Traceability validation of six enzyme measurements on the Abbott Alinity c analytical system

Documenting and validating metrological traceability of serum alanine aminotransferase measurements: a priority for medical laboratory community for providing high quality service in hepatology

Alanine aminotransferase (ALT) represents the first-level test to detect individuals with hepatocellular damage of any etiology. However, it has been highlighted that the lack of assay harmonization may lead to overdiagnosis and unnecessary further testing if guideline-recommended fixed cut-offs are uncritically employed. To solve the issue of ALT (dis)harmonization and improve the interpretation of its values, a series of urgent actions for documenting and validating metrological traceability of serum ALT measurements, as described in this paper, are no longer postponeable. It is time that all medical laboratory stakeholders (in vitro diagnostic manufacturers, laboratorians, external quality assessment scheme organizers) actively co-operate to implement the ALT standardization in a concerted action following well-established theoretical assumptions and applying experimental approaches described in literature.

Validation of metrological traceability of the new generation of Abbott Alinity alkaline phosphatase assay

OBJECTIVES

Recently, Abbott Diagnostics marketed a new generation of Alinity enzyme assays, introducing a multiparametric calibrator [Consolidated Chemistry Calibrator (ConCC)] in place of or in addition to factor-based calibrations. For alkaline phosphatase (ALP), both calibration options are offered, i.e., with ConCC (ALP2) and with an experimental calibration factor (ALP2F). Both options are declared traceable to the 2011 IFCC reference measurement procedure (RMP). Before to replace the old generation (ALP1) with the new one, we decided to validate the trueness of ALP2/ALP2F.

METHODS

Three approaches were employed: (a) preliminary comparison on 48 native frozen serum samples with ALP1, of which traceability to RMP was previously successfully verified; (b) examination of three banked serum pools (BSP) with values assigned by RMP; (c) direct comparison with RMP on a set of 24 fresh serum samples. Bias estimation and regression studies were performed, and the standard measurement uncertainty associated with ALP measurements on clinical samples (uresult) was estimated and compared with established analytical performance specifications (APS). ConCC commutability was also assessed.

RESULTS

A positive proportional bias was found with both ALP2 and ALP2F when compared to ALP1 and RMP. This positive bias was confirmed on BSP: in average, +13.1 % for ALP2 and +10.0 % for ALP2F, respectively. uresult were 13.28 % for ALP2 and 10.04 % for ALP2F, both not fulfilling the minimum APS of 4.0 %. Furthermore, ConCC was not commutable with clinical samples.

CONCLUSIONS

Our results unearth problems in the correct implementation of traceability of Alinity ALP2/ALP2F, with the risk for the new assay to be unfit for clinical purposes.

Definition and application of performance specifications for measurement uncertainty of 23 common laboratory tests: linking theory to daily practice

Laboratories should estimate and validate [using analytical performance specifications (APS)] the measurement uncertainty (MU) of performed tests. It is therefore essential to appropriately define APS for MU, but also to provide a perspective on suitability of the practical application of these APS. In this study, 23 commonly ordered measurands were allocated to the models defined during the 2014 EFLM Strategic Conference to derive APS for MU. Then, we checked if the performance of commercial measuring systems used in our laboratory may achieve them. Most measurands (serum alkaline phosphatase, aspartate aminotransferase, creatine kinase, γ-glutamyltransferase, lactate dehydrogenase, pancreatic amylase, total proteins, immunoglobulin G, A, M, magnesium, urate, and prostate-specific antigen, plasma homocysteine, and blood red and white cells) were allocated to the biological variation (BV) model and desirable APS were defined accordingly (2.65%, 4.75%, 7.25%, 4.45%, 2.60%, 3.15%, 1.30%, 2.20%, 2.50%, 2.95%, 1.44%, 4.16%, 3.40%, 3.52%, 1.55%, and 5.65%, respectively). Desirable APS for serum total cholesterol (3.00%) and urine albumin (9.00%) were derived using outcome-based model. Lacking outcome-based information, serum albumin, high-density lipoprotein cholesterol, triglycerides, and blood platelets were temporarily reallocated to BV model, the corresponding desirable APS being 1.25%, 2.84%, 9.90%, and 4.85%, respectively. A mix between the two previous models was employed for serum digoxin, with a 6.00% desirable APS. In daily practice by using our laboratory systems, 16 tests fulfilled desirable and five minimum APS, while two (serum albumin and plasma homocysteine) exceeded goals, needing improvements.

Protective Mechanism of Polygonum perfoliatum L. Extract on Chronic Alcoholic Liver Injury Based on UHPLC-QExactive Plus Mass Spectrometry Lipidomics and MALDI-TOF/TOF Mass Spectrometry Imaging

Polygonum perfoliatum L. has a long history of medicinal and edible applications. Studies have shown that it can significantly protect liver injury, but the mechanism is unclear. The purpose of this study was to explore the protective mechanism of P. perfoliatum on chronic alcoholic liver injury from the perspective of lipid metabolism. After 8 weeks of alcohol exposure in male Wister mice, the levels of aspartate aminotransferase (AST), alanine aminotransferase (ALT) and alkaline phosphatase (ALP) in serum were significantly increased, and the activities of alcohol dehydrogenase (ADH) and acetaldehyde dehydrogenase (ALDH) in liver were significantly decreased. Meanwhile, pathological changes of liver tissue in mice were observed by histopathology. Then, Ultra-High Performance Liquid Chromatography (UHPLC) QExactive Plus Mass Spectrometer lipidomics and matrix-assisted laser desorption/ionization time-of-flight/time -of-flight (MALDI-TOF/TOF) mass spectrometry imaging methods were established to analyze lipid metabolism in mice. Ten different lipids were identified by statistical analysis, including Fatty Acyls, Glycerophospholipids, Prenol lipids and Sphingomyelins. After intervention with P. perfoliatum extracts at different doses (25 to 100 mg/kg), levels of AST, ALT, ALP in serum, and activities of ADH and ALDH in liver were significantly corrected. The hepatic cord structure was clear, and the liver cells were closely arranged without other obvious abnormalities. Non-target lipidomics analysis showed that P. perfoliatum extract could regulate the metabolic disorders of the 10 different lipids caused by continuous alcohol exposure. Pathway analysis suggested that the mechanism of P. perfoliatum extract on chronic alcoholic liver injury may be related to the regulation of linoleic acid and α-linolenic acid.

Lipase elevation in serum of COVID-19 patients: frequency, extent of increase and clinical value

OBJECTIVES

Previous studies reported lipase elevations in serum of COVID-19 patients trying to establish a causal link between SARS-CoV-2 infection and pancreatic damage. However, the degree and prevalence of hyperlipasemia was not uniform across studies.

METHODS

We retrospectively evaluated 1,092 hospitalized patients with COVID-19 and at least one available lipase result. The number and frequency of patients with lipase above the upper reference limit (URL), >3 URL, and >6 URL were estimated. Correlations between lipase values and other biomarkers of organ or tissue damage were performed to identify possible extra-pancreatic sources of lipase release. The potential prognostic role of lipase to predict death and intensive care unit (ICU) admission during hospitalization was also evaluated.

RESULTS

Lipase was >URL in 344 (31.5%) of COVID-19 patients. Among them, 65 (5.9%) and 25 (2.3%) had a peak lipase >3 URL and >6 URL, respectively. In the latter group, three patients had acute pancreatitis of gallstone or drug-induced etiology. In others, the etiology of lipase elevations appeared multifactorial and could not be directly related to SARS-CoV-2 infection. No correlation was found between lipase and other tested biomarkers of organ and tissue damage. Lipase concentrations were not different between survivors and non-survivors; however, lipase was significantly increased (p<0.001) in patients admitted to the ICU, even if the odds ratio for lipase as predictor of ICU admission was not significant.

CONCLUSIONS

Lipase was elevated in ∼1/3 of COVID-19 patients, but the clinical significance of this finding is unclear and irrelevant to patient prognosis during hospitalization.

Sources and clinical significance of aspartate aminotransferase increases in COVID-19

BACKGROUND

Aspartate aminotransferase (AST) is often increased in COVID-19 and, in some studies, AST abnormalities were associated with mortality risk.

METHODS

2054 hospitalized COVID-19 patients were studied. To identify sources of AST release, correlations between AST peak values and other biomarkers of tissue damage, i.e., alanine aminotransferase (ALT) for hepatocellular damage, creatine kinase (CK) for muscle damage, lactate dehydrogenase for multiorgan involvement, alkaline phosphatase and γ-glutamyltransferase for cholestatic injury, and C-reactive protein (CRP) for systemic inflammation, were performed and coefficients of determination estimated. The role of AST to predict death and intensive care unit admission during hospitalization was also evaluated. All measurements were performed using standardized assays.

RESULTS

AST was increased in 69% of patients. Increases could be fully explained by summing the effects of hepatocellular injury [AST dependence from ALT, 66.8% [95% confidence interval (CI): 64.5-69.1)] and muscle damage [AST dependence from CK, 42.6% (CI: 39.3-45.8)]. We were unable to demonstrate an independent association of AST increases with worse outcomes.

CONCLUSION

The mechanisms for abnormal AST in COVID-19 are likely multifactorial and a status related to tissue suffering could play a significant role. The clinical significance of AST elevations remains unclear.

EQA/PT scheme to improve the equivalence of enzymatic results between mutual recognition laboratories in Beijing

Background

To utilize the external quality assessment (EQA)/proficiency testing (PT) scheme to evaluate the equivalence of different clinical enzymatic measuring systems in Beijing.

Methods

The Beijing Center for Clinical Laboratory (BCCL) distributed three investigation samples to mutual recognition clinical laboratories in Beijing including alanine aminotransferase (ALT), aspartate aminotransferase (AST), γ‐glutamyltransferase (GGT), creatine kinase (CK), and lactate dehydrogenase (LDH). These samples were derived from serum pools with values assigned by the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) enzymatic reference measurement procedures (RMPs). Each laboratory performed duplicate tests of the samples. Then, the samples at level 1 were used to recalibrate individual measuring systems for repeating the tests. BCCL collected data for evaluation of their analytical quality.

Results

Before recalibration, the biases of ALT and AST tests were not traceable to the IFCC RMPs, and the bias pass rates of GGT, CK, and LDH tests were only 51.2%, 55.7%, and 48.6% respectively. After recalibration, the pass rates of ALT, AST, GGT, CK, and LDH increased to 95.1%, 82.9%, 95.1%, 97.1%, and 70.0% respectively. The EQA/PT also showed that after recalibration, more than 95% of laboratories met the optimum level specifications of the biological variation for ALT, AST, GGT, and CK tests and the desirable for LDH tests.

Conclusion

The enzymatic tests in Beijing need to be further standardized by category 1 or 2 EQA/PT scheme for mutual recognition between clinical laboratories. The criteria of biological variation are more relevant for determining the equivalence of clinical enzymatic tests.

A Comprehensive Appraisal of Laboratory Biochemistry Tests as Major Predictors of COVID-19 Severity

CONTEXT.—

A relevant portion of coronavirus disease 2019 (COVID-19) patients develop severe disease with negative outcomes. Several biomarkers have been proposed to predict COVID-19 severity, but no definite interpretative criteria have been established to date for stratifying risk.

OBJECTIVE.—

To evaluate 6 serum biomarkers (C-reactive protein, lactate dehydrogenase, D-dimer, albumin, ferritin, and cardiac troponin T) for predicting COVID-19 severity and to define related cutoffs able to aid clinicians in risk stratification of hospitalized patients.

DESIGN.—

A retrospective study of 427 COVID-19 patients was performed. Patients were divided into groups based on their clinical outcome: nonsurvivors versus survivors and patients admitted to an intensive care unit versus others. Receiver operating characteristic curves and likelihood ratios were employed to define predictive cutoffs for evaluated markers.

RESULTS.—

Marker concentrations at peak were significantly different between groups for both selected outcomes. At univariate logistic regression analysis, all parameters were significantly associated with higher odds of death and intensive care. At the multivariate analysis, high concentrations of lactate dehydrogenase and low concentrations of albumin in serum remained significantly associated with higher odds of death, whereas only low lactate dehydrogenase activities remained associated with lower odds of intensive care admission. The best cutoffs for death prediction were greater than 731 U/L for lactate dehydrogenase and 18 g/L or lower for albumin, whereas a lactate dehydrogenase activity lower than 425 U/L was associated with a negative likelihood ratio of 0.10 for intensive treatment.

CONCLUSIONS.—

Our study identifies which biochemistry tests represent major predictors of COVID-19 severity and defines the best cutoffs for their use.

Searching for a role of procalcitonin determination in COVID-19: a study on a selected cohort of hospitalized patients

Objectives

Procalcitonin (PCT) has been proposed for differentiating viral vs. bacterial infections. In COVID-19, some preliminary results have shown that PCT testing could act as a predictor of bacterial co-infection and be a useful marker for assessment of disease severity.

Methods

We studied 83 COVID-19 hospitalized patients in whom PCT was specifically ordered by attending physicians. PCT results were evaluated according to the ability to accurately predict bacterial co-infections and death in comparison with other known biomarkers of infection and with major laboratory predictors of COVID-19 severity.

Results

Thirty-three (39.8%) patients suffered an in-hospital bacterial co-infection and 44 (53.0%) patients died. In predicting bacterial co-infection, PCT showed a relatively low accuracy (area under receiver-operating characteristic [ROC] curve [AUC]: 0.757; 95% confidence interval [CI]: 0.651-0.845), with a strength for detecting the outcome not significantly different from that of white blood cell count and C-reactive protein (CRP). In predicting patient death, PCT showed an AUC of 0.815 (CI: 0.714-0.892), not better than those of other more common laboratory tests, such as blood lymphocyte percentage (AUC: 0.874, p=0.19), serum lactate dehydrogenase (AUC: 0.860, p=0.47), blood neutrophil count (AUC: 0.845, p=0.59), and serum albumin (AUC: 0.839, p=0.73).

Conclusions

Procalcitonin (PCT) testing, even when appropriately ordered, did not provide a significant added value in COVID-19 patients when compared with more consolidated biomarkers of infection and poor clinical outcome. The major application of PCT in COVID-19 is its ability, associated with a negative predictive value >90%, to exclude a bacterial co-infection when a rule-out cut-off (<0.25 μg/L) is applied.

Lactate dehydrogenase: an old enzyme reborn as a COVID-19 marker (and not only)

Background Historically, the lactate dehydrogenase (LDH) measurement was introduced into Laboratory Medicine as component (together with creatine kinase (CK) and aspartate aminotransferase) of the classical enzyme triad employed for the diagnosis of myocardial infarction, which was subsequently replaced by CK-MB, and more recently by cardiac troponins. Afterwards, for many years, the clinical application of serum LDH measurement has been limited to the evaluation of anemias and to as a rough prognostic tool for certain tumors. Content In the last few years, significant changes have happened. First, the test has been confirmed as a robust predictor of poor outcomes in many neoplastic conditions. Furthermore, in the Revised International Staging System adopted in the 2015 by the International Myeloma Working Group, LDH acts as determinant of disease biology in differentiating myeloma stages. Finally, in the last few months, LDH is definitively reborn given its proven significant contribution in defining the COVID-19 severity. Conclusions This increased clinical role calls for an improvement of LDH assay standardization through the implementation of traceability of results of clinical samples to the available reference measurement system.

The internal quality control in the traceability era

To be accurate and equivalent, laboratory results should be traceable to higher-order references. Furthermore, their quality should fulfill acceptable measurement uncertainty (MU) as defined to fit the intended clinical use. With this aim, in vitro diagnostics (IVD) manufacturers should define a calibration hierarchy to assign traceable values to their system calibrators. Medical laboratories should know and verify how manufacturers have implemented the traceability of their calibrators and estimate the corresponding MU on clinical samples. Accordingly, the internal quality control (IQC) program should be redesigned to permit IVD traceability surveillance through the verification by medical laboratories that control materials, provided by the manufacturer as a part of measuring systems, are in the clinically suitable validation range (IQC component I). Separately, laboratories should also monitor the reliability of employed IVD measuring systems through the IQC component II, devoted to estimation of MU due to random effects and to obtaining MU of provided results, in order to apply prompt corrective actions if the performance is worsening when compared to appropriate analytical specifications, thus jeopardizing the clinical validity of test results.