Skip to content
cccskills
FreePublished on GitHub

diagnostic-study-quality-assessment-quadas

Assess bias and applicability in clinical diagnostic accuracy studies with QUADAS-2. Review patient selection, the index test, reference standard, and study flow, supporting each judgment with a paper quotation and marking missing information as unclear.

OriginalShow the original 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").

Run score Not tested

See how to install

Good for

  • Assessing a diagnostic accuracy paper with QUADAS-2
  • Reviewing risk of bias across the four study domains
  • Checking whether a study applies to a target setting
  • Extracting quotations to support assessment judgments

Files included (7)

  • SKILL.md5.6 KB
  • assets/example_asset.txt889 B
  • diagnostic-study-quality-assessment-quadas-2_audit_result_v1.json12.6 KB
  • references/api_reference.md1.0 KB
  • references/quadas_2_criteria.md2.0 KB
  • scripts/pdf_extractor.py4.0 KB
  • scripts/quadas_assessment.py454 B

SKILL.md (original)

Review the instructions the agent will receive before you install.

Source: 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

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

Reviews

No reviews yet. Tell others what you thought.

Comments

No login needed. Share how it worked for you, ask a question, or note where it did not run.

No comments yet. Be the first to write one.

Comments are published right away. Do not include personal information such as email addresses or phone numbers. Up to 2 URLs.

0 / 1,000 characters

This form is protected by reCAPTCHA, and the Google Privacy Policy and Terms of Service apply.

More skills from this repository

Condense an academic paper into a structured abstract of up to 250 words, organized by background, objective, methods, results, and conclusion. It aims to retain key quantitative findings and supports papers from several research fields; figures and charts are not interpreted.

  • Creating a concise abstract from a research paper
  • Summarizing empirical studies while retaining key statistics
  • Preparing structured summaries across multiple papers
aipoch/medical-research-skills2KUpdated Sep 17, 2026

abstract-trimmer

FreeSummary

Trim English academic abstracts to a target word count while preserving key findings, statistics, and the background-to-conclusion structure. Choose conservative, balanced, or aggressive compression, check word counts, and review the edited text for readability and accuracy.

  • Cutting an abstract to meet a journal word limit
  • Preparing a conference abstract with a strict word count
  • Checking an abstract's word count before submission
aipoch/medical-research-skills2KUpdated Sep 17, 2026

Refines long medical drafts, reports, or literature notes into formal, single-paragraph Chinese and English abstracts in an SCI journal style. It can place both abstracts in a Markdown report while keeping claims grounded in the source text.

  • Condensing a medical study report into bilingual abstracts
  • Preparing unstructured abstracts from literature notes
  • Creating a Markdown report with Chinese and English abstracts
aipoch/medical-research-skills2KUpdated Sep 17, 2026

Creates three to five concise English Highlights for journal submission from manuscript text or supported files. It adapts bullets to the article type, keeps each within 85 characters, and grounds every claim in the supplied source without inventing results.

  • Draft journal Highlights from an abstract or manuscript
  • Summarize a meta-analysis or review for submission
  • Extract key findings from a supported PDF or DOCX
aipoch/medical-research-skills2KUpdated Sep 17, 2026

Design comparative drug safety studies using FAERS, the FDA’s adverse event reporting database, within one defined safety area. The plan compares drugs or classes, lays out workload options and analysis steps, and distinguishes detected signals from conclusions the data cannot support.

  • Comparing drug classes within one adverse event area
  • Planning a FAERS study with active comparators
  • Adding declared subgroup or onset characterization
aipoch/medical-research-skills2KUpdated Sep 17, 2026

Predicts absorption, distribution, metabolism, and excretion properties for small molecules from their structures. Use the results to compare compounds, screen libraries, and review drug-likeness scores in structured outputs. Predictions support prioritization and need experimental validation.

  • Compare predicted ADME profiles for small-molecule candidates
  • Screen a compound library for drug-likeness
  • Rank candidates against target property ranges
aipoch/medical-research-skills2KUpdated Sep 17, 2026

See all skills by aipoch

Report a problem with this skill