OBJECTIVES:This study aimed to evaluate sex-based differences in outcomes following ruptured abdominal aortic aneurysm (AAA) repair, focusing on mortality, morbidity, and postoperative complications. DESIGN:Retrospective cohort study SETTING: Multi-institutional data from the Vascular Quality Initiative national database, covering a period from January 2003 to December 2022. PARTICIPANTS:We included 7,548 patients undergoing open or endovascular repair for ruptured AAA: 5,829 men (77.2%) and 1,719 women (22.8%). INTERVENTIONS:Patients underwent either open surgical repair or endovascular aneurysm repair for ruptured AAA. MEASUREMENTS AND MAIN RESULTS:Between 2003 and 2022, the rate of mortality decreased significantly for both sexes (57.1% to 31.6% in women and 38.5% to 19.6% in men). Men had a higher incidence of coronary artery disease (22.7% v 17.3%; p < 0.001), more frequent occurrences of prior percutaneous coronary intervention (12.8% v 10.2%; p = 0.004), and previous aneurysm repair (7.2% v 5.3%; p = 0.005) compared with women. Men demonstrated worse cardiovascular (OR 0.82 [0.72-0.94]; p = 0.005) and pulmonary (OR 0.86 [0.73-1.00]; p = 0.025) complications. Women exhibited higher in-hospital mortality (OR 1.27 (1.12-1.44); p < 0.001) and presented at an older age (76.0 years v 71.0 years; p < 0.001), with a higher incidence of hypertension (78.1% v 75.0%; p = 0.008). Women experienced a significantly longer average time from symptom onset to repair (8.00 hours v 7.00 hours; p = 0.002). CONCLUSIONS:Significant sex-based disparities were found in AAA repair outcomes. Men had higher comorbidity burdens while women presented at an older age with an increased time from symptom onset to repair. These findings support the need for sex-specific guidelines and interventions to improve outcomes for both women and men.

OBJECTIVE:To describe the development and implementation of a comprehensive in situ simulation-based curriculum for anesthesia residents. DESIGN:This is a prospective study. SETTING:This study was conducted at a university hospital. PARTICIPANTS:This single-center prospective study included all 53 anesthesia residents enrolled in the anesthesia residency program. INTERVENTIONS:Introduction of a routine, high-fidelity, in situ simulation program that incorporates short sessions to train residents in the necessary skill sets and decision-making processes required in the operating room. MEASUREMENTS AND MAIN RESULTS:Our team conducted 182 individual 15-minute simulation sessions over 3 months during regular working hours. All 53 residents in our program actively participated in the simulations. Most residents engaged in at least 3 sessions, with an average participation rate of 3.4 per resident (range, 1-6 sessions). Residents completed an online anonymous survey, with a response rate of 71.7% (38 of 53 residents) over the 3-month period. The survey aimed to assess their overall impression and perceived contribution of this project to their training. CONCLUSIONS:Our proposed teaching method can bridge the gap in resident training and enhance their critical reasoning to manage diverse clinical situations they may not experience during their residency.

Simulation-based training is an essential component in the education of transthoracic echocardiography (TTE). Nevertheless, current TTE teaching methods may be subject to certain limitations. Hence, the authors in this study aimed to invent a novel TTE training system employing three-dimensional (3D) printing technology to teach the basic principles and psychomotor skills of TTE imaging more intuitively and understandably. This training system comprises a 3D-printed ultrasound probe simulator and a sliceable heart model. The probe simulator incorporates a linear laser generator to enable the visualization of the projection of the ultrasound scan plane in a 3D space. By using the probe simulator in conjunction with the sliceable heart model or other commercially available anatomic models, trainees can attain a more comprehensive understanding of probe motion and related scan planes in TTE. Notably, the 3D-printed models are portable and low-cost, suggesting their potential utility in various clinical scenarios, particularly for just-in-time training.

Objectives To investigate whether implementation of a multidisciplinary protocol for ruptured abdominal aortic aneurysm (rAAA) management reduces rates of adverse complications. Design A retrospective before-after study. Setting A tertiary-care academic hospital. Participants Adult patients who underwent open or endovascular rAAA repair; data were stratified into before-protocol implementation (group 1: 2015-2018) and after-protocol implementation (group 2: 2019-2022) groups. Intervention The protocol details the workflow for vascular surgery, anesthesia, emergency department, and operating room staff for a rAAA case; training was accomplished through yearly workshops. Measurements and Main Results The primary outcome was in-hospital mortality. Secondary outcomes included all-cause morbidity and other major complications. Differences in postoperative complication rates between groups were assessed using Pearson's χ2 test. Of the 77 patients included undergoing rAAA repair, 41 (53.2%) patients were in group 1, and 36 (46.8%) patients were in group 2. Patients in group 2 had a significantly shorter median time to incision (1.0 v 0.7 hours, p=0.022) and total procedure time (180.0 v 160.5 minutes, p=0.039) for both endovascular and open repair. After protocol implementation, patients undergoing endovascular repair exhibited significantly lower rates of mortality (46.2% v 20.0%, p=0.048), all-cause morbidity (65.4% v 44.0%, p=0.050), and renal complications (15.4% v 0.0%, p=0.036); patients undergoing open repair for a rAAA exhibited significantly lower rates of mortality (53.3% v 27.3%, p=0.018) and bowel ischemia (26.7% v 0.0%, p=0.035). Conclusions Implementation of a multidisciplinary protocol for the management of a rAAA may reduce rates of adverse complications and improve the quality of care.

Background:This study's primary aim was to determine how training programs use simulation-based medical education (SBME), because SBME is linked to superior clinical performance.Methods:An anonymous 10-question survey was distributed to anesthesiology residency program directors across the United States. The survey aimed to assess where and how SBME takes place, which resources are available, frequency of and barriers to its use, and perceived utility of a dedicated departmental education laboratory.Results:The survey response rate was 30.4% (45/148). SBME typically occurred at shared on-campus laboratories, with residents typically participating in SBME 1 to 4 times per year. Frequently practiced skills included airway management, trauma scenarios, nontechnical skills, and ultrasound techniques (all ≥ 77.8%). Frequently cited logistical barriers to simulation laboratory use included COVID-19 precautions (75.6%), scheduling (57.8%), and lack of trainers (48.9%). Several respondents also acknowledged financial barriers. Most respondents believed a dedicated departmental education laboratory would be a useful or very useful resource (77.8%).Conclusion:SBME is a widely incorporated activity but may be impeded by barriers that our survey helped identify. Barriers can be addressed by departmental education laboratories. We discuss how such laboratories increase capabilities to support structured SBME events and how costs can be offset. Other academic departments may also benefit from establishing such laboratories.

OBJECTIVE:To establish agreement among nationwide experts through a Delphi process on the key components of perioperative ultrasound and the recommended minimum number of examinations that should be performed by a resident upon graduation.DESIGN:A prospective cross-sectional study.SETTING:A survey on multiinstitutional academic medical centers.PARTICIPANTS:Anesthesiology residency program directors and/or experts in perioperative ultrasound.INTERVENTIONS:A list of components and examinations recommended for anesthesiology resident training in perioperative ultrasound was developed based on guidelines and 2 survey rounds among a steering committee of 10 experts. A questionnaire asking for a rating of each component on a 5-point Likert scale subsequently was sent to an expert panel of 120 anesthesiology residency program directors across the United States. An agreement of at least 70% of participants, rating a component as 4 or 5, was compulsory to list a component as essential for anesthesiology resident training in perioperative ultrasound.MEASUREMENTS AND MAIN RESULTS:The nationwide survey's response rate was 62.5%, and agreement was reached after 2 Delphi rounds. The final list included 44 essential components for basic ultrasound physics and knobology, cardiac ultrasound, lung ultrasound, and ultrasound-guided vascular access. Agreement was not reached for abdominal ultrasound, gastric ultrasound, and ultrasound-guided airway assessment. Agreement for the recommended minimum number of examinations that should be performed by a resident upon graduation included 50 each for transthoracic and transesophageal echocardiography, and 20 each for lung ultrasound, ultrasound-guided central line, and ultrasound-guided arterial line placements.CONCLUSIONS:The recommendations outlined in this survey can be used to establish standardized training for perioperative ultrasound by anesthesiology residency programs.

The coronavirus disease 2019 (COVID-19) pandemic has altered approaches to anesthesiology education by shifting educational paradigms. This vision article discusses pre-COVID-19 educational methodologies and best evidence, adaptations required under COVID-19, and evidence for these modifications, and suggests future directions for anesthesiology education. Learning management systems provide structure to online learning. They have been increasingly utilized to improve access to didactic materials asynchronously. Despite some historic reservations, the pandemic has necessitated a rapid uptake across programs. Commercially available systems offer a wide range of peer-reviewed curricular options. The flipped classroom promotes learning foundational knowledge before teaching sessions with a focus on application during structured didactics. There is growing evidence that this approach is preferred by learners and may increase knowledge gain. The flipped classroom works well with learning management systems to disseminate focused preclass work. Care must be taken to keep virtual sessions interactive. Simulation, already used in anesthesiology, has been critical in preparation for the care of COVID-19 patients. Multidisciplinary, in situ simulations allow for rapid dissemination of new team workflows. Physical distancing and reduced availability of providers have required more sessions. Early pandemic decreases in operating volumes have allowed for this; future planning will have to incorporate smaller groups, sanitizing of equipment, and attention to use of personal protective equipment. Effective technical skills training requires instruction to mastery levels, use of deliberate practice, and high-quality feedback. Reduced sizes of skill-training workshops and approaches for feedback that are not in-person will be required. Mock oral and objective structured clinical examination (OSCE) allow for training and assessment of competencies often not addressed otherwise. They provide formative and summative data and objective measurements of Accreditation Council for Graduate Medical Education (ACGME) milestones. They also allow for preparation for the American Board of Anesthesiology (ABA) APPLIED examination. Adaptations to teleconferencing or videoconferencing can allow for continued use. Benefits of teaching in this new era include enhanced availability of asynchronous learning and opportunities to apply universal, expert-driven curricula. Burdens include decreased social interactions and potential need for an increased amount of smaller, live sessions. Acquiring learning management systems and holding more frequent simulation and skills sessions with fewer learners may increase cost. With the increasing dependency on multimedia and technology support for teaching and learning, one important focus of educational research is on the development and evaluation of strategies that reduce extraneous processing and manage essential and generative processing in virtual learning environments. Collaboration to identify and implement best practices has the potential to improve education for all learners.

Background: Readmission to the Intensive Care Unit (ICU) is associated with a high risk of in-hospital mortality and higher health care costs. Previously published tools to predict ICU readmission in surgical ICU patients have important limitations that restrict their clinical implementation. We sought to develop a clinically intuitive score that can be implemented to predict readmission to the ICU after surgery or trauma. We designed the score to emphasize modifiable predictors. Methods: In this retrospective cohort study, we included surgical patients requiring critical care between June 2015 and January 2019 at Beth Israel Deaconess Medical Center, Harvard Medical School, MA, USA. We used logistic regression to fit a prognostic model for ICU readmission from a priori defined, widely available candidate predictors. The score performance was compared with existing prediction instruments. Results: Of 7,126 patients, 168 (2.4%) were readmitted to the ICU during the same hospitalization. The final score included 8 variables addressing demographical factors, surgical factors, physiological parameters, ICU treatment and the acuity of illness. The maximum score achievable was 13 points. Potentially modifiable predictors included the inability to ambulate at ICU discharge, substantial positive fluid balance (>5 liters), severe anemia (hemoglobin <7 mg/dl), hyperglycemia (>180 mg/dl), and long ICU length of stay (>5 days). The score yielded an area under the receiver operating characteristic curve of 0.78 (95% CI 0.74-0.82) and significantly outperformed previously published scores. The performance of the underlying model was confirmed by leave-one-out cross-validation. Conclusion: The RISC-score is a clinically intuitive prediction instrument that helps identify surgical ICU patients at high risk for ICU readmission. The simplicity of the score facilitates its clinical implementation across surgical divisions.

High quality feedback on resident clinical performance is pivotal to growth and development. Therefore, a reliable means of assessing faculty feedback is necessary. A feedback assessment instrument would also allow for appropriate focus of interventions to improve faculty feedback. We piloted an assessment of the interrater reliability of a seven-item feedback rating instrument on faculty educators trained via a three-workshop frame-of-reference training regimen. The rating instrument's items assessed for the presence or absence of six feedback traits: actionable, behavior focused, detailed, negative feedback, professionalism / communication, and specific; as well as for overall utility of feedback with regard to devising a resident performance improvement plan on an ordinal scale from 1 to 5. Participants completed three cycles consisting of one-hour-long workshops where an instructor led a review of the feedback rating instrument on deidentified feedback comments, followed by participants independently rating a set of 20 deidentified feedback comments, and the study team reviewing the interrater reliability for each feedback rating category to guide future workshops. Comments came from four different anesthesia residency programs in the United States; each set of feedback comments was balanced with respect to utility scores to promote participants’ ability to discriminate between high and low utility comments. On the third and final independent rating exercise, participants achieved moderate or greater interrater reliability on all seven rating categories of a feedback rating instrument using Gwet's agreement coefficient 1 for the six feedback traits and using intraclass correlation for utility score. This illustrates that when this instrument is utilized by trained, expert educators, reliable assessments of faculty-provided feedback can be made. This rating instrument, with further validity evidence, has the potential to help programs reliably assess both the quality and utility of their feedback, as well as the impact of any educational interventions designed to improve feedback.

BACKGROUND High-quality and high-utility feedback allows for the development of improvement plans for trainees. The current manual assessment of the quality of this feedback is time consuming and subjective. We propose the use of machine learning to rapidly distinguish the quality of attending feedback on resident performance. METHODS Using a preexisting databank of 1925 manually reviewed feedback comments from 4 anesthesiology residency programs, we trained machine learning models to predict whether comments contained 6 predefined feedback traits (actionable, behavior focused, detailed, negative feedback, professionalism/communication, and specific) and predict the utility score of the comment on a scale of 1-5. Comments with ≥4 feedback traits were classified as high-quality and comments with ≥4 utility scores were classified as high-utility; otherwise comments were considered low-quality or low-utility, respectively. We used RapidMiner Studio (RapidMiner, Inc, Boston, MA), a data science platform, to train, validate, and score performance of models. RESULTS Models for predicting the presence of feedback traits had accuracies of 74.4%-82.2%. Predictions on utility category were 82.1% accurate, with 89.2% sensitivity, and 89.8% class precision for low-utility predictions. Predictions on quality category were 78.5% accurate, with 86.1% sensitivity, and 85.0% class precision for low-quality predictions. Fifteen to 20 hours were spent by a research assistant with no prior experience in machine learning to become familiar with software, create models, and review performance on predictions made. The program read data, applied models, and generated predictions within minutes. In contrast, a recent manual feedback scoring effort by an author took 15 hours to manually collate and score 200 comments during the course of 2 weeks. CONCLUSIONS Harnessing the potential of machine learning allows for rapid assessment of attending feedback on resident performance. Using predictive models to rapidly screen for low-quality and low-utility feedback can aid programs in improving feedback provision, both globally and by individual faculty.

THE NOVEL coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has led to a global pandemic termed as “coronavirus disease 2019 (COVID-19)”, causing an unprecedented pressure on healthcare systems. Clinical care for COVID-19 patients varies widely in different parts of the world, with rapid evolution in diagnostic and therapeutic management. New insights into clinical imaging techniques are being acquired rapidly to reduce infection risk and maximize resource utilization. Previously, ultrasonography was established as an effective and inexpensive alternative imaging modality for the identification and monitoring of pneumonia and acute respiratory distress syndrome (ARDS).

Anesthesiology residents spend most of their training in operating rooms, but intraoperative teaching is often unstructured. Needs assessment indicated a need to incorporate a more evidence-based approach to education and improvement of our methods of introducing residents to primary anesthesiology literature. Kern's 6-step approach to curriculum development was used to create a robust and innovative curriculum to increase both the evidence-based component of our curriculum and the amount of educational intraoperative discussion among trainees and faculty. Our curriculum uses a structured topic outline, an e-journal club, and other relevant resources to facilitate discussion of the topics.

*Department of Anesthesia, Critical Care and Pain Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts †Department of Anesthesiology, Beaumont Health, Royal Oak, Michigan The authors declare that they have nothing to disclose. Address Correspondence to: Sara Neves, MD, Department of Anesthesia, Critical Care and Pain Medicine, Beth Israel Deaconess Medical Center, 330 Brookline Avenue, Boston, MA 02215. E-mail: [email protected]