The present database contains information on patient falls in the hospital setting. Data were collected in January 2018 with of describing in-hospital falls reported from 1st January 2012 to 31 December 2017 in a large hospital in the South of Brazil. Learning about the characteristics of these events and establishing a profile may contribute to the design of adequate prevention and improvement strategies that are effective to reduce the risk of falls. This data set encompasses 1.071 in-patients falls characterized by the follow variables: year, date, patient birth, weekday, shift, department/location of the incident, location, severity, presence of companion, age, sex, risk level, medication associated with fall risk, implemented fall prevention protocol, type of injury, reason, restraint prescription, physical therapy prescription.

Este artigo investiga o impacto das tecnologias emergentes como Inteligência Artificial (IA), Learning Management Systems (LMS) e Intelligent tutoring systems (ITS) em contextos educacionais. Esta revisão de escopo busca compreender o quanto e como a IA pode ser integrada e utilizada em plataformas de educação a distância, ferramenta importante na transição para esta forma de se estudar e aprender. Para tanto, é realizado um levantamento das aplicações da IA que possam ter aplicações educacionais e que sejam viáveis de incorporação na plataforma Moodle. O objetivo é estudar o alcance da personalização do ensino em plataformas educacionais que oferecem esta possibilidade e verificar como incorporar estes resultados da pesquisa de IA aplicada à educação. Os resultados indicam que a IA contribui para o aprendizado adaptativo e o feedback em tempo real, permitindo a personalização do ensino de acordo com o desempenho dos alunos, mas ainda apresenta limitações para plataformas educacionais de longo alcance. Os STIs, por sua vez, oferecem experiências personalizadas que apoiam o estudo individual, com feedback imediato. Contudo, a implementação dessas tecnologias enfrenta desafios, como a necessidade de investimentos em infraestrutura tecnológica e preocupações com a privacidade dos dados dos alunos. A conclusão sugere que a integração de tecnologias de IA em ambientes de ensino de massa ainda é restrita e apresenta dificuldades tecnológicas e de formação docente para a sua efetivação.

Background/Objectives: Venous thromboembolism (VTE) is a common and potentially fatal condition in hospitalized patients. Although appropriate risk assessment and prophylaxis reduce VTE events, preventive measures remain underutilized. This study aimed to evaluate the effectiveness of an electronic risk stratification tool within multifaceted interventions for implementing VTE prophylaxis protocols in adult clinical and surgical patients at Hospital Moinhos de Vento, Brazil. Methods: A prospective before-and-after hospital-based study was conducted from 2017 to 2019, including 772 patients admitted to clinical and surgical units for over 48 h. The electronic tool based on the Maynard risk assessment model classified patients’ VTE risk. Padua and Caprini scores served as reference standards for clinical and surgical patients, respectively. Prophylaxis was considered adequate if it complied with institutional protocols. Results: Globally, the Maynard model classified 0.9% as low risk, 76.4% intermediate, and 22.7% high risk, differing notably in orthopedic surgical patients. Overall prophylaxis adequacy was 69.3%, with no significant difference between phases. Orthopedic surgical patients showed a significant decrease in prophylaxis adequacy in phase 2 (p = 0.02). Conclusions: The Maynard model underestimated high-risk classification compared to Padua and Caprini scores, especially in orthopedic surgical patients. Implementation of the electronic tool alongside multifaceted interventions did not improve prophylaxis adequacy.

Objective: To analyze the temporal trend, hospital mortality, and cost of hospitalizations for Acute Myocardial Infarction (AMI) and Heart Failure (HF) in Brazil from 2001 to 2021. Methodology: Ecological study based on secondary data from DATASUS, including hospitalizations for AMI and HF among individuals aged ≥15 years. Percentage changes and temporal trends in hospitalization, mortality, and hospital costs were calculated. Results: AMI hospitalizations increased by approximately 326.66% (R² = 0.975; p<0.001), while HF hospitalizations decreased by more than 40% (R² = 0.957; p<0.001). Mortality from AMI decreased (p<0.001; R² = 0.652), whereas mortality from HF increased (p<0.001; R² = 0.961). The mean hospitalization cost was R$ 3,774.79 for AMI and R$ 1,845.05 for HF. Conclusion: The observed variations in hospitalization, mortality, and cost trends reflect changes in risk factors and health care practices, emphasizing the need for continuous surveillance and public policies aimed at reducing morbidity, mortality, and economic burden associated with cardiovascular diseases.