nf-risk-stratification provides a lightweight Python API for reproducible
clinical risk stratification in necrotizing fasciitis.
It mirrors the repository's R package workflow with:
- clinical descriptive summaries
- approximate one-sample partial tests
- Fisher, Tippett, and Liptak NPC-style p-value combinations
- Bonferroni correction
- bootstrap confidence intervals
- patient severity ranking
- a complete pipeline runner
Install from GitHub until the first PyPI release is published:
python -m pip install "git+https://github.com/saitejabandaru-in/nf-risk-stratification.git"PyPI and GitHub release pages will be linked after the first public release is published.
from nf_risk_stratification import (
bootstrap_ci,
descriptive_stats,
npc_analysis,
rank_patients,
read_nf_data,
run_nf_pipeline,
)
data = read_nf_data("data/nf_clinical_data.csv")
print(descriptive_stats(data))
print(npc_analysis(data))
print(bootstrap_ci(data))
print(rank_patients(data)[:10])
results = run_nf_pipeline("data/nf_clinical_data.csv")Required CSV columns:
| Column | Meaning |
|---|---|
HBA1C |
Glycemic control |
ALBUMINA |
Nutritional status |
Optional columns:
| Column | Meaning |
|---|---|
MORTO |
Mortality outcome |
AMPUTAZIONE |
Major amputation outcome |
PATIENT_ID |
Patient identifier |
The real clinical dataset is not included for privacy and ethics reasons.
PyPI API tokens and credentials are not required at runtime and must never be committed to this repository. Use a local environment variable or trusted keyring only when uploading release artifacts.
Permutation-Based Analysis of Clinical Variables in Necrotizing Fasciitis Using NPC and Bootstrap. Piscopo, G., Bandaru, S. T., Giacalone, M., & Longobardi, M. (2025). Mathematics, 13(17), 2869. https://doi.org/10.3390/math13172869