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<p>Lupus anticoagulant (LAC) testing is central to antiphospholipid syndrome diagnostics and thrombotic risk assessment, but guideline-based workflows can be operationally complex, resource-intensive, and highly imbalanced. In our real-world cohort, completed LAC evaluations required an average of approximately 7 downstream clot-based assays, while nearly 90% of final classifications were negative. We developed and evaluated MINI-LAC™ (Minimal Lupus Anticoagulant), a biologically grounded digital decision-support framework designed for early exclusion of cases highly likely to yield negative final LAC classifications using routinely available pre-LAC coagulation parameters. Across 7454 LAC evaluations from a tertiary medical center, the phospholipid-poor versus phospholipid-rich activated partial thromboplastin time ratio (PTT-FSL/PTT-FS) demonstrated strong discrimination across LAC outcome categories (<i>p</i> &lt; 10<sup>−53</sup>) and consistently emerged as the dominant predictive feature. In the independent prospective cohort and complete-case analyses, MINI-LAC achieved approximately 98% negative predictive value, with preserved performance in analyses not relying on imputation of the primary biomarker, while maintaining full guideline-based evaluation for all non-negative or uncertain cases. These findings support integration of biologically meaningful functional coagulation signals into digital laboratory decision support to improve efficiency in LAC diagnostics.</p>

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Digital decision support using a phospholipid-dependent biomarker for early exclusion of negative cases in lupus anticoagulant diagnostics

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月25日

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  • Khen Khermesh,
  • Yaniv Alon,
  • Roi Gatt,
  • Irina Shalev,
  • Tanya Badelbayev,
  • Yifat Alcalay,
  • Varda Deutsch,
  • Ilia Kirgner,
  • Mor Saban,
  • Ben-Zion Katz

摘要

Lupus anticoagulant (LAC) testing is central to antiphospholipid syndrome diagnostics and thrombotic risk assessment, but guideline-based workflows can be operationally complex, resource-intensive, and highly imbalanced. In our real-world cohort, completed LAC evaluations required an average of approximately 7 downstream clot-based assays, while nearly 90% of final classifications were negative. We developed and evaluated MINI-LAC™ (Minimal Lupus Anticoagulant), a biologically grounded digital decision-support framework designed for early exclusion of cases highly likely to yield negative final LAC classifications using routinely available pre-LAC coagulation parameters. Across 7454 LAC evaluations from a tertiary medical center, the phospholipid-poor versus phospholipid-rich activated partial thromboplastin time ratio (PTT-FSL/PTT-FS) demonstrated strong discrimination across LAC outcome categories (p < 10−53) and consistently emerged as the dominant predictive feature. In the independent prospective cohort and complete-case analyses, MINI-LAC achieved approximately 98% negative predictive value, with preserved performance in analyses not relying on imputation of the primary biomarker, while maintaining full guideline-based evaluation for all non-negative or uncertain cases. These findings support integration of biologically meaningful functional coagulation signals into digital laboratory decision support to improve efficiency in LAC diagnostics.