MEDICINE 432C
Introduction to Duke Medical Intensive Care Unit
Katherine A. Young
Description from DukeHub
Course Goals Introduce students to the principles of the diagnosis and care of critical illness. This course is identical to MEDICINE 405C but is the 2-week elective rather than 4-week elective. By the end of the course students should be able to recognize the pathophysiologic processes underlying shock and respiratory failure, should be able to recognize basic principles of mechanical ventilation and have explored death and dying issues as they apply in the ICU. How Goals Are Achieved Students perform patient evaluations and procedures as well as diagnostic and treatment planning under the direct supervision of a junior medical resident, pulmonary fellow, and critical care attending. Educational material is available on the Duke MICU website (sites.duke.edu/micu) but patient-oriented, evidence-based, bedside training is the primary teaching method. Evaluation The attending physician, critical care fellows and residents primarily assess each student's performance. Input from junior medical residents working with each student is also obtained, as is the input of the course director. For questions or to obtain a permission number to enroll, please contact Dr. Young via email, (contact listed in DukeHub). Requisite: Students that take this course are not eligible to enroll in MEDICINE 405C. This course does not satisfy the Acute Care Course requirement. The course will be graded 'Credit/No Credit'. Permission of the instructor is required for enrollment. Course cannot be dropped online. In order to drop the course, student must submit an electronic Drop request form. Course Credit: 2; Maximum Enrollment: 2 per section. Katie Young, MD
Skills
AI-resilient: 3 of 5
- Yes: Physical, lab or field work · clinical rotation
- Yes: Live work with people · "patient"
- Yes: Judgment someone is accountable for · "diagnosis"
- No: A craft you practice with your hands or body
- No: Small, in-person format
The checks lean on Microsoft Research, Working with AI (2025), which found generative AI applies least to physical work and hands-on work with people. A signal, not a promise. How the score works
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