Sequential combinations of rapid immunoassays for prompt recognition of heparin-induced thrombocytopenia Available to Purchase

• A Bayesian approach combining pretest probability with likelihood ratio of quantitative IA results allows accurate HIT diagnostic workup.

• Sequential combinations of 2 rapid immunoassays for HIT antibodies perform better in comparison to the use of a single immunoassay.

Early recognition and treatment of heparin-induced thrombocytopenia (HIT) are crucial to prevent severe complications. Although immunoassays offer rapid diagnosis, their sensitivity and specificity are suboptimal. Sequential combinations of quantitative immunoassay results improve their diagnostic accuracy. We aimed to validate 2 Bayesian approaches combining 2 rapid immunoassays and to compare their diagnostic performance with 2 other diagnostic approaches (Hamilton and TORADI-HIT algorithms). We included 1194 patients with suspected HIT, of whom 6.0% had confirmed HIT. HemosIL Acustar HIT-IgG (chemiluminescent immune assay [CLIA]) and HemosIL HIT-Ab (latex immune-turbidimetric assay [LIA]) (Instrumentation Laboratory, Munich, Germany) were performed. Definite HIT confirmation or exclusion was made using heparin-induced platelet activation (HIPA) test and platelet factor 4–enhanced HIPA (PIPA). Our sequential approaches (CLIA first and LIA for 15-20% unsolved cases or vice versa) correctly excluded HIT in 95.6% and 96.4%, predicted HIT in 95.8% and 97.2%, with 3.3% and 2.3% of cases remaining undetermined; there were no false-negative predictions, and 13 and 15 false-positive predictions, respectively The modified version of the Hamilton algorithm correctly excluded HIT in 92.1% and predicted HIT in 97.2% with 88 false-positive and 2 false-negative results. The TORADI-HIT algorithm correctly excluded HIT in 97.9% and predicted HIT in 93.8% (10 false positives, 3 false negatives). In conclusion, a Bayesian approach sequentially using 2 immunoassays is accurate for HIT diagnosis. Performing immunoassays simultaneously without considering clinical pretest probability misses HIT cases. The TORADI-HIT algorithm offers better HIT exclusion with a 6% false-negative rate. Using our Bayesian approach, HIT exclusion or recognition can be achieved in ≥97% of cases within <1 hour.