P132. Lumbar fusion during the COVID-19 pandemic: greater rates of morbidity and longer procedures

BACKGROUND CONTEXT: The coronavirus-19 (COVID-19) pandemic has altered the standard of care for spine surgery in many ways. However, there is a lack of literature evaluating the potential changes in surgical outcomes and perioperative factors for spine procedures performed during the pandemic. In particular, no large database study evaluating the impact of the COVID-19 pandemic on spine surgery outcomes has been published. PURPOSE: To evaluate the impact of the COVID-19 pandemic on perioperative factors and postoperative outcomes of lumbar fusion procedures. STUDY DESIGN/SETTING: Retrospective cohort study. PATIENT SAMPLE: Patients who underwent primary, elective lumbar fusionbetween 2019 and 2020. OUTCOME MEASURES: Thirty-day readmission, reoperation, morbidity, complications, operative time, non-home discharge disposition, length of hospital stay, total RVUs and RVUs per minute. METHOD(S): The ACS-NSQIP database was queried for all patients who underwent primary lumbar fusion in 2019 and 2020. Exclusion criteria included cervical or thoracic fusion, arthroplasty, non-elective, emergency cases, deformity procedures, malignancy, preoperative sepsis, wound infection and missing perioperative variables. Patients were grouped into cohorts based on 2019 or 2020 operation year. Multivariate logistic and Poisson regression models were utilized to evaluate the impact of 2020 operative year on postoperative outcomes. RESULT(S): A total of 27,446 patients were included in the analysis (12,473 cases in 2020). For the 2020 cohort, non-white race (24.9% vs 23.4%, p=0.004), functional dependence (1.8% vs 1.4%, p=0.022), congestive heart failure (0.5% vs 0.3%, p=0.015), and ASA class =3 (53.5% vs 52.2%, p=0.037) were more common. Lumbar fusions performed in 2020 were also associated with longer mean operative time (209.3+/-99.3 vs. 205.9+/-98.6 minutes, p=0.005) and higher mean fusion levels (1.45+/-0.69 vs 1.41+/-0.65, p 0.05). However, operation year 2020 independently predicted morbidity (OR 1.087 [95% CI 1.007-1.172], p=0.032), pneumonia (1.407 [1.039-1.906], p=0.027), DVT (1.508 [1.106-2.056], p=0.009) and sepsis (1.537 [1.101-2.146], p=0.012). In terms of perioperative variables, operation year 2020 predicted greater operative time (1.012 [1.001-1.013], p=0.046), non-home discharge (0.690 [0.642-0.743], p<0.001), and total RVUs (1.044 [1.004-1.083], p=0.033). CONCLUSION(S): Lumbar fusion procedures performed amidst the COVID-19 pandemic were associated with poorer outcomes, including higher rates of morbidity, pneumonia, DVT and sepsis. In addition, surgeries performed in 2020 were associated with longer operative times and less frequent non-home discharge disposition. FDA DEVICE/DRUG STATUS: This does not discuss or include any applicable devices or drugs. Copyright © 2022

Collateral Damage: Investigating the Impacts of COVID on STEM Professionals with Caregiving Responsibilities

Numerous reports have showcased the negative impacts of the pandemic on women in the workforce-especially those in STEM and with caregiving responsibilities-and the ways in which COVID-19 has further compounded the challenges they face. We developed a survey to investigate how these individuals have navigated the pandemic, asking them to compare their experiences before and during the pandemic as well as to prospectively consider a future as we begin to recover from the pandemic. We compare self-reported pandemic experiences of these NSF STEM professionals, contrasting by gender and caregiving status. Specifically, we address how the COVID-19 pandemic impacted the professional and personal lives of STEM professionals and whether these effects emerge primarily as gender effects, primarily as caregiver effects, or at the intersection of gender and caregiving roles. Our results highlighted that women, non-binary individuals, and transgender men in STEM have been particularly vulnerable during the pandemic, since they tend to bear the heavier load of caregiving responsibilities. Compared to cismen and non-caregivers, they reported decreased productivity in and satisfaction with their job/work;reduced time spent on research/writing but increased time teaching;an increased toll of societal, political, and personal physical/mental health;and greater blurring of boundaries between work and personal life. To date, the story told about the impact of the pandemic has focused on the acute crisis of COVID-19 on the STEM workforce. It may be too early to tell what the abiding, long-term effects will be for STEM professionals. As we move forward, we must begin to focus on the long-range story of what we do to support individuals in the STEM professions, preventing an “epidemics loss” of caregivers and women, non-binary individuals, and transgender men. © American Society for Engineering Education, 2022.

Work-in-Progress: Using Latent Dirichlet Allocation to uncover themes in student comments from peer evaluations of teamwork

This work-in-process research paper investigates common themes in peer-to-peer comments of teamwork behavior effectiveness collected with peer evaluations in engineering student teams in three time horizons - prior to COVID-19 pandemic, early phase of pandemic, and mature phase of pandemic. Constructive feedback is imperative to maintaining healthy team climate and dynamic, which facilitates positive individual and team learning outcomes. Asking engineering students to provide self- and peer-evaluation feedback in comments accomplishes multiple objectives. Students reflect on teammates' behavior and performance rather than relying on (potentially biased) general perceptions to provide evidence-based comments for the assessment period. Repeated practice giving feedback also tends to improve students' ability to provide constructive and insightful evaluations. To better understand what and how engineering students provide feedback in teamwork, the Comprehensive Assessment of Team-Member Effectiveness (CATME) peer evaluation tool suite was used to provide a framework to teach students about effective team behaviors using a behavioral-anchored rating scale. Using CATME also provided a mechanism for collecting self- and peer- evaluation survey data in both structured (the behavioral scale) and open-ended (comments) ways. Latent Dirichlet Allocation (LDA) was used as the classic method for topic modeling to analyze first-year engineering students' self- and peer- comments in the introductory engineering foundation courses in a large Midwestern R1 university. Topic Coherence measure (c_v) for topic quality was used to determine the optimal number of topics to represent the comment data. The themes of each of the topics identified were interpreted by thematic analysis of the most commonly used words and responses associated with each topic identified by the LDA model. The preliminary results showed that pre-pandemic themes closely matched the five behavioral dimensions of the CATME instrument. Data collected in Spring 2020 required more themes to capture the complexity of the transition to online learning. Comments from Spring 2021 required an even larger number of themes to describe the experience of teamwork during a fully virtual class implementation. © American Society for Engineering Education, 2022.

Development of Hybrid Laboratory Sessions During the COVID-19 Pandemic

This paper presents the hybrid delivery method of a laboratory experiment at the Stability Wind Tunnel of Virginia Tech to some 170 students during April 2020, which can be considered the early stages of the COVID-19 induced lockdown. The steps of converting the hands-on labs to hybrid labs are presented in detail. Namely, a videoconferencing tool was used to (i) stream the instrumentation used, (ii) provide live video feed, and (iii) to interact with the students. Labs began with a remote tour of the facility, whilst the presence of an expert-at-a-distance added key value to the labs as it enhanced students conceptual understanding via verbal interaction. The experiments were then performed by laboratory personnel while student’s engagement was kept high via the teleconferencing session. At the end of the two-week laboratory campaign, the students provided feedback of the laboratory sessions via an open-ended and closed-ended survey. They highlighted the added value of expert-at-distance, the live video feed, and the ability of working with instructors. While their feedback was rather positive, students showed a strong preference toward hands-on laboratories. Overall, the methodologies presented here can be considered a relatively low-cost method to upgrade hands-on laboratories to hybrid or remote labs. © 2022, Advances in Engineering Education. All Rights Reserved.

Using Natural Language Processing to Facilitate Student Feedback Analysis

This research paper compares the results of a novel computer-assisted approach for analyzing a large volume of open-ended responses with those of a more traditional open coding approach. The work is motivated by the observation that in engineering education ecosystems, community members produce text through myriad activities both inside and outside of the classroom in teaching and research settings. In many of these cases, there is an abundance of text available to educators and researchers that could provide insight into various phenomena of interest within the system - student conceptual understanding, student experiences outside the classroom, how instructors can improve their teaching, or even shifts in collective conversations. Unfortunately, while these bodies of text have the potential to provide novel insights to educators and researchers, traditional analysis techniques do not scale well. For example, analyzing larger amounts of text can take one grader or researcher significantly more time than grading a small set of text responses. A larger body of text also creates more challenges for intrarater reliability. Likewise, expanding the size of the grading or research team can create interrater reliability challenges and the possibility of bias. To address this opportunity, we have created a natural language processing system that augments human analysis so as to facilitate and enhance the work of one person (or team). Specifically, we take minimally pre-processed text, embed them using a pre-trained transformer (a specific kind of neural network architecture trained to encode inputs and decode outputs), and perform a sequence of dimension reduction techniques capped with a final clustering step. Such a system can help reduce the amount of time needed to analyze the text by effectively running a first pass on the text to group similar responses together. The human user can utilize these groupings to perform further analysis to fine tune and identify meanings in ways that only a human could. The system also can help improve consistency by analyzing across the entire collection of texts simultaneously and grouping similar items together. This is in contrast with a single person or a team that would have to work in series, analyzing responses sequentially and thereby creating the potential for inconsistencies across time. In this paper we describe the system's architecture and data processing steps. We demonstrate the utility of this approach by applying the method on three questions from an end-of-semester feedback survey in a large, required introductory engineering course. The survey questions were part of a general feedback survey and asked students about their experiences in the transition to online learning subsequent to the SARS-CoV-2 outbreak.. Our results suggest that the pre-analysis text clustering can improve speed and accuracy of coding when compared with unassisted human coding-the system augments what we have traditionally done in coding, grading, or making sense of large quantities of textual data. As natural language processing techniques continue to develop, the engineering education research community should continue to explore potential applications to improve understanding and sensemaking from large volumes of underutilized text data from both within and outside of classroom settings. © American Society for Engineering Education, 2021

Effectiveness of a virtual team simulation exercise for interprofessional students at the university of hawaii

Background: The University of Hawaii Health Sciences Schools have conducted the Hawaii InterProfessional Team Collaboration Simulation (HIPTCS) exercise since 2014. The scenario is discharge planning for a complex geriatric patient. Due to the COVID-19 pandemic, it was converted to a virtual format, and we compared efficacy to the original format. Methods: In 2020, half the students participated in person in February (pre-COVID), and half via video conferencing in April (during COVID). This included medical, nursing, pharmacy, social work and dietetics students. In the online version, teams of students and facilitators were managed with breakout rooms. The exercise began with a virtual icebreaker team puzzle, with debriefing by interprofessional (IP) faculty. Students then developed a discharge plan and participated in a simulated family meeting with an actor. After the exercise, IP faculty again provided structured co-debriefing to highlight principles of effective teamwork. Students self-rated IP collaborative practice core competencies using a retrospective pre-post ICCAS survey with 20 items (5-point Likert scale). Results: Participants included 122 students in-person, and 113 virtually. Paired T-tests showed significant improvements in ICCAS scores in all IPE categories for both cohorts (all p<0.0001), with no significant differences comparing in-person to virtual. Students also evaluated the activity (Likert Scale 1-5, 5=best). They were very satisfied with ability to work through the simulation (mean 4.15±0.71) and improved in IP collaboration (mean 4.28±0.67), with no significant differences whether in-person or virtual. For both cohorts, students described the most helpful aspect of the simulation was 'Collaborating with other health professions' with the second being 'Working with Actors.' Conclusions: We were able to convert a geriatrics simulation to a completely virtual format during the COVID-19 pandemic. Students still achieved significant improvements in all IPE core competencies for both in-person and virtual cohorts, with high levels of satisfaction for both.

The development of remote laboratory sessions at the stability wind tunnel of virginia tech during the coronavirus pandemic

This paper discusses the remote delivery of wind tunnel experiments performed at the Stability Wind Tunnel of Virginia Tech, in April 2020, during the early stages of the coronavirus pandemic. The originally in-person laboratories were transformed to entirely remote sessions, on a time-frame of a few weeks, to ensure the delivery of the laboratory sessions and the safety of all participants via social distancing and the use of widely-available video conferencing software. The paper outlines the structure of the laboratory sessions, comprising the tour of the facility, data acquisition, and data visualization alongside with all information technology components used to ensure the successful remote delivery of the laboratory sessions. After the two-week-long experimental campaign, participating students provided feedback on the efficacy of the laboratories via a detailed questionnaire. It was found that the students were highly satisfied with the remote delivery of the laboratory sessions but showed a preference for in-person laboratories. © 2021, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

SHARP Joint Action – Strengthening International Health Regulations and preparedness in the EU

Although the preparedness to health emergencies of biological, chemical, environmental and unknown origin across the Europe is at high level, gaps do exist across the EU Member States and European countries. The previous coronavirus epidemic, SARS in 2002, showed that countries responded largely individually to this emerging threat. EU wide, joint responses were not taken. SARS epidemic showed that strengthening of the common EU efforts was needed. Many actions were taken, and since 2013 the European Commission Decision 1082/2013/EU on serious cross-border threats to health has provided a framework to improve preparedness and to strengthen the response capacities in Europe to health threats. SHARP Joint Action is a 3-year collaborative action of 26 countries and 61 partners, co-funded by the EC and coordinated by the Finnish Institute for Health and Welfare, Finland, and co-coordinated by Robert Koch Institute, Germany and National Institute of Infectious Diseases Lazzaro Spallanzani, Italy. SHARP started it's actions in June 2019, and it aims to strengthen implementation of the International Health Regulations (IHR) and the Decision 1082/2013/EU. SHARP consists of ten work packages covering core public health capacities, including: IHR core capacity strengthening and assessment, preparedness and response planning, training, laboratory preparedness and responsiveness, chemical safety and threats, and case management, infection prevention and control preparedness. Through this cross-sectoral approach, SHARP supports the Member States and partner countries in strengthening their capacities. In response to the COVID-19 outbreak, SHARP has also supported the EC and the Member States, and especially work packages for laboratory preparedness and responsiveness (WP7) and for case management and infection prevention and control preparedness (WP10) were activated. The activities regarding laboratory preparedness and response have been coordinated with the ECDC. Key messages SHARP Joint Action strengthens the implementation of Decision 1082/2013/EU on serious cross-border threats to health and the implementation of International Health Regulations in the EU. SHARP improves preparedness and response to serious cross-border threats to health, and resilience of the health systems at national, EU and regional level.