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.
# COLCHI-MYO: Transparent Colchicine-Associated Neuromyopathy Risk-Context Stratification Before or During Therapy **Authors:** Dr. Erick Zamora-Tehozol, DNAI, RheumaAI **ORCID:** 0000-0002-7888-3961 ## Abstract Colchicine remains an important anti-inflammatory drug in gout, calcium pyrophosphate disease, pericarditis, and selected autoinflammatory disorders, but clinically meaningful toxicity can emerge when exposure rises because of renal failure, dialysis, interacting drugs, or prolonged treatment.
ALLO-SCAR is an executable clinical skill for transparent allopurinol severe cutaneous adverse reaction risk-context stratification before initiation or during early toxicity assessment. The model integrates HLA-B*58:01 status, ancestry context, chronic kidney disease, allopurinol dose, diuretic exposure, cardiovascular comorbidity or hypertension, prior rash, timing since start, and early warning signs including fever, facial edema, mucosal involvement, eosinophilia, transaminitis, and creatinine rise.
Febuxostat is an important urate-lowering option when allopurinol is not tolerated, contraindicated, or ineffective, but cardiovascular safety remains a real bedside concern in patients with gout and high cardiac comorbidity. We present **FEBUX-CV**, a transparent executable skill for cardiovascular risk-context stratification before or during febuxostat exposure.
TNF-HF is an executable Python clinical skill for transparent heart-failure decompensation risk stratification before or during TNF inhibitor therapy in rheumatic and autoimmune disease. The model integrates TNF agent, NYHA class, left ventricular ejection fraction, prior heart-failure hospitalization, NT-proBNP, loop diuretic use, ischemic heart disease, uncontrolled hypertension, chronic kidney disease, diabetes, congestion symptoms, and recent TNF start or escalation timing.
MTX-PNEUMO is an executable Python clinical skill for transparent methotrexate-associated pneumonitis risk stratification in rheumatic and autoimmune disease. The model integrates age, time since methotrexate initiation, weekly dose, pre-existing ILD/fibrosis, abnormal baseline chest imaging, prior DMARD lung toxicity, diabetes, hypoalbuminemia, CKD, dyspnea, dry cough, fever, hypoxemia, eosinophilia, diffuse interstitial or ground-glass imaging pattern, and whether infection has been excluded.
We present CYCLO-OVA, an executable Python skill for transparent ovarian-failure risk stratification before or during cyclophosphamide exposure in rheumatic and autoimmune disease. The model integrates age, planned cumulative dose, oral daily versus pulse exposure, prior cyclophosphamide exposure, baseline low ovarian reserve or prior amenorrhea, expectation of repeated treatment cycles, other gonadotoxic exposures, fertility goals, GnRH agonist mitigation planning, and availability of less gonadotoxic alternatives.
Leflunomide-associated interstitial lung toxicity is uncommon but clinically important because presentations can be abrupt, severe, and difficult to separate from rheumatoid arthritis-associated interstitial lung disease or pulmonary infection. The bedside problem is not merely whether the adverse event is rare.
Lower gastrointestinal perforation during IL-6 blockade is uncommon but clinically serious, and tocilizumab has repeatedly been associated with higher rates of diverticulitis-related lower-GI perforation than several alternative biologic strategies in rheumatoid arthritis cohorts. We present TCZ-PERF, an executable Python skill for transparent risk stratification before or during tocilizumab use in rheumatic and autoimmune disease.
MMF-PREG is an executable clinical skill for transparent reproductive-safety triage around mycophenolate use in rheumatic and autoimmune disease. It addresses a real bedside problem: fetal-teratogenic exposure risk and preconception transition failure when patients remain on mycophenolate during possible conception, stop it without completed washout, or lack a pregnancy-compatible maintenance plan.
RTX-IGG is an executable clinical skill for transparent monitoring-oriented risk stratification of rituximab-associated hypogammaglobulinemia and infection vulnerability in rheumatic and autoimmune disease. The model integrates baseline and current IgG, IgM, rituximab course count, recency of dosing, maintenance intent, cyclophosphamide and glucocorticoid exposure, lymphocyte count, prior serious infection, chronic lung disease, kidney disease, and persistent B-cell suppression.
We present MTX-LIVER, an executable Python skill for transparent liver-safety risk stratification before or during low-dose methotrexate therapy in rheumatic and autoimmune disease. The model integrates obesity, diabetes, known steatosis/NAFLD, alcohol exposure, chronic hepatitis B/C, baseline and current aminotransferases, albumin, platelet count, methotrexate weekly dose, treatment duration, cumulative dose, folate supplementation, concomitant leflunomide, and persistent transaminitis.
Janus kinase inhibitors are effective therapies for rheumatoid arthritis and other autoimmune diseases, but thrombotic safety concerns remain clinically important. We present VTE-JAK, an executable Python skill for transparent pre-treatment and treatment-review stratification of venous thromboembolism risk in patients being considered for JAK inhibitor therapy.
Executable clinical skill for steroid-induced hyperglycemia risk stratification using baseline glycemic vulnerability, glucocorticoid exposure burden, and host susceptibility in rheumatic and autoimmune disease.
Fibromyalgia overlap commonly inflates composite disease activity measures in rheumatoid arthritis and related inflammatory rheumatic disease, creating risk of unnecessary biologic or immunosuppressive escalation. We present FIBRO-OVERLAP, an executable transparent clinical skill that integrates subjective symptom burden, objective inflammatory markers, tender-to-swollen joint mismatch, optional 2016 fibromyalgia criteria support, and imaging context to estimate likely fibromyalgia-driven inflation of apparent inflammatory activity.
Thiopurines remain clinically useful across rheumatology and systemic autoimmune disease, but preventable myelotoxicity still occurs when pharmacogenetic risk, baseline blood counts, interacting medications, and monitoring readiness are reviewed separately instead of together. We present THIO-SAFE, a transparent 10-domain weighted bedside score for estimating near-term azathioprine myelotoxicity risk.
We present GI-BLEED-NSAID, a transparent 10-domain clinical decision-support score for estimating near-term upper gastrointestinal bleeding risk before or during NSAID therapy in rheumatic and autoimmune disease. The model addresses a common real-world problem: deciding when standard NSAID use is acceptable, when proton pump inhibitor gastroprotection or COX-2 selection should be prioritized, and when nonselective NSAIDs should be avoided because cumulative bleeding risk is too high.
We present the Optimistic Response Verification System (ORVS) with Quantum Semantic (QS) retrieval, a verification-first architecture for specialist clinical AI in rheumatology. ORVS generates candidate responses optimistically, then subjects each to a structured verification loop scored across four weighted dimensions: clinical accuracy (0.