Evidence map›Paper›PMID 33216907›Full record

ArticleJournal of analytical toxicology2022

Analysis of Electronic Health Records Reveals Medication-Related Interference on Point-of-Care Urine Drug Screening Assays.

Nadia Ayala-Lopez, Jennifer M Colby, Jacob J Hughey

Open access · greenAbstract read
In one paragraph

Article in Journal of analytical toxicology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.3field-weighted citation impact, top 48% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 4 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 1 institution in 1 country.

Nadia Ayala-LopezDepartment of Pathology, Microbiology, and Immunology, Vanderbilt University Medical Center, 1161 21st Ave South, Nashville, TN, 37232 USA.
Jennifer M ColbyDepartment of Pathology, Microbiology, and Immunology, Vanderbilt University Medical Center, 1161 21st Ave South, Nashville, TN, 37232 USA.
Jacob J HugheyDepartment of Biomedical Informatics, Vanderbilt University Medical Center, 2525 West End Ave, Nashville, TN, 37203 USA.
Vanderbilt University Medical Center · US

Funding

Vanderbilt Institute for Clinical and Translational Research (VICTR) -Identifying correlates of functional immunity in SARS-CoV-2 convalescent plasmaUL1TR002243 · NCATS · VANDERBILT UNIVERSITY MEDICAL CENTER · PI Paul A. Harris, Wesley H Self · 2017 to 2026
$130.7M
NCATS NIH HHS UL1 TR002243NCATS NIH HHS UL1TR002243
6 · The paper itself

Abstract

Point-of-care (POC) urine drug screening (UDS) assays provide immediate information for patient management. However, POC UDS assays can produce false-positive results, which may not be recognized until confirmatory testing is completed several days later. To minimize the potential for patient harm, it is critical to identify sources of interference. Here, we applied an approach based on statistical analysis of electronic health record (EHR) data to identify medications that may cause false positives on POC UDS assays. From our institution's EHR data, we extracted 120,670 POC UDS and confirmation results, covering 12 classes of target drugs, along with each individual's prior medication exposures. Our approach is based on the idea that exposure to an interfering medication will increase the odds of a false-positive UDS result. For a given assay-medication pair, we quantified the association between medication exposures and UDS results as an odds ratio from logistic regression. We evaluated interference experimentally by spiking compounds into drug-free urine and testing the spiked samples on the POC device. Our dataset included 446 false-positive UDS results (presumptive positive screen followed by negative confirmation). We quantified the odds ratio of false positives for 528 assay-medication pairs. Of the six assay-medication pairs we evaluated experimentally, two showed interference capable of producing a presumptive positive: labetalol on the 3,4-methylenedioxymethamphetamine (MDMA) assay (at 200 μg/mL) and ranitidine on the methamphetamine assay (at 50 μg/mL). Ranitidine also produced a presumptive positive for opiates at 1,600 μg/mL and for propoxyphene at 800 μg/mL. These findings highlight the generalizability and the limits of our approach to use EHR data to identify medications that interfere with clinical immunoassays.

Indexed as

Electronic Health RecordsPoint-of-Care SystemsSubstance Abuse DetectionUrinalysisFalse Positive ReactionsHumans

Identifiers

PMID33216907
PMCPMC8841984
OpenAlexW3098370329

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.