Compassion, Burnout, and Self-care During COVID-19: On the Collective Impact of Self-soothing Super Highways

This is a story of six researchers who came together to make sense of the tumult triggered by the COVID-19 pandemic. The team centered emotion and affectivity, letting it guide research design, team meetings, and the ways we related with interviewees and each other. The project also prompted us to critically examine our habits and realize the relatively privileged ways our own strategies of self-soothing could have problematic repercussions on the collective. As such, centering compassion and emotion not only served as a method of individual coping but also served to critically reveal how we as academics are enmeshed in systems that bring trauma to bear. This chapter closes with several ideas about how we might engage in research methods during and about times of collective suffering that move beyond individual emotional release and may prompt relational work toward communal catharsis and systematic change. © The Editor(s) (if applicable) and The Author(s), under exclusive licence to Springer Nature Switzerland AG 2022.

Impact of Time-Motion Patient Flow Analysis on the Productivity of an Endoscopy Unit in a Large Safety-Net Health Center

Introduction: The COVID-19 pandemic disrupted health care delivery, particularly for high-volume procedural areas. To improve productivity in the Los Angeles County 1 University of Southern California Medical Center (LAC + USC) Endoscopy Unit, we initiated an iterative rapid cycle quality improvement process to identify inefficiencies and implement changes to our workflow. Method(s): A time-motion analysis of patient flow through the LAC + USC Endoscopy Unit was used to construct a time-tracked flow sheet to track individual patients as they moved through the Unit. Data were collected weekly over 3 9-10 week phases, and intervening plan-do-study-act (PDSA) cycles were conducted to direct interventions for subsequent phases. Following phase 1 (9/1/21 to 11/9/21) we implemented targeted interventions at the start of phase 2 (12/1/21 to 2/1/22) and phase 3 (3/15/22 to 5/31/22). Phase 2 was focused on our anesthesia supported endoscopy room which requires greater resource coordination. Metrics were compared to published benchmarks. Linear regression was used to compare outcome parameters for the lean process flow improvement project. Result(s): Our phase 1 analysis showed operational delays in room turnover time for all procedures and pre-operative assessment and first-case on time start percentage for procedures supported by anesthesia, when compared to published benchmarks (Table 1). In phase 2 we implemented an intervention of combining pre-anesthesia visits with endoscopy teaching visits for patients designated to have anesthesia support. This significantly improved both turnover time and throughput for the anesthesia room (Table 1). In phase 3 we initiated a policy of preparing the first patient of the day in the procedure room which dramatically increased first-case on time start percentage. We further streamlined inter-procedure processes by simultaneously consenting, placingmonitoring equipment and documenting in the time between procedures, leading to a greater than 20% increase in total procedure volume (Table 1). Procedure throughput for the anesthesia supported procedure room increased from 4.5 to 7 to 9 procedures per room per day for phases 1, 2, and 3 respectively (Table 1). EndoscopyUnit staffing remained unchanged throughout the study period. Conclusion(s): Time-motion analysis of patient flow may be used to perform targeted interventions with significant improvements in Endoscopy Unit efficiency. This may be achieved without costly interventions such as hiring additional support staff or faculty. (Table Presented).

Exploring Language-Interfaced Fine-Tuning for COVID-19 Patient Survival Classification

We present Language-Interfaced Fine-Tuning (LIFT) in application to COVID-19 patient survival classification. LIFT describes translating tabular Electronic Health Records (EHRs) into text inputs for transformer neural networks. We study LIFT with a dataset of 5,371 COVID-19 patients. We focus on the predictive task of survival classification utilizing demographic and medical history features. We begin by presenting information about our dataset. We preface our investigation in text-based transformers by reporting the performances of conventional machine learning models such as Logistic Regression and Random Forest classifiers. We also present the results of a few configurations of tabular input-based Deep Multilayer Perceptron (MLP) networks. 86% of the patients in our database survived in the measured time window. Thus, predictive models are heavily biased to predict that a patient will survive. We emphasize that this problem of Class Imbalance was a major challenge in developing these models. Our balanced sampling strategy from examples in the majority and minority classes is crucial to achieving even reasonable predictive performance. For this reason, we also report performance based on Precision, Recall, and F-score metrics, in addition to Accuracy. Having established baselines with tabular inputs, we then shift our focus to the prompts for translating from tabular to text inputs. We report the performance of 5 prompts. The LIFT model achieves an F-score on the held-out test set of 0.21, slightly behind the Deep MLP with Tabular Features score of 0.23. Both models outperform the Random Forest with Tabular Features at 0.15. We believe that LIFT is a very exciting direction for machine learning in healthcare applications because text-based inputs enables us to take advantage of recent advances in Transfer Learning and Retrieval-Augmented Learning. This study illustrates the effectiveness of converting tabular EHRs to text inputs and utilizing transformer neural networks for prediction. © 2022 IEEE.

Procedures for the Integrative Assessment Process in Pandemic Conditions: Its Application

The design of three procedures for the integrative evaluation in the Bachelor of Construction Education career requires an accurate evaluation of its results, tempered to the current conditions caused by the Covid-19 pandemic. The purpose of this article is to present the achievements of the application of three procedures. For the application of the first procedure, a workshop was developed and observation was used to assess its effectiveness. The second procedure is deployed in a sample of students and is evaluated through a motivation questionnaire and a satisfaction survey, using the Iadov technique. The third procedure is applied through a pre-experimental design, with a post-test to the control group and the experimental group, using the Mann-Whitney U as a statistical technique. The application of the procedures allowed to verify the disposition and understanding of the students towards the new evaluation process and it was revealed with the third procedure a significant advance in the development of the modes of action in the students of the experimental group. It is concluded that the use of the three procedures allows to improve the development of the students of the Bachelor of Construction Education profile.

COVID-19 and remittances to Mexican states

With the onset of the COVID-19 pandemic and its negative effect on economic activity, a decrease in remittances was expected. However, on the contrary, remittances have increased in countries like Mexico. Using a fixed-effect model with information at the state level, this study finds evidence that the increase in COVID-19 cases was associated with a higher level of remittances to Mexican states, allowing some degree of insurance against the pandemic. However, remittances did not respond to the decrease in employment caused by the pandemic in local economies. A portion of the observed increases in remittances during the pandemic can be explained by factors at the national level. © 2023, Oviedo University Press. All rights reserved.

Volatile Organic Compound Exhaled Breath Sensing

This book chapter presents a broad overview of the application of nanotechnology in the biomedical area, exemplified by the application of several gas sensors (electrochemical sensors, piezoelectric sensors, optical, chemoresistive, metal oxide sensors, surface acoustic wave sensors) and focusing on the study of volatile organic compounds (VOCs) in exhaled breath for the screening of diseases of worldwide interest such as breast cancer, lung cancer, COVID-19, post COVID-19 syndrome, colorectal cancer, prostate cancer, diabetes, chronic obstructive disease, among others. This document aims to provide the state of the art in disruptive technologies based on nanosensors, especially electronic noses and the advances and perspectives in this field. The present work represents an important tool for researchers who are in the field of the development of sensing disruptive technologies for the study of VOCs in biological matrices (i.e., exhaled breath). Thus, the application of gas sensors has proven to be feasible in the biomedical area and a promising area within the diagnosis of communicable and non-communicable diseases, to be applied in POC settings, clinics, hospitals, doctors' offices, and especially in-field applications for less-favored populations where they lack the minimum resources to achieve universal health coverage. © 2023 Elsevier Ltd. All rights reserved

Smart Urban Planning and Videogames: The Value of Virtualization as Prognosis of Urban Scenes

Urban planning and architecture have always played a fundamental role in videogames, directly or indirectly. Together with the characters and the historical plot of the game, they have made it possible to create attractive virtual worlds in which to enjoy experiences that go beyond fiction. Today, we are at a turning point. New technologies applied to the development of videogames provide a great opportunity to rethink new smart ways of planning and managing the city that are more participatory and inclusive in the post-Covid world. Within this context, the main objective of this paper is to explore and highlight the experimental possibilities that virtual space can offer to urban planning and architecture of a smart city. In this sense, it is proposed the integration in the urban planning process of a methodology that seeks to speculate on the possibilities that virtual models can offer, merging virtual space and real space in a collaborative work. As a result, the existence of a symbiotic relationship between reality and virtuality is confirmed, making possible new resilient ways of understanding space, as well as testing new strategies, systems and complex social, political and/or economic organizations in virtual urban environments very close to reality. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Adapting mental health care after the COVID-19 outbreak: Preliminary findings from a public general hospital in Madrid (Spain)

This letter discusses mental health care after the COVID-19 outbreak by presenting preliminary findings from a public general hospital in Madrid. The pandemic caused by the SARS-CoV-2 poses a major challenge for national health systems around the globe. In these situations, healthcare centers are urged to adjust their structures to the demands of the outbreak in order to protect both the users and the workers. However, this emergency has no precedent in the recent history, and entire hospitals and clinics need further adaptations for which there is no previous evidence. This affects mental healthcare teams, which deal with the unknown psychological consequences of an overwhelming, global crisis. La Paz University Hospital is a public general hospital that provides healthcare to a catchment area of more than half a million people in Madrid. So far, more than 2,700 confirmed cases of SARS-CoV-2 have been attended in this hospital, which required a complete restructuring process. A few days after the outbreak, its mental health team managed to develop a COVID-19 intervention protocol that was based on its previous experience during the 2014 Ebola crisis in Madrid and on the reports that were coming from China. (PsycInfo Database Record (c) 2022 APA, all rights reserved)

Overview of Rest-Mex at IberLEF 2022: Recommendation System, Sentiment Analysis and Covid Semaphore Prediction for Mexican Tourist Texts

This paper presents the framework and results from the Rest-Mex task at IberLEF 2022. This task considered three tracks: Recommendation System, Sentiment Analysis and Covid Semaphore Prediction, using texts from Mexican touristic places. The Recommendation System task consists in predicting the degree of satisfaction that a tourist may have when recommending a destination of Nayarit, Mexico, based on places visited by the tourists and their opinions. On the other hand, the Sentiment Analysis task predicts the polarity of an opinion issued and the attraction by a tourist who traveled to the most representative places in Mexico. We have built corpora for both tasks considering Spanish opinions from the TripAdvisor website. As a novelty, the Covid Semaphore Prediction task aims to predict the color of the Mexican Semaphore for each state, according to the Covid news in the state, using data from the Mexican Ministry of Health. This paper compares and discusses the participants' results for all three tacks.

In vitro antiviral effect of silver nanoparticles against SARS-CoV-2

Introduction: COVID-19 is an acute respiratory tract disease caused by the emerging coronavirus SARS-CoV-2. Although several options for che-moprophylaxis are under development, effective treatment for COVID-19 is not yet available. Objective(s): To investigate the antiviral properties of synthesized silver na-noparticles (AgNPs) against SARS-CoV-2 using in vitro models. Material(s) and Method(s): This work synthesized AgNPs using an electrochemical method and characterized them using physico-chemical techniques (ICP-OES, ultraviolet-visible spectroscopy, and transmission electron microscopy). AgNPs with diameter sizes ranging between 2.6 to 30 nm and an average size of 6.2 nm were obtained by the electrochemical method. The cytotoxic effect and the antiviral activity of prepared AgNPs against SARS-CoV-2 were evaluated in vitro using Vero E6 cells. Cell viability was evaluated by MTT assay in the presence of serial dilutions of AgNPs. The antiviral effect of AgNPs was evaluated before and after the infection of Vero E6 cells by plaque assay. Result(s): Cytotoxic effect was observed at concentrations above 0.07 ppm. AgNPs exhibit a significant reduction of SARS-CoV-2 viral titer after a pre-post treatment strategy with inhibition of 96.5%, 64.13%, and 74.72% at 0.03, 0.017, and 0.008 ppm, respectively. Conclusion(s): Our results suggest that AgNPs could reduce SARS-CoV-2 replication with a low cytotoxic effect. Still, additional in vitro and in vivo studies are required to define its potential therapeutic application in humans. Copyright © 2023 Universidad de Antioquia.

Mortality and Bleeding Complications of COVID-19 Critically Ill Patients with Venous Thrombo-Embolism

Introduction: Venous thrombo-embolism (VTE) disease in critically ill COVID-19 patients is a remarkable issue, especially its relationship with bleeding events and mortality. The objective of this study was to describe the outcomes of critically ill patients with COVID-19 hospitalised in the intensive care unit (ICU) in relationship with VTE during their stay. The secondary objective was to describe prognostic factors in relation with these outcomes. Methods: This was a prospective cohort study of critically ill COVID-19 patients in two Spanish university hospitals that underwent, at the beginning of the study, venous ultrasound of both lower limbs in April 2020. When there was clinical suspicion of new VTE during the 30 day follow up, additional ultrasound or thoracic computed tomography were performed. Global VTE frequency, major bleeding events, and survival were collected, and their predictors were studied. Results: In total, 230 patients were included. Mean age was 60.1 ± 9.9 years and 77% of them were men. After 30 days of follow up, there were 95 VTE events in 86 patients (37.4%). Of these, 60 patients (69.8%) presented with deep vein thrombosis (DVT), 17 patients with pulmonary embolism (PE;19.8%), and nine patients with DVT and PE (10.5%). VTE was related to a longer hospital stay: 50.3 days in VTE patients and 47.2 days in non-VTE patients (p =.014). D-dimer at admission was significantly related to VTE development (p =.007). Major bleeding complications were found in 13 patients (5.7%). None of the demographic variables, treatments, or classic risk factors were related to a higher risk of major bleeding. During the 30 day follow up, 42 patients (18.3%) died. Variables related to mortality were older age (67.4 vs. 58.4 years;p <.001), lower weight (77.9 vs. 87.5 kg;p <.001), lower body mass index (28.2 vs. 30,8 kg/m2;p =.006), hypertension (43.1% vs. 69% of patients;p =.002), lymphocyte count at admission < 0.45 ×109/L (p =.003) and D-dimer at admission > 1 500 ng/mL (p =.014). Patients with VTE at any moment during the follow up tended to die more frequently (50%) than non-VTE patients (34.6%), but this difference was not statistically significant (p =.062). Independent predictors of mortality in the regression model were older age (> 66 years), D-dimer at admission (> 1 500 ng/mL), and low lymphocyte count (< 0.45 ×109/L) with an area under the receiver operating curve of 0.81 (95% confidence interval 0.73 – 0.89). Patients presenting these three conditions presented a mortality of a 100% in the predictive model. Conclusion: VTE frequency in ICU COVID-19 patients is high and the risk of major bleeding is low. Comorbidities and laboratory parameters of admission in these patients can be a useful tool to predict mortality.

INTERDISCIPLINARY STUDENT LEAD CALL CENTER TO SUPPORT SOCIAL NEEDS OF PATIENTS DIAGNOSED WITH COVID19

STATEMENT OF PROBLEM/QUESTION: Social risk factors (SRF), such as food insecurity, represent adverse social circumstances associated with poor health outcomes. The COVID-19 pandemic impacted impoverished communities by exacerbating existing SRF. Students and faculty at Boston University Medical Center (BUMC), an academic safety net hospital, and Boston University School of Social Work (BUSSW) partnered to develop an outreach call center (CC) to explore SRF of patients with COVID-19 and connect them with available social need resources. In this , the development and operations of the CC and descriptive data on the volume and type of outreach efforts will be presented. DESCRIPTION OF PROGRAM/INTERVENTION: Call Center (CC) Operation: An ambulatory RN performed SRF screening in patients diagnosed with COVID-19 and sent referrals to the CC. Then, students called patients and screened for SRF using the THRIVE screening tool, and used the THRIVE Directory, an online repository of resources, to provide information about organizations to support their social needs. Two weeks later, students called the patients to assess whether they received help and provided additional support as needed. MEASURES OF SUCCESS: Volume of outreach calls and type of outreach efforts were evaluated. Number of patients reached through the CC were tracked using Epic reports. Types of referrals were tracked using automated reports from the THRIVE Directory database. Finally, students completed surveys to reflect on their experiences and to evaluate the impact on skills to address social needs. FINDINGS TO DATE: Between 10/2020 and 03/2021, the CC served 312 patients and 478 referrals were made, with a mean of 1.53 referrals per patient. Patients were most often referred to the City of Boston Food Delivery (148 referrals). Patients were most often referred to Government programs (188), followed by BMC programs (133) and Local Non-Profits (70). The most common primary support area was Food. Preliminary results from students' surveys showed a positive impact in their skills to collaboratively address social needs. KEY LESSONS FOR DISSEMINATION: It was feasible to develop and implement an interdisciplinary social needs outreach workforce to support patients with COVID-19. Food was the most important driver of social need among BUMC patients. Our partnership with the City of Boston was key to effective assistance with food delivery, showing the importance of collaborative partnerships when developing outreach efforts to support patients with social needs. Finally, interdisciplinary outreach opportunities like the CC can be used to teach health professional students about the different scopes of practice and how to effectively collaborate with other disciplines when addressing patient health related social needs.

Application of Affective Computing in the Analysis of Emotions of Educational Content for the Prevention of COVID-19

Affective computing is an emerging research area focused on the development of devices and systems that have the ability to recognize, interpret, process and simulate human emotions in order to improve a user's experience when interacting with a software system. One of the possible fields of application of the techniques provided by affective computing is in the design and generation of multimedia content in the context of formal and non-formal education, which can generate greater interest in students through the transmission of different emotions throughout this content. Based on the above, in this article, an analysis of emotions is carried out on a set of content provided by the Ministry of Health of Colombia as a measure for the prevention and mitigation of contagion by COVID-19. For the development of the study, a tool has been built in the Java language, which allows the segmentation of the audio fragments of the multimedia content, as well as the extraction of the acoustic parameters of arousal and valence, and the application of clustering models on the set of properties extracted from the segments. Copyright © 2022 Praise Worthy Prize S.r.l.-All rights reserved. © 2022 Praise Worthy Prize S.r.l.-All rights reserved.

AN OPERATIONS MANAGEMENT APPROACH TO A CRITICAL ENDOSCOPIC BACKLOG

Background: The COVID-19 pandemic introduced unprecedented disruptions to healthcare delivery, particularly for ambulatory services such as gastrointestinal endoscopy. At the peak of the pandemic in our region between December 2020 to February 2021, ambulatory endoscopy services were suspended at the Los Angeles County + University of Southern California Medical Center (LAC+USC). While endoscopy services resumed in March 2021, the operational challenges introduced by COVID-19 led to a mounting backlog of patients awaiting endoscopic procedures reaching 1,035 by June 2021. As part of our solution to this crisis, we used the principles of operations management to perform a process flow analysis to identify inefficiencies and develop targeted interventions to enhance the operational performance of our endoscopy unit. Methods: A time-motion analysis of patient flow through the LAC+USC Endoscopy Unit was used to construct a comprehensive time-tracked flow sheet to track individual patients as they moved through the unit from check-in to discharge on random dates over a 6-week period (Figure 1). Simultaneously, a qualitative stakeholder survey on perceived operational inefficiencies was distributed to all faculty, staff, and fellows in the endoscopy unit. At the end of 6 weeks, collected data were compared to both published benchmarks and stakeholder survey responses, and inefficiencies identified for intervention. Results: Data were collected for 214 procedures (179 moderate sedation, 35 monitored anesthesia care) in the endoscopy unit. When compared to established benchmarks, we found operational delays in 1) check-in to procedure start time, 2) room turnover time, and 3) first-case on-time start percentage (Table 1). Results from the stakeholder survey aligned with these data. Targeted interventions (Table 1) developed by a multi-disciplinary group of faculty, nursing staff, and trainees from both Gastroenterology and Anesthesiology departments were then implemented, including 1) preparation of the first patient of the day in the procedure room, 2) pre-operative clinic visits for all patients designated to require anesthesia during endoscopy, 3) implementation of a brief-operative note and 4) a time study to encourage first-case on-time start. In combination with maneuvers to streamline the pre-procedure process, this resulted in a reduction of the backlog to 430 by November 2021. Conclusion: Granular analysis of data tracking process flow times through the LAC+USC Endoscopy Unit aligned with stakeholder perceptions regarding operational inefficiencies. The combination of objective and subjective data allowed us to rapidly implement targeted interventions to increase the throughput of the endoscopy unit and address the backlog of endoscopy procedures caused by the COVID-19 pandemic. (Figure Presented) (Table Presented)