Anesthesia Updates

Can an AI-powered virtual patient teach anesthesiology residents how to perform a preoperative assessment? In this episode, we discuss a 2026 Anesthesiology study by Barra and colleagues that tested AI-driven avatars as a tool for preanesthesia assessment training. The results suggest that virtual patients may improve learner confidence while dramatically reducing the cost and logistical burden of traditional simulation. Join us for conversation powered by NYSORA's MAIA, featuring insights from study authors Dr. Federico Lorenzo Barra and Dr. Luca Carenzo. Together, we examine the promise, limitations, and future of AI-powered simulation in anesthesiology education, and discuss why the future may not be AI versus educators, but AI working alongside them.
Read more about this topic HERE.
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Disclaimer: Medicine is an ever-changing science. As new research and clinical experience broaden, changes in treatment and drug therapy are required. The authors and publishers have checked with sources believed to be reliable in efforts to provide accurate information within the available or accepted standards of care. However, given the possibility of human error or changes in medical practice, neither the authors nor the publisher, nor any other party involved in the preparation of this platform warrants that the information contained herein is in every aspect accurate or complete, and they disclaim all responsibility for any errors or omissions for the results obtained from the use of the information contained in this work. Readers are advised to confirm the information contained herein with other sources. For example, readers are advised to check the product information of each drug mentioned, and that any information contained on NYSORA's Podcast is accurate.

Every fifth patient you anesthetize has diabetes, and the medications they're on are no longer just a pre-op checkbox. In this podcast, we dissect the latest evidence: why GLP-1 agonists may be safer to continue than to stop, what the SGLT-2 data is really telling us, and the shift toward highly personalized, evidence-based risk assessments..
Read more about this topic HERE.
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Disclaimer: Medicine is an ever-changing science. As new research and clinical experience broaden, changes in treatment and drug therapy are required. The authors and publishers have checked with sources believed to be reliable in efforts to provide accurate information within the available or accepted standards of care. However, given the possibility of human error or changes in medical practice, neither the authors nor the publisher, nor any other party involved in the preparation of this platform warrants that the information contained herein is in every aspect accurate or complete, and they disclaim all responsibility for any errors or omissions for the results obtained from the use of the information contained in this work. Readers are advised to confirm the information contained herein with other sources. For example, readers are advised to check the product information of each drug mentioned, and that any information contained on NYSORA's Podcast is accurate.

In pediatric regional anesthesia, the margin for error is razor-thin, and some of our longest-held assumptions are starting to crack. In this podcast, we dissect the latest controversies: neonatal dosing limits, the adjuvant debate, compartment syndrome fear, and whether awake blocks in children are ready for prime time. 
Read more about this topic HERE.

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Disclaimer: Medicine is an ever-changing science. As new research and clinical experience broaden, changes in treatment and drug therapy are required. The authors and publishers have checked with sources believed to be reliable in efforts to provide accurate information within the available or accepted standards of care. However, given the possibility of human error or changes in medical practice, neither the authors nor the publisher, nor any other party involved in the preparation of this platform warrants that the information contained herein is in every aspect accurate or complete, and they disclaim all responsibility for any errors or omissions for the results obtained from the use of the information contained in this work. Readers are advised to confirm the information contained herein with other sources. For example, readers are advised to check the product information of each drug mentioned, and that any information contained on NYSORA's Podcast is accurate.

In this episode, we unpack a massive 2026 systematic review and network meta-analysis covering nearly 15,000 patients and 166 clinical trials on intrathecal adjuvants used during cesarean delivery. From morphine and dexmedetomidine to fentanyl combinations and off-label spinal agents, we explore which medications truly extend pain relief, reduce opioid use, and improve recovery, without increasing serious side effects. What does the evidence actually support, and where does uncertainty still remain? 
Read more about this study HERE.
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Disclaimer: Medicine is an ever-changing science. As new research and clinical experience broaden, changes in treatment and drug therapy are required. The authors and publishers have checked with sources believed to be reliable in efforts to provide accurate information within the available or accepted standards of care. However, given the possibility of human error or changes in medical practice, neither the authors nor the publisher, nor any other party involved in the preparation of this platform warrants that the information contained herein is in every aspect accurate or complete, and they disclaim all responsibility for any errors or omissions for the results obtained from the use of the information contained in this work. Readers are advised to confirm the information contained herein with other sources. For example, readers are advised to check the product information of each drug mentioned, and that any information contained on NYSORA's Podcast is accurate.

In this episode, we explore a 2026 New England Journal of Medicine article that asks a deceptively simple question: Can AI say "I don't know"? From the Hippocratic oath to the “Pikachu problem”, we examine why calibrated uncertainty is a safety mechanism, not a weakness, and what clinicians should demand from AI tools at the point of care.
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Disclaimer: Medicine is an ever-changing science. As new research and clinical experience broaden, changes in treatment and drug therapy are required. The authors and publishers have checked with sources believed to be reliable in efforts to provide accurate information within the available or accepted standards of care. However, given the possibility of human error or changes in medical practice, neither the authors nor the publisher, nor any other party involved in the preparation of this platform warrants that the information contained herein is in every aspect accurate or complete, and they disclaim all responsibility for any errors or omissions for the results obtained from the use of the information contained in this work. Readers are advised to confirm the information contained herein with other sources. For example, readers are advised to check the product information of each drug mentioned, and that any information contained on NYSORA's Podcast is accurate.