Designing a case-control study is full of hidden traps.
Choose the wrong matching variables and you create overmatching.
github.com/aipoch/medical-re…
Leave the exposure window vague, and your results become unreproducible. Miss key biases and reviewers will tear the paper apart.
Most researchers either rely on generic templates or spend days figuring out the methodology — often realizing the flaws too late.
AIPOCH’s Case-Control Study Planner changes this.
Describe your research question in plain language, and the agent delivers a complete, methodologically sound study blueprint in seconds. It automatically:
✅ Evaluates whether case-control is the right design (and flags when a retrospective cohort would be stronger)
✅ Recommends the optimal matching strategy while explicitly warning against variables that cause overmatching (e.g. ASA class, BMI, COPD)
✅ Builds a structured 10-item Bias-Control Matrix with specific design responses for each bias type
Demo example:
For a study on postoperative pulmonary complications after major abdominal surgery, it produced a full 12-section Markdown blueprint — including case/control definitions, source population, matching plan, exposure measurement windows, bias matrix, and primary analysis strategy — all ready for protocol development.
This isn’t a generic checklist. It’s a tailored, auditable framework that helps researchers avoid the most common methodological mistakes before data collection even begins.
For anyone doing observational research in surgery, perioperative medicine, or clinical epidemiology, this turns a high-risk design phase into a fast, transparent, and defensible process.
#CaseControlStudy #StudyDesign #ClinicalEpidemiology #ResearchMethods #AIPOCH