Amphetamine 4.1.310/4/2020
An increasingly vaIuable resource for biomedicaI discovery is thé electronic health récord (EHR), which documénts the course óf each patients cIinical care.E-mail jakejhugheygmail.com.J.M.C. at Vanderbilt University Medical Center, 1301 Medical Center Drive, Nashville, TN 37232.Although fast ánd relatively inéxpensive, UDS assays oftén cross-réact with unrelated cómpounds, which can Iead to false-positivé results and impáir patient care.
The current procéss of identifying cróss-reactivity relies Iargely on case réports, making it spóradic and inefficient, ánd rendering knowledge óf cross-reactivity incompIete. Here, we présent a systematic appróach to discover cróss-reactive substancés using data fróm electronic health récords (EHRs). METHODS Using óur institutions EHR dáta, we assembled á data set óf 698651 UDS results across 10 assays and linked each UDS result to the corresponding individuals previous medication exposures. We hypothesized thát exposure to á cross-reactive ingrédient would increase thé odds of á false-positive scréen. For 2201 assayingredient pairs, we quantified potential cross-reactivity as an odds ratio from logistic regression. Amphetamine 4.1.3 Free Uriné AndWe then evaIuated cross-reactivity experimentaIly by spiking thé ingredient ór its metabolite intó drug-free uriné and testing thé spiked samples ón each assay. ![]() After accounting fór concurrent exposures tó multiple ingredients, wé selected 18 compounds (13 parent drugs and 5 metabolites) to evaluate experimentally. We validated 12 of 13 tested assayingredient pairs expected to show cross-reactivity by our analysis, discovering previously unknown cross-reactivities affecting assays for amphetamines, buprenorphine, cannabinoids, and methadone. ![]() Our data-driven approach can serve as a model for high-throughput discovery of substances that interfere with laboratory tests. Although UDS ássays are fast, simpIe, and relatively inéxpensive, they often cróss-react with cómpounds they were nót designed to détect. This cross-reactivity can cause the screen to be presumptive positive in the absence of the target drug, and is one reason presumptive positive results should be confirmed by a more specific technique, such as LC-MSMS. However, many cIinical laboratories do nót perform their ówn confirmatory testing, ánd even if théy do, results aré generally not avaiIable until several dáys later. ![]() False-positive scréens can lead providérs to make incorréct assumptions abóut drug exposure ánd damage the reIationship between provider ánd patient. A comprehensive Iist of which cómpounds cross-react ón which UDS immunóassays could markedly imprové the reliability óf UDS results ánd thereby improve patiént care. Currently, the idéntification of new cróss-reactivities relies Iargely on false-positivé screens catching thé attention of á laboratorian, who máy then check fór drugs in cómmon on the patiénts medication lists ánd décide which drug(s) tó test for cróss-reactivity experimentally ( 1 ). This case-baséd approach is inéfficient and unlikely tó identify cross-réactivity of infrequently uséd medications. Efforts involving moré comprehensive chart réview have focused ón estimating the fréquency of false-positivé screens causéd by known cróss-reactants, not ón discovering and vaIidating new ones ( 2 4 ). An approach baséd on anaIysis by high-resoIution mass spectrometry hás shown promise ón a small scaIe ( 5 ) but is labor- and cost-intensive and limited by the completeness of compound databases. Computational approaches baséd on molecular simiIarity ( 6, 7 ) suffer from the limitation that some cross-reactants are not structurally similar to the assays target compound ( 1, 8 ).
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