PREGNA-RISK: Pregnancy Risk in SLE/APS

Calculates a weighted composite score predicting adverse pregnancy outcomes in SLE/APS patients to guide risk stratification and management.

Security Scan

This is a self-contained local risk‑scoring tool whose inputs, dependencies, and behavior line up with its stated purpose (no unexplained network access or secret requirements), though you should still validate clinical accuracy and provenance before using it in care.

Purpose & Capability

Name and description match the included code and instructions: a weighted composite risk score with Monte Carlo uncertainty estimation for SLE/APS pregnancy risk. The code implements the weights, scoring, classification, and reporting described in SKILL.md. One caution: registry metadata lists source/homepage as unknown — the package contains an implementation, but provenance and authorship claims (affiliations) are not verifiable from the registry entry.

Instruction Scope

SKILL.md only instructs installing numpy and running the local script; the script computes scores and prints a report. There are no instructions to read arbitrary system files, access environment variables, or send data to external endpoints.

Install Mechanism

Install spec is a single pip dependency (numpy). This is proportionate for Monte Carlo simulations. There is no download-from-URL, no extraction of remote archives, and no creation of nonstandard binaries.

Credentials

The skill requires no environment variables, no credentials, and no config paths. That is appropriate for a local calculator that performs purely local computation.

Persistence & Privilege

The skill is not always-enabled and requests no elevated or persistent privileges. It does not modify other skills or system settings.

Assessment

This code appears to be a straightforward, local risk calculator (no network calls or secret access). Before using it clinically: 1) review the full source (you have pregna_risk.py) to confirm behavior and to ensure no hidden I/O; 2) validate the model and weights against the cited literature and against real/known test cases; 3) run it in an isolated environment (virtualenv) and install numpy from PyPI; 4) do not feed identifiable patient data until you are satisfied with privacy practices — the tool prints reports to stdout and does not appear to exfiltrate data, but provenance is unclear (registry shows no homepage), so confirm authorship/maintenance and licensing; 5) treat outputs as decision support only and consult specialists before relying on the score for clinical care.

PREGNA-RISK: Pregnancy Risk Stratification in SLE/APS

Overview

Quantitative risk stratification tool for pregnancy in patients with Systemic Lupus Erythematosus (SLE) and/or Antiphospholipid Syndrome (APS). Computes a weighted composite score predicting adverse pregnancy outcomes (APO) including preeclampsia, fetal loss, preterm birth, and IUGR.

Authors

• Erick Adrián Zamora Tehozol (Board-Certified Rheumatologist)
• DNAI (Distributed Neural Artificial Intelligence)
• Claw 🦞

Clinical Problem

Pregnancy in SLE/APS carries 2-5x higher risk of adverse outcomes compared to general population. Current management relies on subjective clinical judgment. PREGNA-RISK provides an evidence-based composite score integrating serological, clinical, and treatment factors to guide preconception counseling and monitoring intensity.

Model

Risk Factors and Weights

Based on PROMISSE study (Buyon et al., NEJM 2015), Hopkins Lupus Cohort, and EUROAPS registry data:

Factor	Weight	Evidence
Active lupus nephritis (current or <6mo)	+25	Bramham et al. 2011, Smyth et al. 2010
Anti-dsDNA positive + low C3/C4	+15	Buyon PROMISSE 2015
Triple aPL positivity (LA+aCL+aβ2GPI)	+20	Pengo et al. 2018
LA positive (isolated)	+12	PROMISSE 2015
aCL >40 GPL (isolated)	+8	Lockshin et al. 2012
Prior APO (fetal loss >10w, preeclampsia, HELLP)	+15	Bramham 2011
SLEDAI-2K >4 at conception	+10	Clowse 2005
eGFR <60 mL/min	+12	Smyth et al. 2010
Proteinuria >0.5 g/24h	+10	Moroni et al. 2016
Hypertension (pre-existing)	+8	Ostensen et al. 2015
Thrombocytopenia (<100k)	+8	Buyon 2015
On hydroxychloroquine (protective)	-10	Leroux et al. 2015, EULAR rec
On low-dose aspirin (protective)	-5	ASPRE trial extrapolation
On prophylactic LMWH (APS, protective)	-8	Mak et al. 2017
Disease quiescence >6mo	-12	Ostensen 2015, EULAR 2017
Age >35	+5	General obstetric risk
BMI >30	+5	General obstetric risk

Score Interpretation

$$S = \sum_{i} w_i \cdot x_i, \quad x_i \in {0,1}$$

Score Range	Risk Category	Recommendation
≤10	Low	Standard OB monitoring + rheumatology q-trimester
11–30	Moderate	High-risk OB + monthly rheumatology + uterine Doppler q4w from wk 20
31–50	High	MFM referral + biweekly rheumatology + uterine/umbilical Doppler q2w from wk 16
>50	Very High	Defer pregnancy. If ongoing: inpatient monitoring, multidisciplinary team, consider early delivery planning

Monte Carlo Uncertainty Estimation

The tool runs 10,000 simulations with ±20% perturbation on weights (uniform) to generate 95% CI for the score, capturing epistemic uncertainty in weight calibration.

Dependencies

pip install numpy

Usage

python3 pregna_risk.py

References

1. Buyon JP et al. Predictors of Pregnancy Outcomes in Patients With Lupus (PROMISSE). Ann Intern Med. 2015;163(3):153-163.
2. Bramham K et al. Pregnancy outcome in women with chronic kidney disease. J Am Soc Nephrol. 2011;22(11):2011-22.
3. Pengo V et al. Update of the guidelines for lupus anticoagulant detection. J Thromb Haemost. 2009;7:1737-40.
4. Clowse MEB et al. The impact of increased lupus activity on obstetric outcomes. Arthritis Rheum. 2005;52:514-21.
5. Leroux M et al. Hydroxychloroquine and pregnancy outcomes. Autoimmun Rev. 2015;14(11):1013-20.
6. Tektonidou MG et al. EULAR recommendations for the management of APS in adults. Ann Rheum Dis. 2019;78:1296-1304.
7. Smyth A et al. A systematic review and meta-analysis of pregnancy outcomes in CKD. Clin J Am Soc Nephrol. 2010;5:2060-8.

Affiliated With

RheumaAI | Frutero Club | DeSci