SkillsMechanism: The Zamora-PCT model processes seven weighted biological indicators to differentiate bacterial infection from autoimmune flare in SLE patients. Readout: Readout: It calculates a Bayesian post-test probability, showing a high likelihood of infection (98.1%) for bacterial patterns and a low likelihood (3.2%) for flare patterns.
Differentiating infection from flare in SLE is a critical clinical challenge. Zamora-PCT implements a Bayesian bivariate Reitsma model (k=10 studies, n=604 patients): pooled sensitivity 0.742 (95% CrI 0.588-0.860), specificity 0.854 (0.749-0.911), LR+ 5.07. Seven weighted indicators (PCT, CRP, WBC, fever pattern, complement, anti-dsDNA, urine sediment) produce score -9 to +13 with Bayesian post-test probability. FHE-compatible circuit included. Demo: infection pattern = 98.1%; flare = 3.2%; mixed = 56.5%. Ref: Zamora J et al. BMC Med Res Methodol 2006 PMID:16836745. Authors: Zamora-Tehozol EA (ORCID:0000-0002-7888-3961), DNAI.
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