Case Control Study Quality Assessment Nos

Source: https://github.com/aipoch/medical-research-skills

Clinical Research Bias Assessment (NOS)

This skill evaluates the quality of case-control studies based on the Newcastle-Ottawa Scale (NOS).

When to Use

• Use this skill when the request matches its documented task boundary.
• Use it when the user can provide the required inputs and expects a structured deliverable.
• Prefer this skill for repeatable, checklist-driven execution rather than open-ended brainstorming.

Key Features

• Scope-focused workflow aligned to: Clinical Research Bias Assessment - Case-Control Study (NOS) v2.3.0. Use when you need to assess the bias of a case-control study using the Newcastle-Ottawa Scale (NOS) criteria, or when evaluating the quality of a medical paper.
• Packaged executable path(s): scripts/extract_pdf.py plus 1 additional script(s).
• Reference material available in references/ for task-specific guidance.
• 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

See ## Usage above for related details.

cd "20260316/scientific-skills/Data Analytics/Case-control-study-quality-assessment-nos"
python -m py_compile scripts/extract_pdf.py
python scripts/extract_pdf.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/extract_pdf.py with the validated inputs.
4. Review the generated output and return the final artifact with any assumptions called out.

Implementation 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/extract_pdf.py with additional helper scripts under scripts/.
• Reference guidance: references/ contains supporting rules, prompts, or checklists.
• 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.

Usage

1. Extract Metadata: Identify the study's first author and publication year.
2. Evaluate Criteria: Assess the study against the three NOS domains:
   • Selection: Case definition, representativeness, control selection, and definition.
   • Comparability: Comparability of cases and controls (age, other factors).
   • Exposure: Ascertainment of exposure, method of ascertainment, and non-response rate.
3. Synthesize Results: Aggregate the evaluations into a structured JSON format.
4. Format Output: Use scripts/format_nos_table.py to generate the final summary table.

Detailed Workflow

Step 1: Selection Evaluation

Evaluate the "Selection" domain using the criteria detailed in references/nos_criteria_prompts.md. Ensure reasons are provided in Chinese and quote the original text.

Step 2: Comparability Evaluation

Evaluate the "Comparability" domain. Note: If the odds ratio is adjusted for confounders, groups are considered comparable.

Step 3: Exposure Evaluation

Evaluate the "Exposure" domain.

Step 4: Generate Summary Table

Run the formatting script with the aggregated JSON data:

python scripts/format_nos_table.py '<json_string>'

Input Validation

This skill accepts requests that match the documented purpose of case-control-study-quality-assessment-nos and include enough context to complete the workflow safely.

Do not continue the workflow when the request is out of scope, missing a critical input, or would require unsupported assumptions. Instead respond:

case-control-study-quality-assessment-nos only handles its documented workflow. Please provide the missing required inputs or switch to a more suitable skill.

References

• NOS Criteria Prompts

Helper Scripts