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Background: Completion of advance directives can help to ensure consistency with people's preferences at the end of life. However, disparities in access to advance care planning is common among Hispanic population and little is known about their end-of life wishes. Although in Mexico, advance directives were legalized in 2008, only 21% of people know about it. Objective(s): To describe end-of-life wishes among patients with advanced cancer planning in a third level hospital in Mexico City. Method(s): We conducted a cross-sectional analysis of advance directives planning from patients with advanced cancer included in a multidisciplinary patient navigator-led supportive care program in Mexico City (Te Acompanamos). Patients with a life expectancy of 6 months or less were invited to complete advance directives (AD). Life expectancy was calculated using the palliative performance scale (PPS). Descriptive statistics were used for this analysis. Result(s): From September 2017 to November 2021, a total of 238 patients were invited to complete AD and 55 (23.1%) completed it, 14.5% in 2017, 29% in 2018, 34.5% in 2019, 9% in 2020 and 12.7% in 2021. The mean age among those who completed AD was 65.8 years (range 38-91), 52.7% were women and 61.8% had gastrointestinal cancer. Fortythree (78.1%) patients stated their wish to die at home, 18.1% to have cardiopulmonary reanimation, 9% invasive mechanical ventilation, 24.4% tube feeding, 90.9% pain medications, 10.9% organ donation, 40% cremation, 38.1% a funeral and 50.9% a death ritual. At median follow up of 5 months (0-39), 43 (78.1%) patients have died, and their endo-of-life wishes were respected in 77.5 % of them concerning the place of death and in 96.7% regarding cardiopulmonary reanimation and invasive mechanical ventilation. Conclusion(s): In our patient navigator-led supportive program approximately a quarter of patients with advanced cancer and a life expectancy of 6 month or less completed AD and end-of-life wishes were respected in a significant proportion of them. Telemedicine methods used to invite patients during COVID-19 pandemic decreased the proportion of AD completion. Although, advanced care planning is associated with improved in quality of care at the end of life, several barriers and disparities exist among Hispanics and strategies to improve their completion are needed.
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Introduction: Activity monitoring is important in the ICU where delirium, sedation, and critical illness are associated with both inactivity and agitation. Staff monitoring of motion and sleep is intermittent and resource intense. Wearable actigraphic devices are poorly tolerated and limited to limb motion. Here we demonstrate continuous AI video monitoring in the ICU to provide alwayson, unobtrusive patient activity monitoring. Methods: We conducted a pilot study of AI video monitoring in the Duke University Hospital Medical Intensive Care Unit. Video carts continuously recorded data on encrypted hard drives. Second-by-second AI analysis generated binary motion “counts” that were summed to generate our patient motion metric: counts per minute (CPM). Scene intelligence from AI object and people detectors provided room environment information. These data streams along with de-identified (blurred) video data were used to generate prototype graphical and visual summaries of patient activity patterns and the hospital room environment. Results: We enrolled 22 patients and collected 2155 hours (116 days) of video. Representative time-series data streams are shown in the Figure (top left). These data were acquired from a 76-year-old with liver failure and an escalating nasal cannula oxygen requirement who was endotracheally intubated on the subsequent day. Note 1) the declining patient activity as the patient deteriorates and 2) the significant bedside activity (high acuity) throughout the day. We developed a prototype “overnight report” that summarizes patient activity and room environment. The Figure (bottom left) shows the overnight report for a 54-year-old post-COVID-19 patient admitted to the MICU for respiratory failure with hypoactive delirium that resolved per CAM-ICU on day 5 of data collection. Notably, our report demonstrates significant overnight movement, possibly consistent with a mixed or hyperactive delirium. To visually summarize patient motion, we generated activity “heat maps” over 10-minute intervals. As a control, we showed that the intubated and sedated liver failure patient generated a still heat map (Figure upper right). Further, we visualized daytime hypoactivity/sleep in the delirious post-COVID patient (Figure lower right), suggesting disrupted circadian rhythm, giving additional context to the negative CAM assessment. Conclusions: We demonstrated the feasibility of AI to monitor patient activity in a quaternary-care MICU. Our method has advantages compared to wearable actigraphic methods for monitoring patient activity, including being unobtrusive and being able to visualize and summarize wholebody motion. The data presented here suggest that such monitoring may be able to provide clinically actionable insights in delirium care and sedation weaning.
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The CEIPA Business School is a Colombian higher education institution, characterized by providing different education models in the country since its inception. For this reason, CEIPA became the first university institution that created and offered virtual programs in the City of Medellín, and today, it has the largest ratio of the number of high-quality virtual programs in the country. From its first steps in virtual education, since 1996, CEIPA recognized the importance of developing together the virtual education and its own pedagogical model based on problem solving, which allow achieving the learning objectives of its students, understanding the educational process as a whole, in which didactics and teaching methodology cannot be separated. This chapter is aimed to show the case study of CEIPA in the transformation of its graduate and postgraduate programs into digital environments, which shows the changes that were necessary to develop in its academic and administrative process to respond to this new education model, which was a pioneer not only in its beginnings but also in times of the COVID-19 pandemic, spotlighting its success and positioning CEIPA as a leading institution in high educational Colombian´s sector. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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The objective of this article is to present a critical assessment of the importance of teaching philosophy in the post-COVID-19 scenario. To achieve this end, the work is based on three fundamental aspects: the first indicates the core elements of the teaching of philosophy, which, according to Gómez (2008), has a series of particular methods and criteria, vital to generate a critical attitude in students and teachers. Secondly, there is the need to adapt philosophy teaching efforts to the goals proposed by the UN (2020) and UNICEF (2020), which include a fairer and more humane social development. Next, the importance of philosophy as a means to guarantee free thought and the development of a culture of respect and tolerance is emphasized, given the advances of the new global society (Romuroso et all., 2021).. The method used is the hermeneutic-documentary. It is concluded on the importance of the teaching of philosophy as a means to guarantee the formation in values such as justice, respect, tolerance and to give continuity to a dignified life after pandemic COVID-19. © 2021, Universidad del Zulia. All rights reserved.
ABSTRACT
Background: The novel coronavirus disease (COVID-19) results in severe illness in a significant proportion of patients, necessitating a way to discern which patients will become critically ill and which will not. In one large case series, 5.0% of patients required an intensive care unit (ICU) and 1.4% died. Several models have been developed to assess decompensating patients. However, research examining their applicability to COVID-19 patients is limited. An accurate predictive model for patients at risk of decompensation is critical for health systems to optimally triage emergencies, care for patients, and allocate resources. Methods: An early warning score (EWS) algorithm created within a large academic medical center, with methodology previously described, was applied to COVID-19 patients admitted to this institution. 122 COVID-19 patients were included. A decompensation event was defined as inpatient mortality or an unanticipated transfer to an ICU from an intermediate medical ward. The EWS was calculated at 12-hour and 24-hour intervals. Results: Of 122 patients admitted with COVID-19, 28 had a decompensation event, yielding an event rate of 23.0%. 8 patients died, 13 transferred to the ICU, and 6 both transferred to the ICU and died. Decompensation within 12 and 24 hours were predicted with areas under the curve (AUC) of 0.850 and 0.817, respectively. Using a three-tiered risk model, use of the customized EWS score for patients identified as high risk of decompensation had a positive predictive value of 44.4% and 11.1% and specificity of 99.3% and 99.6% and 12- and 24-hour intervals. Amongst medium-risk patients, the score had a specificity of 85.0% and 85.4%, respectively. Conclusion: This EWS allows for prediction of decompensation, defined as transfer to an ICU or death, in COVID-19 patients with excellent specificity and a high positive predictive value. Clinically, implementation of this score can help to identify patients before they decompensate in order to triage at time of presentation and allocate step-down beds, ICU beds, and treatments such as remdesivir.