A avaliação do estudante, que constitui parte essencial da sua educação, sobretudo nas profissões da saúde, vem sofrendo grandes avanços nos seus conceitos fundamentais e, sobretudo, na sua prática cotidiana. Boa parte dessas mudanças relaciona-se à crescente utilização de estratégias de ensino e aprendizagem mediadas pela tecnologia da informação e comunicação (educação à distância ou ensino remoto), que foi, mais recentemente, acelerada pela pandemia do COVID-19. Deve ser também destacado que parte dessas mudanças implicou em maior reconhecimento da grande efetividade da avaliação formativa, desenvolvida, sobretudo, por meio da prática da devolutiva (feedback) frequente e de boa qualidade, seguindo recomendações técnicas adequadas. Neste artigo, apresentam-se alguns conceitos básicos de avaliação educacional e da avaliação do estudante, discute-se o papel estratégico da avaliação formativa e o poder da devolutiva (feedback), descrevem-se algumas das características da devolutiva efetiva e as correspondentes recomendações para a sua prática e descreve-se brevemente um conjunto de sugestões sobre possíveis maneiras efetivas de praticar a avaliação do estudante na educação remota e à distância, com ênfase na finalidade formativa, mas sem desconsiderar a somativa, que implica na tomada de decisões como aprovação ou reprovação.
Objectives: To describe the process of implementing a palliative care team (PCT) in a Brazilian public tertiary university hospital and compare this intervention as an active in-hospital search (strategy I) with the Emergency Department (strategy II). Methods:We described the development of a complex Palliative Care Team (PCT). We evaluated the following primary outcomes: hospital discharge, death (in-hospital and follow-up mortality) or transfer, and performance outcomes-Perception Index (difference in days between hospitalization and the evaluation by the PTC), follow-up index (difference in days between the PTC evaluation and the primary outcome), and the in-hospital stay. Results:We included 1203 patients-strategy I (587; 48.8%) and strategy II (616; 51.2%). In both strategies, male and elderly patients were prevalent. Most came from internal medicine I (39.3%) and II (57.9%), p < 0.01. General clinical conditions (40%) and Oncology I (27.7%) and II (32.4%) represented the majority of the population. Over 70% of all patients had PPS 10 and ECOG 4 above 85%. There was a reduction of patients identified in ICU from I (20.9%) to II (9.2%), p < 0.01, reduction in the ward from I (60.8%) to II (42.5%), p < 0.01 and a significant increase from I (18.2%) to II (48.2%) in the emergency department, p < 0.01. Regarding in-hospital mortality, 50% of patients remained alive within 35 days of hospitalization (strategy I), while for strategy II, 50% were alive within 20 days of hospitalization (p < 0.01). As for post-discharge mortality, in strategy II, 50% of patients died 10 days after hospital discharge, while in strategy I, this number was 40 days (p < 0.01). In the Cox multivariate regression model, adjusting for possible confounding factors, strategy II increased 30% the chance of death. The perception index decreased from 10.9 days to 9.1 days, there was no change in follow-up (12 days), and the duration of in-hospital stay dropped from 24.3 to 20.7 days, p < 0.01. The primary demand was the definition of prognosis (56.7%). Conclusion:The present work showed that early intervention by an elaborate and complex PCT in the ED was associated with a faster perception of the need for palliative care and influenced a reduction in the length of hospital stay in a very dependent and compromised old population.
Objectives: To describe the process of implementing a palliative care team (PCT) in a Brazilian public tertiary university hospital and compare this intervention as an active in-hospital search (Strategy I) with the Emergency Department (Strategy II). Methods: We described the development of a complex Palliative Care Team (PCT). We evaluated the following primary outcomes - hospital discharge, death (in-hospital and follow-up mortality) or transfer - and performance outcomes - Perception Index (difference in days between hospitalization and the evaluation by the PTC), follow-up index (difference in days between the PTC evaluation and the primary outcome), and the in-hospital stay. Results: We included 1203 patients - Strategy I (587; 48.8%) and Strategy II (616; 51.2%). In both Strategies, male and elderly patients were prevalent. Most came from internal medicine I (39.3%) and II (57.9%) - p<0.01. General clinical conditions (40%) and Oncology - I (27.7%) and II (32.4%) - represented the majority of the population. Over 70% of all patients had PPS 10 and ECOG 4 above 85%. There was a reduction of patients identified in ICU from I (20.9%) to II (9.2%) - p <0.01, reduction in the ward from I (60.8%) to II (42.5%) - p <0.01 - and a significant increase from I (18.2%) to II (48.2%) in the emergency department - p <0.01. Regarding in-hospital mortality, 50% of patients remained alive within 35 days of hospitalization (Strategy I), while for Strategy II, 50% were alive within 20 days of hospitalization (p<0 .01). As for post-discharge mortality, in Strategy II, 50% of patients died ten days after hospital discharge, while in Strategy I, this number was 40 days (p<0.01). In the Cox multivariate regression model, adjusting for possible confounding factors, Strategy II increased 30% the chance of death. The perception index decreased from 10.9 days to 9.1 days, there was no change in follow-up (12 days), and the duration of in-hospital stay dropped from 24.3 to 20.7 days - p <0.01. The primary demand was the definition of prognosis (56.7%). Conclusion: The present work showed that early intervention by an elaborate and complex PCT in the ED was associated with a faster perception of the need for palliative care and influenced a reduction in the length of hospital stay in a very dependent and compromised old population.
Introduction: Failure to accurately estimate energy requirements may result in an impaired recovery. Overfeeding has been associated with increased carbon dioxide production, respiratory failure, hyperglycemia and fat deposits in the liver, while underfeeding can lead to malnutrition, muscle weakness and impaired immunity. Objective: This study aimed to determine the metabolic profile of infant and preschool children submitted to mechanical ventilation in the ICU. Methods: A prospective study was carried out in a pediatric ICU in Rio de Janeiro that included children aged from 1 month to 6 years submitted to mechanical ventilation from June 2013 to May 2015. Indirect calorimetry was used to obtain resting energy expenditure (REE) and oxygen consumption (VO 2) in the first 48 hours of admission. The predicted basal metabolic rate (PBMR) was calculated using the Schofield equation. The metabolic state of each patient was assigned as hypermetabolic (REE/PBMR >110%), hypometabolic (REE/PBMR <90%) or normal (REE/PBMR 90-110%). The ratio of caloric intake to REE was also calculated and ratios of >1.5 and <0.5 were classified as overfeeding and underfeeding respectively. Results: A total of 35 infants and 17 preschool children were included. The male/female ratio was 34/18. In respect of severity of sepsis, 19 patients had septic shock, 24 had sepsis, five had severe sepsis and four had systemic inflammatory response syndrome. We observed a high incidence of hypometabolism (88.5%) and a low incidence of normal metabolism (7.7%) and hypermetabolism (3.8%). A low value of VO 2 was observed in 46.1% of the patients (VO 2 ≤120 ml/minute/m 2), a normal value in 40.4% (VO 2 >120 to ≤160 ml/minute/m 2) and a high value in only 13.5% of the patients (VO 2 > 160 ml/minute/m 2). Among the 52 included patients, 18 were fasting at the moment of the examination. The ratio of caloric intake to REE for the remaining 34 patients showed 38.2% overfeeding, 11.8% underfeeding and 50.0% normal feeding. Conclusion: Predictive equations do not accurately predict REE in critically ill infants and preschool children, resulting in inadequate feeding. Although hypermetabolism and enhanced energy expenditure are the main clinical features of critical illness in adults, the majority of our patients were found to be hypometabolic which reinforces the need for a different approach between adult and pediatric critically ill patients.
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