ANEMIA-IMMUNE stratifies anemia in autoimmune disease by combining hemoglobin severity, MCV, ferritin, transferrin saturation, CRP, reticulocytes, kidney function, bleeding signals, hemolysis signals, and myelosuppressive drugs into a transparent 0-100 concern score and phenotype label. The implementation is executable Python and is intended to support differential diagnosis of iron deficiency, inflammation/CKD-pattern anemia, mixed anemia, and probable marrow-suppression/hemolysis context.
LEF-WASH is a transparent clinical heuristic for reproductive-safety triage when leflunomide is active, recently stopped, or being cleared before conception in rheumatic and autoimmune disease. The bedside problem is not whether the drug was merely discontinued, but whether cholestyramine washout occurred, whether teriflunomide clearance below 0.
ANIFRO-HZ is an executable, transparent clinical decision-support skill for stratifying herpes zoster concern in systemic lupus erythematosus during or soon after anifrolumab exposure. The bedside problem is not only knowing that zoster risk exists, but recognizing when glucocorticoids, lymphopenia, nephritis-level co-immunosuppression, absent recombinant zoster vaccination, and early symptom patterns create a treatment context that should alter monitoring or escalation.
## Abstract
Anticoagulation in antiphospholipid syndrome (APS) remains clinically contentious because the convenience of direct oral anticoagulants (DOACs) is not matched by uniform safety across APS phenotypes. The central bedside problem is not whether DOACs are ever usable, but whether a given patient sits in a high-risk phenotype where DOAC exposure is especially unfavorable.
Denosumab discontinuation creates a distinctive clinical hazard: vertebral-fracture risk can rebound rapidly when treatment is delayed or stopped without sequential antiresorptive therapy. This problem is especially relevant in rheumatology and glucocorticoid-treated osteoporosis, where missed injections may go unnoticed until new back pain or clustered vertebral fractures emerge.
RA-MODEL is an executable Python skill that consolidates standard rheumatoid arthritis disease-activity and function indices into one transparent longitudinal workflow. It computes DAS28-CRP, DAS28-ESR, CDAI, SDAI, Boolean remission, HAQ-DI, RAPID3, and a treat-to-target summary across serial visits.
Visual ischemic complications of giant cell arteritis (GCA) are among the most time-sensitive emergencies in rheumatology and ophthalmology because permanent vision loss can occur before diagnostic certainty is complete. GCA-VISION is an executable dependency-free Python skill that converts this bedside problem into a transparent 0-100 ocular ischemia risk-context score.
HCQ-QT is an executable Python skill for transparent QT-prolongation risk-context stratification before or during hydroxychloroquine therapy in rheumatic and autoimmune disease. It weights baseline QTc, sex-age context, kidney function, potassium and magnesium status, structural and arrhythmic cardiac history, bradycardia, concomitant QT-prolonging drugs, hydroxychloroquine dose intensity, and syncope or palpitations into a 0-100 concern score.
Osteonecrosis is a clinically meaningful but often underrecognized complication of systemic lupus erythematosus (SLE), especially after repeated pulse methylprednisolone exposure or sustained high cumulative glucocorticoid burden. The diagnostic problem is practical: early hip or groin pain may be normalized until structural injury is advanced, while the real risk context was created earlier by nephritis, steroid intensity, vascular-metabolic factors, and thrombosis biology.
PRES-LUPUS is an executable Python skill for transparent bedside risk-context stratification of posterior reversible encephalopathy syndrome in systemic lupus erythematosus. It addresses a real clinical recognition problem: when acute neurologic symptoms during lupus nephritis, severe hypertension, and high-intensity immunosuppression should trigger urgent PRES exclusion rather than delayed attribution to flare alone.
Autoimmune congenital heart block is a rare but high-consequence complication of anti-Ro/SSA pregnancies. NEO-LUPUS is an executable Python skill that converts the bedside surveillance problem into a transparent 0-100 risk-context score.
SRC-SHIELD is an executable Python skill for transparent scleroderma renal crisis risk-context stratification in systemic sclerosis. It weights diffuse cutaneous phenotype, early disease duration, anti-RNA polymerase III positivity, glucocorticoid exposure, new hypertension, creatinine rise, proteinuria, and microangiopathic features into a 0-100 concern score.
Occult Strongyloides stercoralis infection is an under-recognized safety problem in rheumatology and autoimmune care because clinically silent infection may accelerate into hyperinfection after glucocorticoids or other potent immunosuppression. STRONGY-GUARD is an executable Python skill that converts this bedside problem into a transparent 0-100 risk-context score using endemic exposure, eosinophilia, positive serology, positive stool/larvae, glucocorticoid intensity and duration, pulse methylprednisolone, rituximab/cyclophosphamide exposure, HTLV-1, compatible symptoms, gram-negative sepsis, current immunosuppression, and recent ivermectin treatment.
Vaccination planning around rituximab is a recurring clinical problem in rheumatic and autoimmune disease because clinicians must balance infection-prevention urgency against expected vaccine blunting after B-cell depletion. RTX-VAX is an executable Python skill for transparent readiness stratification before non-live vaccination.
Adult-onset Still disease activity is often described narratively despite major variability in systemic burden and MAS risk. AOSD-ACTIVITY is an executable Python skill that computes a transparent 12-item systemic feature score rooted in published Still disease literature, then layers practical MAS warning heuristics using ferritin, fibrinogen, platelet count, transaminases, and triglycerides when available.
AXSPA-MODEL is an executable clinical skill for axial spondyloarthritis follow-up. It combines BASDAI, ASDAS-CRP, ASDAS-ESR, BASFI, BASMI, ASQoL, EQ-5D VAS, and ASAS20/40 response into a transparent longitudinal treat-to-target framework.
Pegloticase can produce major improvement in uncontrolled gout, but safe use depends on recognizing G6PD deficiency, urate rebound, prior infusion reactions, weak monitoring setups, and danger symptoms before harm occurs. We present PEGLOTI-GUARD, an executable Python skill for transparent pegloticase infusion-safety risk-context stratification.
Medication-related osteonecrosis of the jaw (MRONJ) is uncommon in routine osteoporosis care, but when it occurs it is clinically disruptive, difficult to reverse, and often amplified by avoidable dental and host-level cofactors. ONJ-GUARD is an executable Python skill for transparent MRONJ risk-context stratification that integrates antiresorptive exposure type, therapy duration, invasive dental procedures, periodontal disease, oral trauma, glucocorticoids or immunosuppression, diabetes, smoking, prior MRONJ or exposed nonhealing bone, and active jaw symptoms.
We present ALLO-SAFE, a transparent executable clinical skill for relative risk stratification before or during very early allopurinol initiation. The model integrates HLA-B*58:01 status, ancestry-linked pretest concern, chronic kidney disease, planned starting dose, thiazide exposure, prior rash history, age, chronic liver disease, urgency pressure to start therapy, and baseline monitoring readiness.