Episode Details
Back to Episodes
The Bipolar Medication Mistake That Keeps Patients Relapsing
Description
There are two kinds of clinicians—the ones who follow algorithms, and the ones who understand the “why.”
Patients know the difference. Know the WHY!
Join our clinical library today on PATREON!
👉 https://www.patreon.com/PearlsandPrep
The Polarity Index may be one of the most underutilized concepts in bipolar disorder—and once you understand it, choosing maintenance medications becomes dramatically easier. In this episode, I break down the Polarity Index into plain language and show you how to stop memorizing drug lists and start thinking like an expert clinician.
You'll learn why acute treatment and maintenance treatment are not the same decision, how to identify a patient's predominant pole (mania vs. depression), and how that single insight can transform your medication selection. Through realistic mock patient cases, we'll walk through when to choose lamotrigine, lithium, quetiapine, aripiprazole, lurasidone, cariprazine, and Symbyax, while tying every decision back to receptor pharmacology and long-term relapse prevention.
In this episode you'll learn:
- What the Polarity Index actually measures
- The difference between acute stabilization and maintenance treatment
- How to identify a patient's predominant pole
- Why treating today's episode isn't always the same as preventing tomorrow's relapse
- When to choose lamotrigine, lithium, quetiapine, aripiprazole, lurasidone or cariprazine.
- The receptor mechanisms that explain why these medications work
- Clinical pearls that can immediately improve your bipolar prescribing
Whether you're a PMHNP student, psychiatry resident, psychiatric nurse practitioner, physician assistant, psychiatrist, or anyone looking to master psychopharmacology, this episode provides a practical framework you'll use every time you treat bipolar disorder.
OG article on polarity index: https://www.sciencedirect.com/science/article/abs/pii/S0924977X11002616?via%3Dihub
This podcast uses the following third-party services for analysis:
Podcorn - https://podcorn.com/privacy