceptable clinical criteria during the 8 h.

Conclusions

Combining 160 mmol/L GLY, 8.4 mmol/L MAN, and LH, proved more effective in maintaining glucose levels than individual additives or the conventional sodium fluoride preservative. It did not yield clinical discrepancies in the 14 biochemical tests during 8 h at room temperature.

Clinical Validation of a Novel Quality Management System for Blood Gas, Electrolytes, Metabolites, and CO-Oximetry

BACKGROUND

Quality management of point-of-care (POC) blood gas testing focuses on verifying instrument accuracy and precision, in addition to performing daily quality control (QC) checks every 8 h and with each patient test (unless internal calibration is verified every 30 min). At the POC, a risk-based approach is suitable to address both systemic and transient sample-specific errors that may negatively impact patient care.

METHODS

We evaluated the performance of the GEM® Premier™ 5000 with next generation Intelligent Quality Management 2 (iQM®2) (Instrumentation Laboratory, Bedford, MA), from the analysis of approximately 84,000 patient samples across 4 sites. Continuous iQM2 was compared to intermittent liquid QC, either manual or automated, at 2 sites. Analysis of error flags for patient samples and statistical characteristics of QC processes, including method sigma and average detection time (ADT) for an error, were examined.

RESULTS

ADT was approximately 2 min with iQM2 and varied from hours to days with intermittent QC. iQM2 Process Control Solutions (PCS) precision was similar or better (>6 sigma for all analytes) than manual (sigma 3.0 for pO2) or automated internal QC (sigma 1.3 for tHb and sigma 3.3 for pO2). In addition, iQM2 detected errors in ∼1.4% of samples, providing an additional safeguard against reporting erroneous results.

CONCLUSIONS

The findings in this study demonstrate excellent performance of the GEM Premier 5000 with iQM2 including >6 sigma precision for all analytes and faster error detection times. These benefits address risk in different phases of testing that are not easily detected by intermittent performance of liquid QC (manual or automated).

Assessment of the effects of repeated freeze thawing and extended bench top processing of plasma samples using untargeted metabolomics

INTRODUCTION

Clinical metabolomics has utility as a screen for inborn errors of metabolism (IEM) and variant classification in patients with rare disease. It is important to understand and characterize preanalytical factors that influence assay performance during patient sample testing.

OBJECTIVES

To evaluate the impact of extended thawing of human EDTA plasma samples on ice prior to extraction as well as repeated freeze-thaw cycling of samples to identify compounds that are unstable prior to metabolomic analysis.

METHODS

Twenty-four (24) donor EDTA plasma samples were collected and immediately frozen at - 80 °C. Twelve samples were thawed on ice and extracted for analysis at time 0, 2, 4, and 6 h. Twelve other donor samples were repeatedly thawed and frozen up to four times and analyzed at each cycle. Compound levels at each time point/freeze-thaw cycle were compared to the control samples using matched-paired t tests to identify analytes affected by each condition.

RESULTS

We identified 1026 biochemicals across all samples. Incubation of thawed EDTA plasma samples on ice for up to 6 h resulted in < 1% of biochemicals changing significantly. Freeze-thaw cycles affected a greater percentage of the metabolome; ~ 2% of biochemicals changed after 3 freeze-thaw cycles.

CONCLUSIONS

Our study highlights that the number and magnitude of these changes are not as widespread as other aspects of improper sample handling. In total, < 3% of the metabolome detected on our clinical metabolomics platform should be disqualified when multiple freeze-thaw cycles or extended thawing at 4 °C are performed on a given sample.

The impact of biosafety enhancement on stat laboratory quality metrics: Lessons from the COVID-19 pandemic

OBJECTIVE

It is unclear if implementation of biosafety action plans in response to the COVID-19 pandemic has affected laboratory quality metrics.

METHODS

This retrospective study used quality data, including turnaround time (TAT) and number/type of unacceptable specimens from a stat laboratory supporting an outpatient medical clinic serving predominantly elderly cancer patients. Four months of data from the height of the COVID-19 pandemic (March-June 2020) were compared to the same months in 2019.

RESULTS

March-May 2020 test volumes were decreased compared to 2019. June 2020 test volume was slightly increased compared to 2019. TATs in 2020 were similar/ slightly improved compared to the same months in 2019, due to shortened collect to receive and receive to verify TATs. The number and types of unacceptable specimens were similar in 2020 and 2019.

CONCLUSIONS

Despite the challenges to the system caused by the pandemic, laboratory quality metrics were maintained.

Reduction of pre-analytical errors in the clinical laboratory at the University Hospital of Korea through quality improvement activities

BACKGROUND

The clinical laboratory is responsible for reporting accurate and expeditious results. However, the pre-analytical phase is directly related to the procedure of specimen collection and is mostly out of the direct control of the laboratory; further, most pre-analytical errors are related to human factors. Therefore, education and training programs for the phlebotomy teams are considered the most significant and necessary measures to reduce these errors.

METHODS

A cross-sectional study was conducted to investigate the types and frequencies of pre-analytical errors in the hospital laboratory. Pre-analytical errors were categorized into four main categories: rejected sample, error related to test ordering, misidentification, and others. Several activities were performed for quality improvement in order to reduce the rates of these errors. The data were analyzed by comparing the pre-intervention and post-intervention results along with the results of questionnaires to assess knowledge to investigate the effects of the activities.

RESULTS

The rates of pre-analytical errors decreased from 0.42% in the pre-intervention period to 0.32% in the post-intervention period. The rejected sample category accounted for the highest rates in the pre- and post-intervention periods. In the questionnaires, the overall average score after the intervention was 71.5, which was a significant increase from 46.0 in the pre-intervention period.

CONCLUSIONS

Each clinical laboratory has various types of pre-analytical errors due to the complexity of the healthcare environment. Therefore, targeted intervention including a quality improvement program and its continuous maintenance should be conducted to reduce pre-analytical errors and to improve patient safety.

Relationship between free hemoglobin (hemolysis), potassium and ionized calcium in lithium heparin blood gas samples collected intraoperatively

OBJECTIVE

Develop sample acceptability rules by determining the relationship between free hemoglobin level (hemolysis) and potassium or ionized calcium in blood gas samples collected intraoperatively.

DESIGN AND METHODS

Hemolysis was assessed visually or by H index for lithium heparin blood gas samples collected intraoperatively. During periods one and three this was done using two different rules for visual assessment of centrifuged lithium heparin plasma. During period two H index was measured for all visually hemolyzed samples on a Roche Cobas c501 analyzer to determine acceptability. Potassium and ionized calcium were measured in 75 lithium heparin whole blood samples on a Radiometer ABL90 to correlate H index and potassium or ionized calcium.

RESULTS

During period one 35 of 5808 (0.6%) blood gas samples had visual hemolysis levels exceeding tolerance for reporting of potassium. By switching to measured H index using a laboratory-established threshold, during period 2 we estimate that 171 of 5396 (3.2%) blood gas samples exceeded the H index threshold for reporting of potassium. In 75 intraoperative blood gas samples with H index and whole blood potassium and ionized calcium measured; we observed no relationship between H index and potassium or ionized calcium. During period 3 we switched to visual assessment of hemolysis with a greater tolerance for hemolysis; with only 3 of 5345 (0.06%) samples exceeding the new visual hemolysis threshold.

CONCLUSION

For blood gas samples collected intraoperatively, there is no relationship between hemolysis and measured potassium or ionized calcium. The results suggest that only grossly hemolyzed intraoperative blood gas samples should be rejected for measurement of whole blood potassium and ionized calcium.

Indices of immune function used by ecologists are mostly unaffected by repeated freeze-thaw cycles and methodological deviations

BACKGROUND

Over the past couple of decades, measuring immunological parameters has become widespread in studies of ecology and evolution. A combination of different immunological indices is useful for quantifying different parts of the immune system and comprehensively assessing immune function. Running multiple immune assays usually requires samples to be repeatedly thawed and re-frozen. There is some evidence that repeated freezing and thawing can affect assay results, but this has never been comprehensively studied in some common ecological immunology assays. We tested the effect of multiple (1, 2, 3, 4, 5, 10) freeze-thaw cycles on the results of four commonly used immunological assays: haemolysis-haemagglutination titres, haptoglobin concentration, bacterial killing capacity and total immunoglobulins (IgY). We tested five different bird species from four different bird orders (Passeriformes, Columbiformes, Charadriiformes and Galliformes), and we included both captive and free-living individuals. In addition, we tested for haptoglobin concentrations and the haemolysis-haemagglutination assay if re-analysing samples 1 year apart led to different results. For the haemolysis-haemagglutination assay we also tested two different sources of rabbit blood, and we compared untreated microtitre plates with plates that were "blocked" to prevent nonspecific interactions between the plate and assay reagents.

RESULTS

Repeated freezing and thawing of plasma had no effect on lysis titres, haptoglobin concentrations, bacterial killing capacity, or total immunoglobulin levels. Agglutination titres were unaffected by up to five cycles but were lower after ten freeze-thaw cycles. For the haemolysis-haemagglutination assay and haptoglobin concentrations, re-analysing samples 1 year apart yielded highly correlated data. For the haemolysis-haemagglutination assay, the source of rabbit blood did not influence the results, and the untreated vs. blocked plates differed slightly overall, but at the individual level assay results were highly correlated. Using different rabbit blood sources or different types of microtitre plates yielded highly correlated data.

CONCLUSIONS

Our data suggest that repeated freeze-thaw cycles do not impair assay results to the point of influencing ecological or evolutionary conclusions. Plasma samples can be safely stored in one tube and thawed repeatedly for different assays. Nevertheless, we recommend consistent treatment of samples in terms of freeze-thaw cycles or other laboratory treatments to minimize the potential for introducing a systematic bias.

Active tracking of rejected dried blood samples in a large program in Nigeria

AIM: To study the impact of rejection at different levels of health care by retrospectively reviewing records of dried blood spot samples received at the molecular laboratory for human immunodeficiency virus (HIV) early infant diagnosis (EID) between January 2008 and December 2012.

METHODS: The specimen rejection rate, reasons for rejection and the impact of rejection at different levels of health care was examined. The extracted data were cleaned and checked for consistency and then de-duplicated using the unique patient and clinic identifiers. The cleaned data were ciphered and exported to SPSS version 19 (SPSS 2010 IBM Corp, New York, United States) for statistical analyses.

RESULTS: Sample rejection rate of 2.4% (n = 786/32552) and repeat rate of 8.8% (n = 69/786) were established. The mean age of infants presenting for first HIV molecular test among accepted valid samples was 17.83 wk (95%CI: 17.65-18.01) vs 20.30 wk (95%CI: 16.53-24.06) for repeated samples. HIV infection rate was 9.8% vs 15.9% for accepted and repeated samples. Compared to tertiary healthcare clinics, secondary and primary clinics had two-fold and three-fold higher likelihood of sample rejection, respectively (P < 0.05). We observed a significant increase in sample rejection rate with increasing number of EID clinics (r = 0.893, P = 0.041). The major reasons for rejection were improper sample collection (26.3%), improper labeling (16.4%) and insufficient blood (14.8%).

CONCLUSION: Programs should monitor pre-analytical variables and incorporate continuous quality improvement interventions to reduce errors associated with sample rejection and improve patient retention.