Welcome to the next installment of the Anesthesia Patient Safety podcast hosted by Alli Bechtel. This podcast will be an exciting journey towards improved anesthesia patient safety.
First, we return to our discussion of APSF research grants and highlight another APSF Grant Recipient for 2020, Scott Segal, MD, Professor and Chair of the department of anesthesiology at Wake Forest School of Medicine. His winning project is “Development of Machine Learning Algorithms to Predict Difficult Airway Management.” This is an APSF/Medtronic Research Award. Segal’s project seeks to develop a facial recognition machine learning program to replace bedside tests and physical exam findings for difficult airway prediction. You can find more information here: https://www.apsf.org/article/apsf-awards-2020-grant-recipients/
Next, we talk about an exciting study published in our February 2020 Newsletter, “A Difficult Airway Early Warning System in Patients at Risk for Emergency Intubation: A Pilot Study.” Follow along with us here: https://www.apsf.org/article/a-difficult-airway-early-warning-system-in-patients-at-risk-for-emergency-intubation-a-pilot-study/
Here are some questions that are useful to identify potential difficult airway:
Question 1: Does the patient have limited neck range of motion? (Cervical collar or severe cervical neck disease)
Question 2: Does the patient have limited mouth opening? (Connective tissue disorder or jaw wiring or trauma)
Question 3: Does the patient grossly appear difficult? (Super morbid obesity, distorted facial anatomy, or airway bleeding)
For more information on how to apply for an APSF Grant, check out our website at https://www.apsf.org/grants-and-awards/
Be sure to check out the APSF website at https://www.apsf.org/
Make sure that you subscribe to our newsletter at https://www.apsf.org/subscribe/
Follow us on Twitter @APSForg
Questions or Comments? Email me at [email protected].
Thank you to our corporate supporters: https://www.apsf.org/donate/corporate-and-community-donors/
© 2020, The Anesthesia Patient Safety Foundation
Hello and welcome back to the Anesthesia Patient Safety Podcast. My name is Alli Bechtel and I am your host. Thank you for joining me for another show. When was the last time that you had to start moving down the difficult airway algorithm when you were taking care of a patient in the OR? Being able to predict a difficult airway can be helpful to make sure that you are prepared to safely take care of a patient and provide appropriate airway management. Today on the show, we are going to talk about one of the APSF 2020 Grant Recipients, Scott Segal and his project, “Development of Machine Learning Algorithms to Predict Difficult Airway Management.”
Before we dive into today’s episode, we’d like to recognize Masimo, a major corporate supporter of APSF. Masimo has generously provided unrestricted support as well as research and educational grants to further our vision that “no one shall be harmed by anesthesia care”. Thank you, Masimo – we wouldn’t be able to do all that we do without you!”
If you would like to follow along on the APSF website, we are headed back to the February 2020 Newsletter. You can find it by clicking on the Newsletter heading, 4th one down is the Newsletter archives and then you can click on February 2020. On the left, you will see the article, APSF Awards 2020 Grant Recipients by Steven Howard, MD. Today, we will talk about another APSF Grant Recipient for 2020, Scott Segal, MD, Professor and Chair of the department of anesthesiology at Wake Forest School of Medicine. His winning project is “Development of Machine Learning Algorithms to Predict Difficult Airway Management.” This is an APSF/Medtronic Research Award. Segal’s project seeks to develop a facial recognition machine learning program to replace bedside tests and physical exam findings for difficult airway prediction. The research team aims to create a convolutional neural network based facial feature extractor with information related to potential difficult airways. The next step is to combine the feature extractor with patient demographics and bedside airway data to develop an algorithm that is capable of classifying faces as easy or difficult to intubate and this is based on prospective observations during actual inductions of general anesthesia and intubation. This promises to be exciting research to help improve patient safety during intubation.
This is such an interesting topic and difficult airway management is such an important area for patient safety during anesthesia care. So, let’s keep talking about it. If you stay in the February 2020 Newsletter, we are going to talk about the article entitled, “A Difficult Airway Early Warning System in Patients at Risk for Emergency Intubation: A Pilot Study” written by Estime and colleagues. To summarize, this article reports on a pilot study on difficult airway management out of the operating room in an emergency. This event is associated with a high morbidity and mortality. The authors created an early warning system to help alert the anesthesia teams about a potential difficult airway. The early warning system included an airway assessment by the rapid response nurse team since this team is often the first to be called to the bedside. The pilot study spanned 2 months during which the rapid response nurse team conducted initial airway assessments and identified 21 patients with known or suspected difficult airways. Of the 21 patients, 62% required an emergency intubation and 92% of the intubated patients who were identified as having a known or suspected difficult airway were reported to be a difficult airway. Thus, an effective and reliable early warning system for rapid response teams represents an opportunity for improved patient safety during emergency intubation.
An emergent intubation out of the OR is often a challenging situation for a variety of reasons: Unstable patients who may be difficult to position and may be at high risk for aspiration as well as with complicated medical histories with decreased availability of airway equipment and assistance. The plot thickens tremendously when you encounter an unanticipated difficult airway in these situations since there is less time to plan and get airway equipment to the offsite location. The authors report from the literature that we are more likely to see desaturations, failed intubation attempts and difficult bag mask ventilation during difficult airway management cases.
How can we make this perilous situation a little safer? Well, advanced knowledge of a suspected or known difficult intubation may help to decrease the risk for an emergency intubation since the team can take action earlier and have multi-disciplinary assistance and the necessary equipment available and on hand. One of the goals of the early warning system is to decrease the time pressure in an emergent intubation situation, but it is not cost effective or practical to perform an airway assessment for every patient in the hospital or ICU since only a fraction of all of these patients will require an emergency intubation. This pilot study required coordination between the anesthesia department and the rapid response nursing teams to include airway assessment as part of the initial rapid response evaluation. This assessment included identification of known difficult airways based on medical history, alert bracelets, and electronic chart notifications. In addition, the rapid response teams received training on a brief airway exam including the LEMON score which stands for Look, Evaluate, Mallampati Score, Obstruction, and Neck Mobility and this exam could be performed quickly at the time of the rapid response evaluation to help identify any patients with suspected difficult airways.
Here are some questions that are useful to identify potential difficult airway patients and don’t worry because I will include these in the show notes as well.
Question 1: Does the patient have limited neck range of motion? Perhaps from a cervical collar or severe cervical neck disease.
Question 2: Does the patient have limited mouth opening? Some examples may include connective tissue disorder or jaw wiring.
Question 3: Does the patient grossly appear difficult? Perhaps from super morbid obesity, distorted facial anatomy, or airway bleeding.
After patients were identified as having a known or suspected difficult airway, they were placed on a difficult airway list in the electronic medical record. These patients were followed for 2 months during the study and their hospital course. The researchers evaluated the incidence of emergency intubation and if the patient was in fact a difficult intubation with a post-intubation assessment. The definition for difficult airway included greater than 2 attempts at direct laryngoscopy by a senior resident, which included a PGY-3 or above, or an attending with or without advanced airway equipment or the use of additional airway equipment including a video laryngoscope or a fiberoptic bronchoscope. The authors noted that for their study they included senior residents into the definition of a difficult airway since residents are often the first responders to an emergent intubation on the floor and difficulties with early intubation attempts may lead to increased patient morbidity. The goal was to come up with objective criteria, a cut-off for resident seniority or attending physician or the use of adjunctive airway equipment, to define a difficult airway since this description is often subjective.
And now the moment you have been waiting for…the results of the study! Over the 2 months of the pilot period, 21 patients were placed on the difficult airway list for either a known or suspected difficult airway. 13 of these 21 patients needed an emergency intubation during their hospital course in the 2 month study period and 12 of these 13 patients did in fact have difficult airways. For intubation, 7 of the 12 were intubated with a video laryngoscope and 5 of the 12 patients required fiberoptic bronchoscopy. All of the patients were able to be intubated successfully and 1 patient death occurred during the difficult intubation event in the setting of a pulmonary embolus in a patient who sustained a cardiac arrest and was receiving CPR when the emergency airway team arrived.
The research team reported that an early warning system is possible and effective in identifying a significant number of difficult airway patients who are more likely to need an emergency intubation. There may be a role for this system to significantly improve patient safety for hospitalized patients who end of needing an emergent intubation. We do need to keep in mind that this is a small pilot study over a short time frame. In addition, we will remember that the definition for a difficult airway is variable and there are many clinicians who use video laryngoscope for the first attempt in an emergent intubation to decrease the risk of a failed intubation attempt. Further studies are needed to assess whether this early warning system changes the intubation attempt either in personnel or equipment and if there are any quantitive improvements in patient safety outcomes as a result of this intervention.
Thank you so much for joining me today on this journey towards improved patient safety. If you are interested in more information about applying for an APSF sponsored grant to study patient safety and further advance the field, please see the show notes where I will link more information. I will continue to introduce grant and award winners in future shows.
If you have any questions or comments from today’s show, please email me at [email protected].
Visit APSF.org for detailed information and check out the show notes for links to all the topics we discussed today.
Until next time, stay vigilant so that no one shall be harmed by anesthesia care.
© 2020, The Anesthesia Patient Safety Foundation