OSTEO-GC: Glucocorticoid-Induced Osteoporosis Modeling

Models BMD T-score trajectories and 10-year fracture risk in chronic glucocorticoid users with uncertainty and ACR 2022 osteoporosis treatment guidance.

Security Scan

The skill's code and instructions are consistent with a local, offline clinical BMD/T-score projection tool and do not request unexplained credentials or external network access in the visible portions, but the provided source appears truncated so full-file review is recommended before use in production.

Purpose & Capability

Name, description, SKILL.md usage example, and the included python module all align: a Monte Carlo T-score/fracture-risk projector that embeds ACR-style guidance. Required binaries/env/config are none, which is proportionate for a pure-Python modelling utility.

Instruction Scope

SKILL.md instructs only local usage (importing functions, calling project_tscore, printing report). It does not instruct reading unrelated system files, accessing environment variables, or sending data externally in the visible instructions.

Install Mechanism

No install spec (instruction-only) and the code declares only Python standard-library dependencies. No downloads or archive extraction are requested.

Credentials

The skill declares no environment variables or credentials and the visible code does not reference os.environ, secrets, or any external service credentials—appropriate for the stated purpose.

Persistence & Privilege

always is false and the skill is user-invocable (normal); there are no instructions or code that attempt to modify other skills or system-wide configurations in the reviewed portions.

Assessment

What to check before installing: 1) Review the complete osteo_gc.py file (the provided snippet was truncated) to confirm there are no hidden network calls, file writes, subprocesses, or use of environment variables at the end of the file. 2) Run a local static scan (look for imports like requests, urllib, socket, subprocess, os.environ, open) and run the code in an isolated environment with non-identifiable test data. 3) Do not use outputs as sole clinical decision-making—this appears to be a modeling aid and should be validated clinically against known cases and local guidelines. 4) Confirm license/attribution and validate the clinical assumptions (dose-response, FRAX approximations, treatment effect sizes) match your institutional practice before acting on recommendations.

OSTEO-GC: Glucocorticoid-Induced Osteoporosis T-Score Trajectory Model

Description

Executable clinical skill for modeling bone mineral density (BMD) T-score trajectories in patients on chronic glucocorticoid therapy. Implements stochastic trajectory projection with Monte Carlo uncertainty estimation, FRAX-inspired 10-year fracture probability, and ACR 2022 GIOP treatment guidance.

Authors

• Erick Adrián Zamora Tehozol (Board-Certified Rheumatologist)
• DNAI (Root Ethical AI Agent, DeSci)
• Claw 🦞

Part of the RheumaAI ecosystem by Frutero Club.

Clinical Problem

Glucocorticoid-induced osteoporosis (GIOP) is the most common form of secondary osteoporosis, affecting 30-50% of patients on chronic GCs. Bone loss is biphasic: rapid (6-12% trabecular in year 1) then chronic (2-3%/yr). Fracture risk increases within 3 months of GC initiation, often before DXA changes are detectable. Clinicians need tools to project bone loss trajectories and guide preventive treatment per ACR 2022 guidelines.

Features

• Prednisone equivalence for 10 glucocorticoids (prednisone, dexamethasone, methylprednisolone, deflazacort, etc.)
• Multi-site T-score projection (lumbar spine, femoral neck, total hip) at 6mo, 1yr, 2yr, 5yr
• Monte Carlo simulation (5000 iterations) with 95% confidence intervals
• Dose-response modeling: <2.5mg, 2.5-5mg, 5-7.5mg, 7.5-15mg, >15mg strata
• Treatment effect modifiers: bisphosphonates (~50% reduction), denosumab (~65%), teriparatide (anabolic reversal)
• FRAX-inspired fracture probability: 10-year major osteoporotic + hip fracture risk
• ACR 2022 GIOP risk stratification: Low / Moderate / High / Very High
• Treatment recommendations: pharmacologic choice, monitoring schedule, GC tapering guidance

Usage

from osteo_gc import PatientProfile, project_tscore, print_report

patient = PatientProfile(
    age=65, sex="F", bmi=24.0,
    t_score_lumbar=-1.8, t_score_femoral_neck=-1.5,
    gc_name="prednisone", gc_dose_mg=10.0,
    gc_duration_months=6, gc_planned_months=12,
    postmenopausal=True, prior_fracture=False,
    treatment="none", calcium_vitd=False,
)
result = project_tscore(patient, seed=42)
print_report(result)

Dependencies

Python 3.8+ standard library only (math, random, dataclasses, typing). No external packages required.

References

1. Buckley L et al. 2017 ACR Guideline for GIOP. Arthritis Care Res 2017;69(8):1095-1110.
2. Compston J et al. Glucocorticoid-induced osteoporosis. Lancet Diabetes Endocrinol 2018;6:801-811.
3. Weinstein RS. Glucocorticoid-induced bone disease. N Engl J Med 2011;365:62-70.
4. Van Staa TP et al. Bone density threshold and other predictors of vertebral fracture. Arthritis Rheum 2003;48:3224-3229.
5. Kanis JA et al. FRAX and the assessment of fracture probability. Osteoporos Int 2008;19:385-397.