diagnostic-study-quality-assessment-quadas-2
$
npx mdskill add aipoch/medical-research-skills/diagnostic-study-quality-assessment-quadas-2Evaluate diagnostic study bias with QUADAS-2 tool.
- Assesses quality and risk of bias in clinical accuracy papers.
- Depends on scripts/pdf_extractor.py for file processing.
- Decides execution based on user request for reproducible validation.
- Delivers structured assessment of applicability concerns.
SKILL.md
.github/skills/diagnostic-study-quality-assessment-quadas-2View on GitHub ↗
---
name: diagnostic-study-quality-assessment-quadas-2
description: 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").
license: MIT
author: aipoch
---
> **Source**: [https://github.com/aipoch/medical-research-skills](https://github.com/aipoch/medical-research-skills)
# 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
```bash
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:
```markdown
### [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:
```bash
# 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](references/quadas_2_criteria.md): Detailed signaling questions and judgment guidelines.
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