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gh-k-dense-ai-claude-scient…/skills/clinical-decision-support/scripts/validate_cds_document.py
2025-11-30 08:30:14 +08:00

336 lines
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Python
Executable File

#!/usr/bin/env python3
"""
Validate Clinical Decision Support Documents for Quality and Completeness
Checks for:
- Evidence citations for all recommendations
- Statistical reporting completeness
- Biomarker nomenclature consistency
- Required sections present
- HIPAA de-identification
- GRADE recommendation format
Dependencies: None (pure Python)
"""
import re
import argparse
from pathlib import Path
from collections import defaultdict
class CDSValidator:
"""Validator for clinical decision support documents."""
def __init__(self, filepath):
self.filepath = filepath
with open(filepath, 'r', encoding='utf-8', errors='ignore') as f:
self.content = f.read()
self.errors = []
self.warnings = []
self.info = []
def validate_all(self):
"""Run all validation checks."""
print(f"Validating: {self.filepath}")
print("="*70)
self.check_required_sections()
self.check_evidence_citations()
self.check_recommendation_grading()
self.check_statistical_reporting()
self.check_hipaa_identifiers()
self.check_biomarker_nomenclature()
return self.generate_report()
def check_required_sections(self):
"""Check if required sections are present."""
# Cohort analysis required sections
cohort_sections = [
'cohort characteristics',
'biomarker',
'outcomes',
'statistical analysis',
'clinical implications',
'references'
]
# Treatment recommendation required sections
rec_sections = [
'evidence',
'recommendation',
'monitoring',
'references'
]
content_lower = self.content.lower()
# Check which document type
is_cohort = 'cohort' in content_lower
is_recommendation = 'recommendation' in content_lower
if is_cohort:
missing = [sec for sec in cohort_sections if sec not in content_lower]
if missing:
self.warnings.append(f"Cohort analysis may be missing sections: {', '.join(missing)}")
else:
self.info.append("All cohort analysis sections present")
if is_recommendation:
missing = [sec for sec in rec_sections if sec not in content_lower]
if missing:
self.errors.append(f"Recommendation document missing required sections: {', '.join(missing)}")
else:
self.info.append("All recommendation sections present")
def check_evidence_citations(self):
"""Check that recommendations have citations."""
# Find recommendation statements
rec_pattern = r'(recommend|should|prefer|suggest|consider)(.*?)(?:\n\n|\Z)'
recommendations = re.findall(rec_pattern, self.content, re.IGNORECASE | re.DOTALL)
# Find citations
citation_patterns = [
r'\[\d+\]', # Numbered citations [1]
r'\(.*?\d{4}\)', # Author year (Smith 2020)
r'et al\.', # Et al citations
r'NCCN|ASCO|ESMO', # Guideline references
]
uncited_recommendations = []
for i, (_, rec_text) in enumerate(recommendations):
has_citation = any(re.search(pattern, rec_text) for pattern in citation_patterns)
if not has_citation:
snippet = rec_text[:60].strip() + '...'
uncited_recommendations.append(snippet)
if uncited_recommendations:
self.warnings.append(f"Found {len(uncited_recommendations)} recommendations without citations")
for rec in uncited_recommendations[:3]: # Show first 3
self.warnings.append(f" - {rec}")
else:
self.info.append(f"All {len(recommendations)} recommendations have citations")
def check_recommendation_grading(self):
"""Check for GRADE-style recommendation strength."""
# Look for GRADE notation (1A, 1B, 2A, 2B, 2C)
grade_pattern = r'GRADE\s*[12][A-C]|Grade\s*[12][A-C]|\(?\s*[12][A-C]\s*\)?'
grades = re.findall(grade_pattern, self.content, re.IGNORECASE)
# Look for strong/conditional language
strong_pattern = r'(strong|we recommend|should)'
conditional_pattern = r'(conditional|weak|we suggest|may consider|could consider)'
strong_count = len(re.findall(strong_pattern, self.content, re.IGNORECASE))
conditional_count = len(re.findall(conditional_pattern, self.content, re.IGNORECASE))
if grades:
self.info.append(f"Found {len(grades)} GRADE-style recommendations")
else:
self.warnings.append("No GRADE-style recommendation grading found (1A, 1B, 2A, etc.)")
if strong_count > 0 or conditional_count > 0:
self.info.append(f"Recommendation language: {strong_count} strong, {conditional_count} conditional")
else:
self.warnings.append("No clear recommendation strength language (strong/conditional) found")
def check_statistical_reporting(self):
"""Check for proper statistical reporting."""
# Check for p-values
p_values = re.findall(r'p\s*[=<>]\s*[\d.]+', self.content, re.IGNORECASE)
# Check for confidence intervals
ci_pattern = r'95%\s*CI|confidence interval'
cis = re.findall(ci_pattern, self.content, re.IGNORECASE)
# Check for hazard ratios
hr_pattern = r'HR\s*[=:]\s*[\d.]+'
hrs = re.findall(hr_pattern, self.content)
# Check for sample sizes
n_pattern = r'n\s*=\s*\d+'
sample_sizes = re.findall(n_pattern, self.content, re.IGNORECASE)
if not p_values:
self.warnings.append("No p-values found - statistical significance not reported")
else:
self.info.append(f"Found {len(p_values)} p-values")
if hrs and not cis:
self.warnings.append("Hazard ratios reported without confidence intervals")
if not sample_sizes:
self.warnings.append("Sample sizes (n=X) not clearly reported")
# Check for common statistical errors
if 'p=0.00' in self.content or 'p = 0.00' in self.content:
self.warnings.append("Found p=0.00 (should report as p<0.001 instead)")
def check_hipaa_identifiers(self):
"""Check for potential HIPAA identifiers."""
# 18 HIPAA identifiers (simplified check for common ones)
identifiers = {
'Names': r'Dr\.\s+[A-Z][a-z]+|Patient:\s*[A-Z][a-z]+',
'Specific dates': r'\d{1,2}/\d{1,2}/\d{4}', # MM/DD/YYYY
'Phone numbers': r'\d{3}[-.]?\d{3}[-.]?\d{4}',
'Email addresses': r'[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}',
'SSN': r'\d{3}-\d{2}-\d{4}',
'MRN': r'MRN\s*:?\s*\d+',
}
found_identifiers = []
for identifier_type, pattern in identifiers.items():
matches = re.findall(pattern, self.content)
if matches:
found_identifiers.append(f"{identifier_type}: {len(matches)} instance(s)")
if found_identifiers:
self.errors.append("Potential HIPAA identifiers detected:")
for identifier in found_identifiers:
self.errors.append(f" - {identifier}")
self.errors.append(" ** Ensure proper de-identification before distribution **")
else:
self.info.append("No obvious HIPAA identifiers detected (basic check only)")
def check_biomarker_nomenclature(self):
"""Check for consistent biomarker nomenclature."""
# Common biomarker naming issues
issues = []
# Check for gene names (should be italicized in LaTeX)
gene_names = ['EGFR', 'ALK', 'ROS1', 'BRAF', 'KRAS', 'HER2', 'TP53', 'BRCA1', 'BRCA2']
for gene in gene_names:
# Check if gene appears but not in italics (\textit{} or \emph{})
if gene in self.content:
if f'\\textit{{{gene}}}' not in self.content and f'\\emph{{{gene}}}' not in self.content:
if '.tex' in self.filepath.suffix:
issues.append(f"{gene} should be italicized in LaTeX (\\textit{{{gene}}})")
# Check for protein vs gene naming
# HER2 (protein) vs ERBB2 (gene) - both valid
# Check for mutation nomenclature (HGVS format)
hgvs_pattern = r'p\.[A-Z]\d+[A-Z]' # e.g., p.L858R
hgvs_mutations = re.findall(hgvs_pattern, self.content)
if hgvs_mutations:
self.info.append(f"Found {len(hgvs_mutations)} HGVS protein nomenclature (e.g., p.L858R)")
# Warn about non-standard mutation format
if 'EGFR mutation' in self.content and 'exon' not in self.content.lower():
self.warnings.append("EGFR mutation mentioned - specify exon/variant (e.g., exon 19 deletion)")
if issues:
self.warnings.extend(issues)
def generate_report(self):
"""Generate validation report."""
print("\n" + "="*70)
print("VALIDATION REPORT")
print("="*70)
if self.errors:
print(f"\n❌ ERRORS ({len(self.errors)}):")
for error in self.errors:
print(f" {error}")
if self.warnings:
print(f"\n⚠️ WARNINGS ({len(self.warnings)}):")
for warning in self.warnings:
print(f" {warning}")
if self.info:
print(f"\n✓ PASSED CHECKS ({len(self.info)}):")
for info in self.info:
print(f" {info}")
# Overall status
print("\n" + "="*70)
if self.errors:
print("STATUS: ❌ VALIDATION FAILED - Address errors before distribution")
return False
elif self.warnings:
print("STATUS: ⚠️ VALIDATION PASSED WITH WARNINGS - Review recommended")
return True
else:
print("STATUS: ✓ VALIDATION PASSED - Document meets quality standards")
return True
def save_report(self, output_file):
"""Save validation report to file."""
with open(output_file, 'w') as f:
f.write("CLINICAL DECISION SUPPORT DOCUMENT VALIDATION REPORT\n")
f.write("="*70 + "\n")
f.write(f"Document: {self.filepath}\n")
f.write(f"Validated: {Path.cwd()}\n\n")
if self.errors:
f.write(f"ERRORS ({len(self.errors)}):\n")
for error in self.errors:
f.write(f" - {error}\n")
f.write("\n")
if self.warnings:
f.write(f"WARNINGS ({len(self.warnings)}):\n")
for warning in self.warnings:
f.write(f" - {warning}\n")
f.write("\n")
if self.info:
f.write(f"PASSED CHECKS ({len(self.info)}):\n")
for info in self.info:
f.write(f" - {info}\n")
print(f"\nValidation report saved to: {output_file}")
def main():
parser = argparse.ArgumentParser(description='Validate clinical decision support documents')
parser.add_argument('input_file', type=str, help='Document to validate (.tex, .md, .txt)')
parser.add_argument('-o', '--output', type=str, default=None,
help='Save validation report to file')
parser.add_argument('--strict', action='store_true',
help='Treat warnings as errors')
args = parser.parse_args()
# Validate
validator = CDSValidator(args.input_file)
passed = validator.validate_all()
# Save report if requested
if args.output:
validator.save_report(args.output)
# Exit code
if args.strict and (validator.errors or validator.warnings):
exit(1)
elif validator.errors:
exit(1)
else:
exit(0)
if __name__ == '__main__':
main()
# Example usage:
# python validate_cds_document.py cohort_analysis.tex
# python validate_cds_document.py treatment_recommendations.tex -o validation_report.txt
# python validate_cds_document.py document.tex --strict # Warnings cause failure