Clinical Reasoning Education

Patient On Warfarin For Mechanical Heart Valve — Needs Emergency Extraction, INR 3.8

Clinical reasoning simulation for healthcare students and educators

General Medicine Critical Dentistry

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 patient on warfarin for mechanical heart valve / needs emergency extraction / inr 3.8 in a general medicine context. Learners work through a structured 10-phase simulation covering initial differential, history-taking, physical examination, labs and imaging, and management planning.

"A patient with a mechanical mitral valve replacement requires emergency extraction of an abscessed tooth. INR is 3.8. His cardiologist cannot be reached. He has trismus and cannot tolerate the abscess pain. What is your decision about the extraction — and what does the INR level and valve type tell you about the risk of holding anticoagulation even briefly?"

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 Dentistry students and practicing clinicians seeking to sharpen diagnostic thinking in general medicine.

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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.