Clinical Study Bias Assessment (QUADAS-2)

This skill evaluates clinical diagnostic accuracy studies for bias and applicability concerns using the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool.

When to Use

• Use this skill when you need analyzes clinical diagnostic accuracy studies for bias using the quadas-2 tool. use when claude needs to assess the quality, risk of bias, or applicability of diagnostic accuracy studies (e.g., "assess this paper using quadas-2") in a reproducible workflow.
• Use this skill when a data analytics task needs a packaged method instead of ad-hoc freeform output.
• Use this skill when the user expects a concrete deliverable, validation step, or file-based result.
• Use this skill when scripts/pdf_extractor.py is the most direct path to complete the request.
• Use this skill when you need the diagnostic-study-quality-assessment-quadas-2 package behavior rather than a generic answer.

Key Features

• Scope-focused workflow aligned to: Analyzes clinical diagnostic accuracy studies for bias using the QUADAS-2 tool. Use when Claude needs to assess the quality, risk of bias, or applicability of diagnostic accuracy studies (e.g., "Assess this paper using QUADAS-2").
• Packaged executable path(s): scripts/pdf_extractor.py plus 1 additional script(s).
• Reference material available in references/ for task-specific guidance.
• Reusable packaged asset(s), including assets/example_asset.txt.
• Structured execution path designed to keep outputs consistent and reviewable.

Dependencies

• Python: 3.10+. Repository baseline for current packaged skills.
• Third-party packages: not explicitly version-pinned in this skill package. Add pinned versions if this skill needs stricter environment control.

Example Usage

cd "20260316/scientific-skills/Data Analytics/diagnostic-study-quality-assessment-quadas-2"
python -m py_compile scripts/pdf_extractor.py
python scripts/pdf_extractor.py --help

Example run plan:

1. Confirm the user input, output path, and any required config values.
2. Edit the in-file CONFIG block or documented parameters if the script uses fixed settings.
3. Run python scripts/pdf_extractor.py with the validated inputs.
4. Review the generated output and return the final artifact with any assumptions called out.

Implementation Details

See ## Workflow above for related details.

• Execution model: validate the request, choose the packaged workflow, and produce a bounded deliverable.
• Input controls: confirm the source files, scope limits, output format, and acceptance criteria before running any script.
• Primary implementation surface: scripts/pdf_extractor.py with additional helper scripts under scripts/.
• Reference guidance: references/ contains supporting rules, prompts, or checklists.
• Packaged assets: reusable files are available under assets/.
• Parameters to clarify first: input path, output path, scope filters, thresholds, and any domain-specific constraints.
• Output discipline: keep results reproducible, identify assumptions explicitly, and avoid undocumented side effects.

Workflow

To assess a study, follow these steps:

1. Analyze Patient Selection:

   • Assess if the sample was consecutive or random.
   • Check for case-control design (should be avoided).
   • Check for inappropriate exclusions.
   • See references/quadas_2_criteria.md for detailed signaling questions.

2. Analyze Index Test:

   • Assess if the index test results were interpreted without knowledge of the reference standard.
   • Check if the threshold was pre-specified.

3. Analyze Reference Standard:

   • Assess if the reference standard correctly classifies the target condition.
   • Check if reference standard results were interpreted without knowledge of the index test.

4. Analyze Flow and Timing:

   • Assess the interval between index test and reference standard.
   • Check if all patients received the reference standard (and the same one).
   • Check if all patients were included in the analysis.

Output Format

For each domain (Patient Selection, Index Test, Reference Standard, Flow and Timing), you MUST output the findings in the following structure:

### [Domain Name]

**[Signaling Question 1]?**
- Comments: [Explanation in Chinese]
- Quote: [Original text quote]
- Answer: [Yes/No/Unclear]

... (Repeat for all signaling questions)

Quality Rules

1. Language: Explanations (Comments) must be in Chinese.
2. Evidence: Every judgment must be supported by a direct quote from the paper.
3. Strictness: If information is missing, select "Unclear". Do not guess.

PDF Parsing Tool

For processing PDF literature, you can use the provided Python script:

# Install dependencies
pip install PyPDF2

# Extract full text
python scripts/pdf_extractor.py "paper.pdf"

# Extract specific page range
python scripts/pdf_extractor.py "paper.pdf" 5 15

The script will automatically extract the text, which you can then copy and send to me for QUADAS-2 assessment.

References

• QUADAS-2 Criteria: Detailed signaling questions and judgment guidelines.