ArticleInternational journal of laboratory hematology2026
Design and Implementation of an Automated Interpretation Algorithm for Lupus Anticoagulant Functional Testing.
Article in International journal of laboratory hematology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
introductionLupus anticoagulant (LA) testing is essential, albeit complex, in the laboratory diagnosis of antiphospholipid syndrome (APS). Given the multi-step workflow and the variability introduced by anticoagulant therapy, reagent differences, and interpretive approaches, result interpretation requires expert evaluation. To address these challenges, we implemented a middleware-based automated algorithm in our four-hospital institution using the HemoHub system, guided by the latest ISTH recommendations. The objectives were to automate reflex testing, standardize interpretation, and support clinical decision-making.
methodsThe algorithm incorporated rules aligned with good laboratory practice for LA diagnostics, including reflex testing, result interpretation, internal comments, integration of historical data, and auto-validation of negative cases. Retrospective validation was performed on 190 historical cases in which the diagnosis was made conventionally and corroborated by follow-up data. A subsequent prospective blind comparison with manual operator-based workflow was conducted on 481 routine samples.
resultsConcordance between automated and manual interpretations reached 100% for LA negative and positive cases, with slightly lower agreement for first-time positives (88.6% and 82.4%). When automated interpretation was not assignable, the system still provided useful internal comments. Additionally, 58.4% of samples were auto-validated, significantly reducing manual workload. Time comparison demonstrated substantial savings for both experienced and less-experienced pathologists.
conclusionThe implementation of the automated algorithm improved consistency, reduced interpretation time, and minimized intra- and inter-laboratory variability. By integrating clinical context and historical data, it enhanced diagnostic accuracy. These findings support the use of middleware-based, rule-driven interpretation as a reliable and efficient approach to standardizing LA testing and optimizing laboratory workflow.
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