A quantitative clinical decision support tool designed to predict adverse pregnancy outcomes in patients with Systemic Lupus Erythematosus and Antiphospholipid Syndrome.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install pregna-risk
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install pregna-risk using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is PREGNA-RISK?
PREGNA-RISK is a specialized clinical tool within the Openclaw Skills ecosystem designed to address the high-risk nature of pregnancy in patients with Systemic Lupus Erythematosus (SLE) and Antiphospholipid Syndrome (APS). By integrating serological, clinical, and pharmacological data, it provides a weighted composite score that predicts the likelihood of adverse pregnancy outcomes (APO) such as preeclampsia, fetal loss, and preterm birth.
Developed by board-certified rheumatologists and AI experts, this skill moves beyond subjective clinical judgment. It utilizes evidence-based weights derived from landmark studies like PROMISSE and the Hopkins Lupus Cohort. The inclusion of Openclaw Skills in a clinical workflow allows for precise, reproducible risk stratification that can guide preconception counseling and tailor the intensity of obstetric monitoring.
PREGNA-RISK Use Cases
- Preconception counseling to determine the safety of starting a pregnancy based on disease activity.
- Risk stratification for pregnant patients with SLE or APS to determine the frequency of rheumatology and MFM follow-ups.
- Clinical research and data analysis for SLE/APS cohorts to standardize risk assessment across study populations.
- Identifying patients who require aggressive prophylactic interventions such as LMWH or low-dose aspirin.
How PREGNA-RISK Works
- The user inputs clinical parameters, including disease activity (SLEDAI-2K), renal function (eGFR), and serological markers (aPL status, dsDNA).
- The skill applies a weighted composite score formula: $$S = \sum_{i} w_i \cdot x_i, \quad x_i \in {0,1}$$.
- A Monte Carlo simulation is executed with 10,000 iterations, applying a ±20% perturbation to weights to calculate a 95% confidence interval.
- The system categorizes the patient into a Risk Category (Low, Moderate, High, or Very High) based on the final score.
- Actionable clinical recommendations are generated, ranging from standard monitoring to inpatient care.
PREGNA-RISK Setup
To integrate this medical risk tool into your workflow, ensure you have Python installed and follow these steps:
# Install the necessary numerical processing library
pip install numpy
# Run the stratification tool
python3 pregna_risk.py
PREGNA-RISK Data Schema & Taxonomy
PREGNA-RISK organizes its data based on clinical evidence weights. The primary data structure includes:
| Data Point | Weight Type | Source Registry |
|---|---|---|
| Active Nephritis | +25 (High Risk) | Bramham et al. |
| Triple aPL Positivity | +20 (High Risk) | Pengo et al. |
| Hydroxychloroquine Use | -10 (Protective) | Leroux et al. |
| Disease Quiescence | -12 (Protective) | EULAR Recs |
The output data provides a numerical score, a risk classification string, and a 95% confidence interval derived from simulation metadata.
PREGNA-RISK Advanced Features
- Monte Carlo Uncertainty Estimation: Performs 10,000 simulations to capture epistemic uncertainty in risk weight calibration.
- Protective Factor Integration: Unlike simple risk checklists, this Openclaw Skills tool accounts for protective treatments like HCQ and aspirin to lower the net risk score.
- Multidisciplinary Logic: Categorizes results into specific management paths for Maternal-Fetal Medicine (MFM) and Rheumatology specialists.
- Evidence-Linked Scoring: Every weight in the model is mapped directly to peer-reviewed clinical trials and registries.
SKILL.md
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