Heparin-induced thrombocytopenia (HIT) is a life-threatening drug reaction caused by anti-platelet factor 4/heparin (anti-PF4/H) antibodies. Commercial tests to detect these antibodies have limitations. We previously developed a diagnostic algorithm for HIT that incorporated "four Ts" (4Ts) scoring and a stratified interpretation of an anti-PF4/H enzyme-linked immunosorbent assay (ELISA) and yielded a discriminant accuracy of 0.97 (95% CI: 0.93-1.00).
The purpose of this study was to validate the algorithm in an independent patient population and quantitate effects that algorithm adherence could have on clinical care.
A retrospective cohort comprised patients who had undergone anti-PF4/H ELISA and serotonin release assay (SRA) testing in our healthcare system from 2010 to 2014. We determined the algorithm recommendation for each patient, compared recommendations to the clinical care received, and enumerated consequences of discrepancies. Operating characteristics were calculated for algorithm recommendations using SRA as the gold standard.
Analysis was performed on 181 patients, ten of whom ruled-in for HIT. The algorithm accurately stratified 98% of patients (95% CI: 95-99%), ruling-out HIT in 158, ruling-in HIT in ten, and recommending an SRA in 13 patients. Algorithm adherence would have obviated 165 SRAs and prevented 30 courses of unnecessary antithrombotic therapy for HIT. Diagnostic sensitivity was 0.82 (95% CI: 0.48-0.98), specificity 0.99 (95% CI: 0.97-1.00), PPV 0.90 (95% CI: 0.56-0.99) and NPV 0.99 (95% CI: 0.96-1.00).
An algorithm incorporating 4Ts scoring and a stratified interpretation of the anti-PF4/H ELISA has good operating characteristics and the potential to improve management of suspected HIT patients. This article is protected by copyright. All rights reserved.
This research output has an Altmetric Attention Score of 5. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 29 July 2017.
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#10,524,745
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#36
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