Journal of Applied Laboratory Medicine最新文献

Background: Aging is associated with subclinical changes in cardiac structure and function as well as an increase in prevalent cardiovascular disease and geriatric syndromes such as frailty and sarcopenia. This can result in levels of cardiac-specific and non-cardiac-specific circulating biomarkers that are frequently above normal range concentrations established in healthy middle-age general population cohorts in the absence of acute disease. Without this recognition, clinicians may be challenged to interpret biomarker results in older adults in the setting of diagnosing an acute illness or for longer term prognostication.

Content: In this review, we provide anticipated findings, their suggested underlying mechanism, as well as interpretation of concentrations for the common cardiovascular biomarkers including cardiac troponins and natriuretic peptides in the acute care and ambulatory settings. Specifically, information to interpret biomarkers in the setting of possible acute myocardial infarction and heart failure is presented. We also present data for interpreting results in older adults with other well-known prognostic biomarkers, as well as biomarkers with application to geriatric syndromes.

Summary: Circulating biomarkers, despite challenges in interpretation in older adults relative to younger adults, play a critical role in the diagnosis and prognosis of cardiovascular disease and have additional roles in geriatric syndromes and assessing risk of harm from specific treatments.

Background: Not all quantity values determined in a medical laboratory are obtained by direct analytical measurement. In many situations, a quantity value is calculated from other measurements through a functional relationship, where the output quantity is derived from one or more input quantities by applying a defined mathematical equation. Even though important for clinical interpretation, the measurement uncertainty (MU) of calculated quantities may not always be considered.

Content: The prostate health index (phi) has been shown to improve the clinical assessment of prostate cancer. Estimates for the MU of phi have been recently provided by a novel approach in which the uncertainty of phi was directly calculated from internal quality control (IQC). However, this method for determining MU generally provides a higher estimate than the procedure recommended by the "Evaluation of Measurement Data-Guide to the Expression of Uncertainty in Measurement" (GUM) and does not allow for the incorporation of a correlation term. A full evaluation of the MU for phi by the GUM procedure is provided.

Summary: The importance of the GUM approach with the inclusion of correlation terms is clearly shown by the phi calculation. By comparison, the relative standard uncertainty obtained by the direct IQC procedure for a mean phi value of 24.48 was given as 7.2%, while by GUM, the relative standard uncertainty for the same mean phi was 3.60% with correlation included and 5.99% without correlation. The influence of correlation terms within the GUM equations is clearly shown for the phi calculation.

Background: Fluid pH remains a standard test when evaluating pleural effusions. Studies recommend using a blood gas analyzer to measure fluid pH immediately after sample collection. Centralization of laboratory services at our institution led to migration of blood gas analysis to a single core laboratory with uncertain impacts on pH results.

Methods: Pleural fluid samples were obtained from 30 patients during routine clinical care, excluding those with frank purulence or blood. Fluid pH and pCO2 were measured on a blood gas analyzer. We compared samples collected in plastic screw-top vials from commercially available thoracentesis kits vs paired samples collected in blood gas syringes. We also examined how differences in processing time, fluid pCO2, and heparin anticoagulant correlated with measured pH.

Results: Of the 30 paired samples obtained, 25 (83.3%) were exudates and 5 (16.7%) were transudates. All samples collected in blood gas syringes had lower mean pH and higher mean pCO2 than samples collected in plastic screw-top vials (mean pH difference ± SD, 0.16 ± 0.06; P < 0.001) (mean pCO2 difference ± SD, 14.09 ± 6.92; P < 0.001). Differences in fluid pH were independent of total nucleated cell count (range 65-28 380 cells/mm3). Neither the presence of heparin in the syringe nor time delays up to 2 h between collection and analysis meaningfully impacted the pH result (P = 0.51 and P = 0.75, respectively).

Conclusion: To accurately measure pleural fluid pH, specimens should be collected anaerobically in blood gas syringes rather than the screw-top vials provided in thoracentesis kits.

Background: While clinical laboratories routinely perform automated chemistry assays on approved specimens (e.g., plasma and serum), the FDA has not evaluated the validity of these assays for nonapproved specimens (e.g., various body fluids). To meet College of American Pathologists' regulatory requirements, clinical laboratories must evaluate body fluid matrix effects. However, full validation studies are challenging due to time and labor demands. Therefore, a rapid and practical approach for validating body fluids benefits clinical laboratories by improving efficiency and minimizing resources utilized.

Methods: Excess body fluids and plasma specimens were collected and frozen until testing was performed. Pooled body fluid specimens were spiked with a 10% spike solution (pooled plasma) containing analyte mixtures with measured concentrations. Matrix interference studies and dilution studies were performed on the Roche cobas automated (6000/8000) analyzers.

Results: The matrix effects for albumin, amylase, blood urea nitrogen, cholesterol, creatinine, glucose, lactate, lactate dehydrogenase, lipase, potassium, sodium, total bilirubin, total protein, triglycerides, and uric acid were all within acceptable limits (±20% of full recovery). However, lipase was observed to be unstable in peritoneal fluid. Dilution linearity was confirmed for all analytes in pleural, peritoneal, ascites, and synovial fluids (R2 > 0.90).

Conclusions: Our study describes a rapid and practical approach for evaluating body fluid matrix effects in automated clinical chemistry assays. By streamlining the validation process, this approach can help laboratories maintain compliance while minimizing time and resources.

Background: Elevated concentrations of the glycoprotein soluble urokinase plasminogen activator receptor (suPAR) predict worse cardiovascular disease (CVD) outcomes. However, glycosylation effects on its measurement are unknown.

Methods: Plasma samples were obtained from healthy volunteers (n = 70), patients with and without myocardial infarction (MI) from an acute chest pain cohort (n = 65), and patients with and without acute decompensated heart failure (ADHF) from an acute breathlessness cohort (n = 103). After the addition of either deglycosylation enzymes or a diluent to paired samples from each patient, subsequent measurements for suPAR were undertaken with the suPARnostic assay. Percentage change in concentrations between enzyme-treated and matched nontreated samples was calculated. MI and ADHF discrimination by receiver operating characteristic area under the curve was used to compare performances of nontreated suPAR vs deglycosylated suPAR.

Results: Following deglycosylation, measured suPAR concentrations are increased by a median of 52.8% (from 1.9 to 3.0 ng/mL, P < 0.0001) in healthy subjects. Similar increases for deglycosylated suPAR were observed in MI (53.6%) and non-MI acute chest pain patients (53.3%). Although acutely breathless patients obtained smaller increases in deglycosylated suPAR values than healthy individuals (P < 0.0001), the percentage increase was higher in ADHF (38.6%) compared to non-HF (24.4%, P = 0.002) patients. ADHF discrimination was superior for deglycosylated suPAR than non-treated suPAR (0.850 vs 0.765, P = 0.003), but no differences were observed for MI discrimination (0.485 vs 0.501, P = 0.508).

Conclusions: Glycosylation underestimates suPAR measurement using the suPARnostic assay. Although glycosylation effects varied across patient groups, removal of suPAR glycosylation appears to enhance heart failure discrimination.

Background: Proficiency testing (PT) should identify systematic errors, which are likely to recur. The Clinical Laboratory Improvement Amendments of 1988 (CLIA) acceptance limits (ALs) include 3 standard deviations (3SD) and concentration limits. We investigated the ability of PT to detect systematic error, especially as affected by the different AL types.

Methods: We removed any ungradable, duplicate, and irregular scores from CLIA laboratory PT data from 2008 to 2018. We calculated the overall miss rate, unsatisfactory event rate, i.e., score <80 (4 of 5 correct), and event rates for score 100 to 0. We used paired t-tests and the Wilcoxon signed-rank test to compare miss rates and unsatisfactory event rates between short- and long-term PT participants. We used the binomial distribution to estimate the expected event scores under the assumption that all misses were independent (random). We compared observed event scores with their expected values as a ratio.

Results: Forty thousand five hundred ninety-six laboratories produced 15 140 128 event scores for 75 analytes. The distribution of event scores was skewed toward multiple event misses (score 0-60) compared to the predicted distribution. Miss rates and unsatisfactory rates were significantly higher for short-term laboratories. Plotting the log ratio of observed vs expected rates for event scores showed that the degree of systematic effect was substantial. The magnitude of the effect was less for 3SD ALs.

Conclusions: In an event, PT misses are often dependent. All ALs detected systematic error. Expressing systematic error using PT data could help to identify and remediate analytical issues.