clinical-research-pitfalls

To mitigate immortal time bias in ICU observational studies, define an explicit time-zero for cohort entry. This prevents misclassifying patients as exposed before treatment occurs, ensuring valid survival estimates in MIMIC-derived datasets.

Information leakage in EHR-based study design occurs when future data improperly informs predictor variables. Avoid it by strictly bounding feature extraction to data available strictly before the defined time-zero, preventing inflated predictive performance.

Handle confounding and selection bias during ICU data extraction by applying a checklist-driven study design. Transparently document all inclusion exclusions, patient censoring rules, and potential confounders to ensure robust observational findings.

Yes, you can apply this framework for peer-review workflows on MIMIC-derived datasets. It provides guided bias assessment, enforces proper censoring handling, and ensures transparent reporting of exclusions and confounders.