Good afternoon. So yeah, I'm Jacqueline Thomp-Garson. I'm the EMIM Program Director as well. And so in preparing this talk, I kind of had to ask myself, what are the things that make emergency physicians really phenomenal critical care physicians? And what do we do really, really well that we bring upstairs that they can't, that we just do really well? Let me put it that way. So I'll start with, I have no financial relationships to disclose, but when I really got to thinking about that, some of the things that we do that were phenomenal is we're amazing resuscitationists. And so this study to me looked at the comparative effectiveness of amiodarone and lidocaine for the treatment of in-hospital cardiac arrest. The authors of this study went back and they said, well, we have studies that tell us that in out-of-hospital cardiac arrest, lidocaine and amiodarone are essentially equivalent. That's why we changed the 2018 guidelines to include both. But what if we looked at in-hospital cardiac arrest? Because the patients who are having refractory VTIB or VT or VFIB in hospital have a different profile. They're more likely to get to definitive care sooner. They're more likely to have high quality CPR and the equipment necessary to take care of them. So maybe in this population, it looks a little bit different. The primary, this was a retrospective cohort study that looked at data from the Get With The Guidelines registry and examined patients with in-hospital refractory VT, VFIB over a 14-year period from January of 2000 to December of 2014. Primary outcome was return of spontaneous circulation, 24-hour survival, survival to hospital discharge, and neurologic recovery, which I'll get into in a second. They looked at almost 40,000 patients and whittled that down to over 14,000 who had either received amiodarone or lidocaine during refractory VT and VF. They eliminated patients who did not receive either drug, who had missing data, or those who had an ambulatory arrest because they assumed that response time in an ambulatory setting would be more similar to an out-of-hospital cardiac arrest than in-hospital. They then broke these arrests down into further details based on age, sex, location during arrest, time and day of arrest, was it a weekend, did they have pre-existing conditions, including pre-existing neurostatus, monitoring, what type of monitoring was employed during the arrest, and the time to first defibrillation and drug choice. And this is a busy slide, and I left this like this for you deliberately. I hate busy slides. But there's a lot of things that they looked at when they started to pull out the different patients. Most notably, in the top-left corner there, you can see that nearly two-thirds of the patients over the 14,000 patients, remember, that they looked at in this retrospective review had gotten Amio as compared to lidocaine. But patients who received lidocaine were more likely to be white, less likely to be male, and had lower rates of pre-existing conditions. Lidocaine was also more likely to be used in areas like the emergency department or any environment that was not the ICU. The authors then looked at both adjusted and unadjusted rates of outcomes comparing Amiodarone and lidocaine. These are the unadjusted rates. They showed no change in ROSC, but a higher likelihood of 24-hour survival, survival to hospital discharge, and a favorable neurologic outcome. So their definition of a favorable neurological outcome, a good neurological outcome meant that they were conscious, alert, able to work, and didn't need any help with their activities, could work in any environment. A moderate cerebral disability were patients who were conscious, they were able to do their independent ADLs, but they needed to work in a sheltered environment in order to achieve their goals. The adjusted rates, after they looked at the odds of higher and lower risks of amio versus lidocaine, so they found statistically significant correlates of lower odds of all four outcomes included age, time to defibrillation, several pre-existing conditions like hypo or hyperperfusion, metastatic or hematologic cancer, renal insufficiency or dialysis, sepsis, or continuous vasopressor use. They saw statistically significant correlates of higher odds of all four outcomes included white race and MI on that admission, cardiac illness category when they were admitted, ECG monitoring, and then the year that they were admitted, because remember, this was over a 14-year period, so the year they admitted actually affected their outcomes. Once they adjusted for all of these odds, outcomes statistically favored lidocaine in all four outcome categories. They postulate that the improvement in neuro outcome could be due either to earlier time to ROSC when compared to amio, but it might be supported by current animal research that describes a neuroprotective effect of lidocaine, and this is thought to be related to lidocaine's chemical and pharmacologic properties that potentially protects the brain from hypoxia and ischemia during an arrest. So why is this important? Prior to 2000, many of you remember, lidocaine was our primary drug of choice. In 2018, in 2000, amio became the number one choice. In 2018, lidocaine was introduced again as a either-or kind of scenario on the ACLS guidelines. This study actually suggests that lidocaine might be the drug of choice. It might be more beneficial in certain populations, and it might be something we should reach for more often. It does, however, have limitations. First, they made a number of adjustments in order to show statistically significant changes, but it's important to note that in the unadjusted outcomes, they still had a higher statistical improvement in outcomes related to 24 hours and hospital discharge. Second, this is a retrospective review, which allowed it to be a large multi-center evaluation, but it's still not a gold standard. And because they used the Get With The Guidelines registry, we don't actually have details on the patients. So we don't know why the physicians chose lidocaine in those scenarios versus amiodarone. Maybe they were already on lidocaine. We don't know if amio or lidocaine was only available in that scenario. And we don't actually know much about the post-arrest care in the hospitals that were involved. So maybe the hospitals that had better neurologic outcomes have better post-arrest care, or maybe the hospitals that had worse outcomes are sooner to involve palliative and hospice and withdraw care. So there are some questions here, but it begs the question of, maybe we should be reaching for lidocaine a bit more often. The next thing I started to think about was, what else are we really good at? So emergency physicians tend to be innovation seekers. Dr. Tett talked to you about the EDICUs and all the care that we're trying to bring downstairs to solve the boarding problem, because we are trying to figure out how to solve a boarding problem. So this is actually a review article talking about artificial intelligence management in the ICU. It was published in Critical Care Medicine in March of 2022, and the authors looked at the use of machine learning and artificial intelligence and the ability to predict infections in the ICU with a focus on how that will affect our infection control processes. The best and most relevant application could be in the prediction of common ICU complications, such as CLABSIs, VAPs, and CAUTIs. However, they note that there are additional applications to things like imaging interpretation. They viewed all of this through the lens of antimicrobial stewardship and how we currently practice in our goals and how can we be supported. So in this slide, you can see that typically our antimicrobial stewardship goals at the start of therapy are to get the correct diagnosis, start antibiotics early, and make sure that we have the right dose. AI and machine learning could support you by potentially predicting those infections sooner, telling us whether or not those are infections or is it just an inflammatory response. It helps with patient surveillance. Are they getting better? Can we stop them sooner? Because artificial intelligence and machine learning can interpret the things on the computer that might even have minor differences that we might throw out as a lab error and can follow that along with the vital signs to give us an earlier signal. And that plugs into this slide. So what the authors of this review article postulated is that what we currently use, the current process is there in red on that bottom yellow part of this slide. That's where we pick up infection, current practice. What they're saying is with artificial intelligence and machine learning, we can do things like forecasting, which is in blue, and now casting, which is in yellow, which actually gives us a pretty significant head start on treating infections before they become so bad that we're throwing all the antibiotics at them. It can decrease potential hospital lakes of stay, reduce the amount of invasive monitoring that we have, and reduce exposure to unnecessary antibiotics. The data is compelling. Machines are being used currently to interpret culture growth results, to collate blood samples and vital signs, and to use these early and potentially subtle findings to predict infection earlier. Additionally, a common diagnostic program of practicing physicians is whether this is actually an infection or an inflammatory response. And a machine learning or artificial intelligence can help us tell the difference, preventing overprescribing antibiotics. Currently, AI and machine learning systems remain in the prototype or design phase, and they are in place in isolated systems, but they've not been deployed broadly or subjected to clinical trials. But before we could even begin to rely on machine learning, we have to understand that machine learning will not be 100% reliable, and that machine learning still relies on humans to input data and to help adjust the data as the medicine landscape change. We all know that medicine is an exceedingly fast, extremely quick-to-change field, and machines rely on us to input the algorithms to make their decisions. If we're not willing to step in and change those algorithms or adjust things as the landscape of medicine changes, then the machines become old and obsolete very, very quickly. And that leads us to actually some ethical concerns. What happens to the physician who makes a decision based on the AI or machine learning that's not supported in current literature? What if the machine suggests a drug that's not FDA-approved, and you withhold it, and the patient dies, and the family finds out that the machine suggested this, and they might have survived? Or what if you prescribe that drug, and there's an unknown side effect because it's not been studied, and the patient dies from the side effect, but you prescribed it based on an outdated or old algorithm? In general, there's a lot more research required to advance this field, but the potential and the prospects are really interesting. And finally, what would be an emergency critical care lecture without a little bit of ultrasound? So this last lecture comes to us from New Mexico. It's looking at TEE performed by intensivists and emergency physicians in a single center. The study points out that many patients in the ICU either require or could benefit from an echo to assist in management decisions regarding their clinical illness, but because of their body habitus, surgical interventions, or their severity, illness, and inability to reposition the patients, we can't get good images, TTE images. As a result, we order TEEs, and then in many places have to rely on our surgical anesthesia or cardiology colleagues to do the TEE for us. So if we can do these ourselves, perhaps we can make management changes sooner. The author supported the presence of this study by recalling pilot studies that showed TEEs during critical illness changed management decisions 36 to 80% of the time with no reported complications. I think it's important when you talk about TEEs and physicians who are not necessarily echo trained to talk about the different levels that this specific institution used in the study. And so they had three different types of TEE certification. Resuscitative TEE credentialed physicians to perform it during cardiac arrest and peri-arrest situations only. Basic critical care TEE was their next level up. They can perform TEE on any intubated patient with hemodynamic instability who was receiving ECMO or if they needed it for procedural assistance. Advanced critical care TEE allowed for assessment of endocarditis, intracardiac thrombics, complex valve assessments, more in-depth assessments, but this actually required either board certification in advanced critical echocardiography or a sign off from other physicians who were certified. Over the five year study, the number of TEEs performed and the number of physicians credentialed in TEEs increased from 31 and three respectively to 116 TEEs per year and 13 credentialed physicians. They actually had a drop between 2019 and 2020 predicted to be due to COVID. The majority of TEEs performed were done by EM critical care physicians followed by non-critical care medicine EM physicians. And the top indication for TEE was hemodynamic instability, cardiac arrest and ECMO cannulation. The majority of these were categorized as emergent. What's most impressive about this study is that they deemed 79% of these TEEs to have changed management. They said that changing management meant things like adding vasopressors or inotropes, reducing vasopressors or inotropes and administration of volume. The most impactful, however, was probably things like adding ECMO, deciding whether or not to do ECMO and deciding whether or not to consult cardiology consultants for more invasive cardiac care. Additionally, there was a large number of TEEs that were performed on off hours and into the weekend, leading the authors to conclude that the physicians who perform these TEEs really appreciated and relied on the value of them. Notable limitations is there was no recorded data on whether a TTE was performed prior to the TEE. So was the TEE necessary or was this just the easy thing for them to do because they'd been trained in it? They also used patients in this study who they were using TEEs to decide to terminate resuscitative efforts and refer to organ donation services, which meant that they had actually a really high mortality. And when they mentioned that the 79% of them changed management decisions, they don't actually tell us what that meant with the survivability. So we don't know if the management decision that they made was terminate resuscitative efforts, refer to organ donation or add vasopressor and the patient lived. We're not actually sure how much of an effect these management changes had on the patients. Regardless, the high degree of use in a single center leads you to question if this is the next wave of ultrasound in critical care and emergency medicine. Thank you.

emergency physicians

lidocaine

amiodarone

artificial intelligence

transesophageal echocardiography