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1.
Service Learning at a Glance ; : 1-160, 2022.
Article in English | Scopus | ID: covidwho-2057218

ABSTRACT

Service Learning at a Glance involves the dissemination of recent findings from empirical research and practical samples of service-learning programs in higher education to better identify the significant drivers of service-learning critical pedagogy. Service-learning is an immersive and experiential learning experience that combines academic course work and community service, underscoring reciprocal learning and sustainable and reflective practices to address community needs, while developing students’ citizenship skills and critical thinking for social justice. While much has been written about service-learning adoption in higher education settings, this book seeks to demonstrate its broad relevance within a multidisciplinary context. Unique about Service Learning at a Glance is that it offers an “international” point of view by including learning experiences and research work from different regions around the world. We believe the comprehensive knowledge offered through this book will advance service-learning research and support the adoption of engaging service-learning experiences and practices in higher education settings, which will be valuable for researchers and practitioners in many national and cultural contexts. Furthermore, we hope that future research will enlarge upon experiences and research provided in this book to continue to build more international service-learning projects across the world. Chapter 1, drawing on Mezirow's transformative learning theory, investigates how intercultural competence is developed as students interact with other cultural groups in a service-learning experience in Spain. Chapter 2 explores through a qualitative research study enactments of service-learning and conceptions of civic engagement within an Irish university in order to understand the cultural and historical contextual influences. Chapter 3, based on the experience of the Latin American Center for Solidarity Service-Learning (CLAYSS), analyzes the development of service-learning in the Latin American continent. Chapter 4 includes a case study from an Austrian perspective and focuses on the extent to which service-learning has become integrated within the policy and practice of German-speaking higher education institutions. Chapter 5 includes a case study in a Philippine institution of Catholic higher education which examines the reforms undertaken to institutionalize service learning based on Kotter's theory of organizational change. Chapter 6 examines the COVID-19 pandemic setting which has overturned the traditional model of in-person service-learning and, using course evaluation qualitative data, argues that students reflect changes in environmental behavior and greater understanding of environmental issues. Chapter 7 documents the experience of an Indian higher education institution regarding emerging trends of techno-pedagogical innovations which could be instrumental for service learning in Remote Teaching-Learning format. Ultimately, the book aims to provide an in-depth perspective of service-learning, which is supported by empirical evidence and practical teaching experiences in different international settings. The overall aim is to offer a unique and appealing insight to service-learning pedagogy. The book does not require successive reading as each chapter can be extracted independently and can be used both as teaching and learning material. © 2022 by Nova Science Publishers, Inc.

2.
Emergencias ; 34(5):361-368, 2022.
Article in Spanish | Scopus | ID: covidwho-2044827

ABSTRACT

Objective. To characterize phenotypes of prehospital patients with COVID-19 to facilitate early identification of at-risk groups. Methods. Multicenter observational noninterventional study of a retrospective cohort of 3789 patients, analyzing 52 prehospital variables. The main outcomes were 4 clusters of prehospital variables describing the phenotypes. Secondary outcomes were hospitalization, mechanical ventilation, admission to an intensive care unit, and cumulative mortality inside or outside the hospital on days 1, 2, 3, 7, 14, 21, and 28 after hospitalization and after start of prehospital care. Results. We used a principal components multiple correspondence analysis (factor analysis) followed by decomposition into 4 clusters as follows: cluster 1, 1090 patients (28.7%);cluster 2, 1420 (37.4%);cluster 3, 250 (6.6%), and cluster 4, 1029 (27.1%). Cluster 4 was comprised of the oldest patients and had the highest frequencies of residence in group facilities and low arterial oxygen saturation. This group also had the highest mortality (44.8% at 28 days). Cluster 1 was comprised of the youngest patients and had the highest frequencies of smoking, fever, and requirement for mechanical ventilation. This group had the most favorable prognosis and the lowest mortality. Conclusions. Patients with COVID-19 evaluated by emergency medical responders and transferred to hospital emergency departments can be classified into 4 phenotypes with different clinical, therapeutic, and prognostic characteristics. The phenotypes can help health care professionals to quickly assess a patient’s future risk, thus informing clinical decisions. © 2022, Saned. All rights reserved.

3.
15th International Conference of Technology, Learning and Teaching of Electronics, TAEE 2022 ; 2022.
Article in English | Scopus | ID: covidwho-2018996

ABSTRACT

This work shows the development of an open online platform that contains the instructions to build a low-cost humanoid robot. This platform is aimed at all Spanish-speaking educational levels given the lack of information on the development of humanoid robots in this language. The project began at the Tecnologico de Monterrey Campus Morelia with the intention that students of Mechatronics Engineering would replicate an open-source humanoid and thus be able to apply all their knowledge, skills, and competencies in electronics, programming, 3D modeling, and additive manufacturing. Using information from this platform, a robot with a focus on outreach was built that can move its arms and head bidirectionally, as well as its fingers. In addition, a second robot was developed with the aim of acting as a health filter in the Covid-19 pandemic contingency. © 2022 IEEE.

5.
Pediatric Diabetes ; 22(SUPPL 30):33, 2021.
Article in English | EMBASE | ID: covidwho-1571042

ABSTRACT

Introduction: An increase in newly diagnosed type 1 diabetes (T1D) has been posited during the COVID-19 pandemic, but data have been conflicting. Objectives: We aimed to determine trends in newly diagnosed T1D and severity of presentation at diagnosis for pediatric and adolescent patients during COVID-19 year (2020) as compared to the previous year (2019) in a multi-center data analysis across the United States. Methods: This retrospective multi-center study included data from seven large U.S. clinical centers recruited from the T1D Exchange Quality Improvement Collaborative (T1DX-QI). Data on diagnosis, diabetic ketoacidosis (DKA), and clinical characteristics were collected from January 1 to December 31, 2020, compared to the prior year. Chi-square tests were used to compare differences in patient characteristics during the pandemic compared to the pre-pandemic comparison group. Results: Across seven member sites, there were 1399 newly diagnosed patients with T1D in 2020, compared to 1277 in 2019 (p=0.007). Of the newly diagnosed patients, a greater number, presented in DKA in 2020 compared to 2019 (599/1399 (42.8%) v. 493/1277 (38.6%), p<0.001), and a higher proportion of these patients presented with severe DKA (p=0.01) as characterized by a pH<7.1 or bicarbonate of <5mmol/L. The mean age at diagnosis was not different, but there were fewer females (p=0.004), and fewer NH White youth diagnosed in 2020 (p<0.001). Newly diagnosed T1D patients in 2020 were less likely to have private insurance (p=0.001). Monthly data trends demonstrated a higher number of new diagnoses of T1D over the spring and summer months (April to September) of 2020 compared to 2019 (p=0.007). Conclusions: We found an increase in newly diagnosed T1D and a greater proportion of newly diagnosed T1D patients presenting in DKA at diagnosis during the COVID-19 pandemic compared to the prior year. Future longitudinal studies are needed to confirm these findings with population level data and determine the long-term impact of COVID-19 on diabetes trends.

6.
Emergencias ; 33(4):265-272, 2021.
Article in Spanish | Web of Science | ID: covidwho-1498765

ABSTRACT

Objective. To develop and validate a scale to stratify risk of 2-day mortality based on data collected during calls to an emergency dispatch center from patients with suspected coronavirus disease 2019 (COVID-19). Methods. Retrospective multicenter study of consecutive patients over the age of 18 years with suspected COVID-19 who were transported from home over the course of 3 months after telephone interviews with dispatchers. We analyzed clinical and epidemiologic variables and comorbidities in relation to death within 2 days of the call. Using data from the development cohort, we built a risk model by means of logistic regression analysis of categorical variables that were independently associated with 2-day mortality. The scale was validated first in a validation cohort in the same province and then in a cohort in a different province. Results. A total of 2320 patients were included. The mean age was 79 years, and 49.8% were women. The overall 2-day mortality rate was 22.6% (376 deaths of patients with severe acute respiratory syndrome coronavirus 2 infection). The model included the following factors: age, location (rural location as a protective factor), institutionalization, desaturation, lung sounds (rhonchi), and altered mental status. The area under the receiver operating characteristic curve for death within 2 days was 0.763 (95% CI, 0.725-0.802;P < .001). Mortality in patients at high risk (more than 2.4 points on the scale) was 60%. Conclusions. This risk scale derived from information available to an emergency dispatch center is applicable to patients with suspected COVID-19. It can stratify patients by risk of early death (within 2 days), possibly helping with decision making regarding whether to transport from home or what means of transport to use, and destination.

7.
Emergencias ; 33(4):282-291, 2021.
Article in Spanish | Web of Science | ID: covidwho-1498758

ABSTRACT

Objective. To compare the prognostic value of 3 severity scales: the Pneumonia Severity Index (PSI), the CURB-65 pneumonia severity score, and the Severity Community-Acquired Pneumonia (SCAP) score. To build a new predictive model for in-hospital mortality in patients over the age of 75 years admitted with pneumonia due to the coronavirus disease 2019 (COVID-19). Methods. Retrospective study of patients older than 75 years admitted from the emergency department for COVID-19 pneumonia between March 12 and April 27, 2020. We recorded demographic (age, sex, living in a care facility or not), clinical (symptoms, comorbidities, Charlson Comorbidity Index [CCI]), and analytical (serum biochemistry, blood gases, blood count, and coagulation factors) variables. A risk model was constructed, and the ability of the 3 scales to predict all-cause in-hospital mortality was compared. Results. We included 186 patients with a median age of 85 years (interquartile range, 80-89 years);44.1% were men. Mortality was 47.3%. The areas under the receiver operating characteristic curves (AUCs) were as follows for each tool: PSI, 0.74 (95% CI, 0.64-0.82);CURB-65 score, 0.71 (95% CI, 0.62-0.79);and SCAP score, 0.72 (95% CI, 0.63-0.81). Risk factors included in the model were the presence or absence of symptoms (cough, dyspnea), the CCI, and analytical findings (aspartate aminotransferase, potassium, urea, and lactate dehydrogenase. The AUC for the model was 0.81 (95% CI, 0.73-0.88). Conclusions. This study shows that the predictive power of the PSI for mortality is moderate and perceptibly higher than the CURB-65 and SCAP scores. We propose a new predictive model for mortality that offers significantly better performance than any of the 3 scales compared. However, our model must undergo external validation.

8.
Rev Esp Quimioter ; 33(6): 422-429, 2020 Dec.
Article in Spanish | MEDLINE | ID: covidwho-1390021

ABSTRACT

OBJECTIVE: Since the discovery of the SARS-CoV-2 virus, the polymerase chain reaction technique (RT-PCR) has become the fundamental method for diagnosing the disease in its acute phase. The objective is to describe the demand-based series of RT-PCR determinations received at a Microbiology Service at a third-level reference hospital for a health area for three months spanning from the onset of the epidemic by SARS-CoV-2. METHODS: A retrospective analysis of the total of the RT-PCR requested in the Microbiology Service analyzed from 02/25/2020 to 05/26/2020 (90 days) has been carried out. They have been grouped by epidemiological weeks and by the petitioner service. A descriptive analysis was carried out by age, gender and number of requests for each patient. In the tests carried out, a confidence level of 95% (p <0.05) was considered significant. RESULTS: A total of 27,106 requests was received corresponding to 22,037 patients. Median age 53.7 (RIC 40.9-71.7) years, women: 61.3%. Proportion of patients with any positive RT-PCR: 14%. Of the total requests for RT-PCR, positive 3,710. Week 13 had the highest diagnosis performance (39.0%). The primary care has been the service thar has made the most requests (15,953). Patients with 3 or more RT-PCR: 565, of them, 19 patients had a positive result after previously having a negative one. CONCLUSIONS: Requests have been increasing depending on the evolution of the epidemic. The RT-PCR has a high diagnostic performance in the phases of highest contagiousness and / or transmissibility of the virus.


Subject(s)
COVID-19/diagnosis , Pandemics , Reverse Transcriptase Polymerase Chain Reaction/statistics & numerical data , SARS-CoV-2/isolation & purification , Adolescent , Adult , Aged , Aged, 80 and over , COVID-19/epidemiology , Child , Child, Preschool , Confidence Intervals , Female , Health Services Needs and Demand/statistics & numerical data , Humans , Infant , Infant, Newborn , Male , Middle Aged , Primary Health Care/statistics & numerical data , Retrospective Studies , Spain/epidemiology , Statistics, Nonparametric , Young Adult
9.
Proceedings of the Xxii 2020 Ieee International Autumn Meeting on Power, Electronics and Computing ; 2020.
Article in English | Web of Science | ID: covidwho-1271442

ABSTRACT

The crisis resulting from the COVID-19 pandemic has generated an adverse situation in which thousands of people dies due to the lack of artificial ventilation devices. In this sense, this work presents a proposal for the robust mechatronic design and control of a low-cost non-invasive ventilator, for which rapid prototyping manufacture strategies such as 3D printing and product design are used. In order to guarantee the reliability of the system operation, in this work, a robust control scheme based on super-twisting sliding modes is proposed, which guarantees the trajectory tracking control corresponding to the breathing profiles required by the patients. Experimental and simulation results validate the effectiveness of the proposed prototype design. Nevertheless, the prototype is waiting to be tested and approved for use in health assistance.

10.
Emergencias ; 32(3):160-161, 2020.
Article | WHO COVID | ID: covidwho-142604
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