Clinical Reasoning Education

Gerald Park — Urosepsis ICU Day 3, Off Vasopressors, Now Agitated, Pulling at Lines

Clinical reasoning simulation for healthcare students and educators

Infectious Disease Urgent Nursing

Practice This Case

Work through the full clinical encounter with AI patient and attending. Free, no signup required.

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About This Case

This clinical reasoning case presents a patient with gerald park / urosepsis icu day 3 / off vasopressors / now agitated / pulling at lines in a infectious disease context. Learners work through a structured 10-phase simulation covering initial differential, history-taking, physical examination, labs and imaging, and management planning.

"Gerald was calm this morning. You return after lunch and he is agitated, trying to climb out of bed, and does not recognize you. CAM-ICU is positive. His temperature is 38.4 and BP has dropped from 118/72 to 96/60 since your last check. You need to escalate immediately. Build your complete SBAR — and identify whether this is delirium, sepsis recurrence, or both."

How the Simulation Works

  1. Read the patient presentation and form your initial differential diagnosis
  2. Interview the AI patient to gather history and explore your hypotheses
  3. Perform a focused physical examination based on your differential
  4. Order appropriate labs and imaging, then interpret the results
  5. Revise your diagnosis and develop a management plan
  6. Receive personalized teaching feedback from your AI attending, Dr. Patel

What You'll Learn

This case builds skills in systematic clinical reasoning, hypothesis-driven history-taking, appropriate test ordering, and evidence-based management. It is designed for Nursing students and practicing clinicians seeking to sharpen diagnostic thinking in infectious disease.

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About ReasonDx

ReasonDx is an AI-powered clinical reasoning education platform developed by Dr. Lauren Fine, MD, FAAAAI, Associate Professor and Assistant Dean of Clinical Skills Education at NSU Dr. Kiran C. Patel College of Allopathic Medicine. The platform features 394 simulation cases across 10 health professions, designed to train the cognitive processes underlying accurate diagnosis.