Algorithm for Rapid Exclusion of Clinically Relevant Plasma Levels of Direct Oral Anticoagulants in Patients Using the DOAC Dipstick: An Expert Consensus Paper.
BACKGROUND: With the widespread use of direct oral anticoagulants (DOACs), there is an urgent need for a rapid assay to exclude clinically relevant plasma levels. Accurate and rapid determination of DOAC levels would guide medical decision-making to (1) determine the potential contribution of the DOAC to spontaneous or trauma-induced hemorrhage; (2) identify appropriate candidates for reversal, or (3) optimize the timing of urgent surgery or intervention. METHODS AND RESULTS: The DOAC Dipstick test uses a disposable strip to identify factor Xa- or thrombin inhibitors in a urine sample. Based on the results of a systematic literature search followed by an analysis of a simple pooling of five retrieved clinical studies, the test strip has a high sensitivity and an acceptably high negative predictive value when compared with levels measured with liquid chromatography tandem mass spectrometry or calibrated chromogenic assays to reliably exclude plasma DOAC concentrations ≥30 ng/mL. CONCLUSION: Based on these data, a simple algorithm is proposed to enhance medical decision-making in acute care indications useful primarily in hospitals not having readily available quantitative tests and 24/7. This algorithm not only determines DOAC exposure but also differentiates between factor Xa and thrombin inhibitors to better guide clinical management.
Duke Scholars
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Related Subject Headings
- Tandem Mass Spectrometry
- Reproducibility of Results
- Reagent Strips
- Predictive Value of Tests
- Humans
- Hemorrhage
- Factor Xa Inhibitors
- Drug Monitoring
- Consensus
- Clinical Decision-Making
Citation
Published In
DOI
EISSN
Publication Date
Volume
Issue
Start / End Page
Location
Related Subject Headings
- Tandem Mass Spectrometry
- Reproducibility of Results
- Reagent Strips
- Predictive Value of Tests
- Humans
- Hemorrhage
- Factor Xa Inhibitors
- Drug Monitoring
- Consensus
- Clinical Decision-Making