Analysis of patient results distributions to reevaluate a reference range change for calcium, after a change in assay reagents on the Roche Cobas c500 analyzer

Introduction: A change in reagents for calcium (Ca) on the Roche Cobas c500 used in our laboratory analyzer took place in 2013. The previous reference range (8.5-10.5 mg/dL) was replaced with that from the manufacturer\u27s study (8.6-10.0 mg/dL), based on correlation of results between the new and old assays. As a matter of quality assurance, we undertook a post-assay-change reevaluation of the reference range change, using a method based on that of Bhattacharya [1]. In short, the method relies on the assumption that the reference range is a normal distribution, which assumption enables this distribution to be isolated mathematically from within all-comers patient distribution data that are not normally distributed

Drug Interaction Study Of Apixaban With Cyclosporine Or Tacrolimus: Results From A Phase 1, Randomized, Open-Label, Crossover Study In Healthy Volunteers

BACKGROUND Solid organ transplant recipients commonly require anticoagulation. Apixaban (APX) is principally metabolized by CYP3A4, undergoes direct intestinal excretion, and is a substrate to P-glycoprotein (P-gp) and Breast Cancer Resistance Protein (BCRP) transporters. We examined the potential drug interaction between cyclosporine (CsA) and tacrolimus (Tac) [combined inhibitors of CYP3A4, P-gp and, BCRP] with APX.https://jdc.jefferson.edu/petposters/1005/thumbnail.jp

Assessment of utility of daily patient results averages as adjunct quality control in a weekday-only satellite chemistry laboratory

ABSTRACT Background: Our department operates a weekday-only (8AM-5PM) satellite laboratory in an infusion center with a menu of 18 chemistry tests on a Roche c501 analyzer. We examined whether daily patient results averages (PRA) in this setting might be useful as a patient-based quality control (PBQC) adjunct to standard daily liquid quality control (LQC) measurements. First, we evaluated the reproducibility (coefficient of variation, CV) of daily PRAs for each analyte, and compared these to CVs of LQC. Second, for select analytes found to have relatively low PRA CVs, we evaluated the extent to which use of daily PRA measurements could improve detection of analytical errors when combined with LQC. Methods: Patient results data for approximately one month (21 weekdays) were obtained from the Sunquest laboratory information system. For calculation of patient results averages (PRA), qualifying results were restricted to those within the reference range for each analyte. PRA and standard deviation (S) of PRA across 21 days was calculated for each analyte. Coefficients of variation for PRA (CV-PRA) were compared to those observed for standard liquid quality control (LQC) measurements (CV-LQC). For those analytes for which CV-PRA was less than CV-LQC, we evaluated the potential advantage of addition of PRA to daily LQC. For each analyte, a presumed PRA shift was determined such that probability of detection (P) was 0.5 when using LQC alone (viz., using high LQC and low LQC measurements), according to criterion that at least one 1-2S deviation from mean was obtained. For this same PRA shift, P = 0.5 for LQC alone was compared to P obtained for LQC + PRA (viz., using high LQC, low LQC, and PRA measurements), according to the same criterion. Results: Across 21 days, the number of results per day per assay ranged from 23 ±4 (uric acid) to 75 ±21 (electrolytes). Qualifying results (results within the reference range) ranged from 70 ± 6 % (LDH) to 99 ± 1 % (Cl). Seven analytes had CV-PRA \u3c CV-LQC (analyte, CV%): albumin, 1.25%; Ca, 0.67%; Cl, 0.62%; CO2, 1.13%; creatinine, 3.44%; K, 1.14%; Na, 0.65%. The remainder did not meet this criterion: ALP, 3.7%; ALT, 5.2%; AST, 5.1%; BUN, 4.6%; glucose, 1.4%; LDH, 2.0%; Mg, 1.4%; P, 2.5%; protein, 0.9%; TBIL, 6.1%; uric acid, 4.3%. Among the seven analytes for which CV-PRA \u3c CV-LQC, probability (P) of shift detection by LQC for circumstances as described in Methods (LQC P = 0.5) was increased substantially by inclusion of PRA (analyte, shift in analyte concentration, P): CO2, ±1.07 mmol/L, 0.97; creatinine, ±0.099 mg/dL, 0.93; albumin, ±0.126 g/dL, 0.85; Ca, ±0.14 mg/dL, 0.80; K, ±0.097 mmol/L, 0.76; Cl, ±1.24 mmol/L, 0.74; Na, ±1.48 mmol/L, 0.68. Conclusions: For 7 analytes, daily PRA demonstrated CVs less than those for LQC. For these analytes, calculations demonstrated that daily PRA can increase probability of detection of small results shifts when used as an adjunct to LQC. Daily PRA is a simple and essentially cost-free form of PBQC that may be useful for certain analytes in part-time laboratory settings