This past week, I had the privilege of leading an in-depth clinical debrief with my anesthesiology nursing residents at the University of North Florida on one of the most challenging aspects of anesthesia: the management of cardiac patients presenting for non-cardiac surgery. What started as a case discussion quickly evolved into an energetic, case-based workshop that highlighted the integration of clinical vigilance, physiologic reasoning, and the power of pattern recognition.
The Teaching Moment
We explored the anesthesia plan for a “classic” 74-year-old ASA IV patient with a history of aorto-femoral bypass, carotid dissection, remote stroke history, and other significant cardiovascular co-morbidities. The patient was scheduled for what would otherwise be considered “routine” GI endoscopy. On the surface, it’s “ just” a MAC case. But what does that even mean when the patient has tenuous cerebral perfusion, critical bilateral carotid pathology, and relies on exquisitely narrow blood pressure tolerances?
We dug into:
- The misnomer of “MAC” anesthesia in GI endoscopy and the compliance risks of improper billing documentation.
- Hemodynamic finesse: titrating propofol in fractional doses, matching pharmacodynamics to the stimulation of EGD vs. colonoscopy.
- The role of real-time drug choice (nicardipine, esmolol, epinephrine) to maintain tight control over perfusion pressure and minimize stroke risk.
- How data from Advanced Goal Directed Fluid Therapy waveform monitoring and a thorough EHR dive can—and should—shape anesthetic planning and preoperative care.
Teaching Future Anesthesia Professionals to Think Like Systems Engineers
We didn’t stop at the HOW. We asked the WHY, repeatedly.
One student shared a brilliant case where rising ST segments triggered a differential: is this a STEMI or the physiologic strain of laparoscopic insufflation in a heart we barely know? Rather than reaching for protocol, we taught them to simulate forward: adjust preload, manipulate inotropy, optimize FiO₂ and PEEP, reassess lead placement, and watch for supply/demand mismatch in real time.
EKG Interpretation as an Active Monitoring Tool
We reviewed a 12-lead EKG together live, following Dubin’s five-step method. But more importantly, we used it as a launch point for how to adjust monitoring strategy—repositioning V leads for anterior coverage, selecting lead II/AVF for inferior wall ischemia detection, and applying Q wave analysis to assess prior infarction patterns.
From Algorithms to Action
We discussed how and when to apply cardiac clearance guidelines and why “cancel the case” isn’t always the answer. Risk management often means proceeding—but doing so with a thoughtful, scaffolded plan. This is anesthesia as both science and strategy.
Why This Matters
This is the kind of training that moves us from protocol-based care to purpose-driven care. And as someone who bridges both clinical anesthesia and data science, I find moments like these—where physiology, pharmacology, and human decision-making intersect—are where transformation happens.
–To my colleagues in anesthesia education and perioperative leadership: let’s give our learners access to the real-world challenges, messy cases, and imperfect data. Let’s train them not just to manage what’s in front of them, but to anticipate, model, and adapt.
Because the future of safe, smart anesthesia care won’t be driven by checklists alone. It will be led by clinicians who know how to think.