Up in Smoke: Uncovering a Lack of Evidence for Proton Pump Inhibitors as a Source of Tetrahydrocannabinol Immunoassay False Positives.

Objective: It is recommended that positives in immunoassay drug screens be followed up with more specific confirmatory testing. The drug package insert for pantoprazole mentions reports of false-positive urine screening tests for tetrahydrocannabinol in patients receiving proton pump inhibitors, but no method details or data are given, referenced, or found in literature searches. Thus, we investigated this using our laboratory's assay. Methods: A spiked sample and samples from 32 patients taking a proton pump inhibitor were analyzed using the EMIT II Plus Cannabinoid assay with a 20 ng/mL cutoff. Additionally, we examined urine samples from 50 patients with false-positive or low-positive screens for evidence of a proton pump inhibitor. To determine whether O-desmethyl pantoprazole sulfate, the major metabolite, shares any structural or electrostatic similarity to suggest a basis for cross-reactivity in the immunoassay, we used computational techniques for analyses. Molecular electrostatic potential energy (MEP) maps were calculated for the global minimum conformers, and the maximum common substructure Tanimoto similarity was calculated for the modeled compounds. Results: Neither the spiked sample nor the patient samples were found to screen positive. None of the false-positive or low-positive screens were found to contain a proton pump inhibitor. Computational studies showed very little similarity in shape or electrostatics between the two molecules. Conclusions: We find no supporting evidence of pantoprazole as the cause of false positives in the EMIT II Plus Cannabinoid assay and caution the use of proton pump inhibitors as an explanation for tetrahydrocannabinol immunoassay false positives.

Lowering the Bar for Mass Spectrometry: A Comparison between Immunoassay and Rapid Time-of-Flight for Presumptive Screening of Drugs in Urine.

BACKGROUND: Immunoassay-based techniques and creatinine quantification have historically been the methods of choice for urine drug screening. Positive presumptive drug screen results are reflexed to more specific, confirmatory testing using gas or liquid chromatography coupled to mass spectrometry. False positives and false negatives with immunoassay techniques are common problems that have substantial down-stream consequences for patient care, laboratory operations, and total costs. METHODS: The final workflow included rapid enzymatic hydrolysis, rapid liquid chromatographic methods, and time-of-flight mass spectrometry for detection. In total, 84 drugs and metabolites were included and reported qualitatively using 11 isotopically labeled internal standards selected to represent compound classes, retention time, and expected abundances to control for method inefficiencies and matrix suppression/enhancement. The method performance validation included 420 individual urine specimens. RESULTS: Of the 420 samples screened by immunoassay, 117 failed to confirm by mass spectrometry and were immunoassay false positives. None of these 117 samples screened positive on the liquid chromatography time-of-flight mass spectrometry (LC-TOF-MS) assay. The LC-TOF-MS method failed to detect 1 sample in each of the following classes: buprenorphine, ethanol markers, and opiates owing to concentrations below the established cutoffs. Out of 579 samples, 275 (47.4%) screened positive by LC-TOF-MS for nicotine and at least 2 of its metabolites. Quantitative creatinine comparison to an existing Jaffe method yielded a slope of 0.91 and a correlation coefficient of 0.96. CONCLUSIONS: We investigated whether immunoassay-based drug screening and creatinine quantification could be sufficiently replaced by a rapid LC-TOF-MS screen with higher specificity and accuracy than existing methods. The LC-LC-TOF-MS method is a sensitive and more specific way to screen for drugs, providing creatinine quantification and potential novel specimen validity testing with the inclusion of nicotine metabolites.

Ordering of the Serum Angiotensin-Converting Enzyme Test in Patients Receiving Angiotensin-Converting Enzyme Inhibitor Therapy: An Avoidable but Common Error.

BACKGROUND: Serum angiotensin-converting enzyme (ACE) levels may be decreased by use of ACE inhibitor (ACEI) medication. In this study, we determined how often ACE levels were measured in patients receiving ACEI therapy. METHODS: ACE levels analyzed over a 54-month preintervention time period at an academic medical center were reviewed retrospectively for tests performed during ACEI therapy. These data were compared with a large, deidentified dataset of ACE levels measured at a national reference laboratory; in vitro studies of ACEI inhibition; and liquid chromatography time-of-flight mass spectrometry detection of lisinopril in a subset of clinical specimens. RESULTS: Over a 54-month period, 1,292 patients had ACE levels measured, with 108 patients (8.4%) receiving ACEI therapy at the time of testing. ACE levels measured for patients receiving ACEI therapy were substantially lower. In general, clinical teams did not recognize a medication effect on ACE levels. Introduction of a warning prompt in the electronic health record reduced the ordering of ACE levels in patients receiving ACEIs by > 60% in a 17-month postintervention time period. The deidentified dataset of ACE levels at a reference laboratory showed a bimodal distribution, with a peak of very low ACE levels. Using liquid chromatography time-of-flight mass spectrometry, the presence of lisinopril was confirmed in a subset of specimens with low ACE activity. In vitro studies of two different ACE assays showed significant inhibition of activity at clinically relevant concentrations. CONCLUSIONS: Assessment of ACE activity is often measured for patients receiving ACEIs, potentially leading to low ACE concentrations and inaccurate interpretations.

Utilization of the clinical laboratory for the implementation of concussion biomarkers in collegiate football and the necessity of personalized and predictive athlete specific reference intervals.

BACKGROUND: A continued interest in concussion biomarkers makes the eventual implementation of identified biomarkers into routine concussion assessment an eventual reality. We sought to develop and test an interdisciplinary approach that could be used to integrate blood-based biomarkers into the established concussion management program for a collegiate football team. METHODS: We used a CLIA-certified laboratory for all testing and chose biomarkers where clinically validated testing was available as would be required for results used in clinical decision making. We summarized the existing methods and results for concussion assessment across an entire season to identify and demonstrate the challenges with the eventual integration of a parallel process using blood-based tests for concussion management. We analyzed the results of the biomarkers chosen for trends consistent with the outcome assessments provided from the current concussion management protocols. RESULTS: Baseline samples were collected with three additional post-concussion samples collected at three separate time points from players with a diagnosed concussion (n = 12). A summary of results from currently used concussion assessment tools were compared to the representative biomarkers S100B and NSE results. Nine sport-related concussions occurred during practice and three during play. For S100B, 50 % had follow-up testing results lower than the post-injury result. In contrast, 92 % of NSE follow-up results were lower than post-injury. One hundred percent of the results for S100B and NSE were within the athlete-derived reference intervals upon return-to-play and season end. CONCLUSIONS: The reported workflow provides a framework for the eventual implementation of biomarkers for concussion assessment into existing assessment protocols and strengthens the need for reliance on clinical laboratory testing. Athlete-specific reference intervals will be required to adequately interpret results.