Envejecimiento y Vejez: ejes, estrategias y líneas de acción en la política pública de Manizales

Esta cartilla busca reflejar el esfuerzo conjunto entre la Universidad Autónoma de Manizales y la Alcaldía de Manizales, con miras a la construcción de la política pública. El objetivo de este material es presentar al lector la realidad de nuestro contexto, la importancia de que sea analizada y, sobre todo, de que en el Municipio se diseñen estrategias para su atención. En primer lugar presentaremos una breve conceptualización del significado del envejecimiento, así como un acercamiento al tema de las políticas públicas. En segundo lugar expondremos las conclusiones y los hallazgos del estudio para adentrarnos en la presentación de la política pública municipal. Finalmente agregaremos un apartado con notas de interés para este grupo poblaciona

Política pública de salud mental del departamento de Caldas: un aporte al bienestar y a la inclusión

Esta cartilla es una presentación sencilla del informe de investigación titulado Lineamientos y elementos que debe considerar la Administración Departamental en la consolidación de una política pública en Salud Mental. El estudio del que forma parte es el resultado de la construcción colectiva de los lineamientos de la Política Pública departamental en Salud Mental, con énfasis en la disminución de la oferta y la demanda de sustancias psicoactiva

Clustering COVID-19 ARDS patients through the first days of ICU admission. An analysis of the CIBERESUCICOVID Cohort

Background Acute respiratory distress syndrome (ARDS) can be classified into sub-phenotypes according to different inflammatory/clinical status. Prognostic enrichment was achieved by grouping patients into hypoinflammatory or hyperinflammatory sub-phenotypes, even though the time of analysis may change the classification according to treatment response or disease evolution. We aimed to evaluate when patients can be clustered in more than 1 group, and how they may change the clustering of patients using data of baseline or day 3, and the prognosis of patients according to their evolution by changing or not the cluster.Methods Multicenter, observational prospective, and retrospective study of patients admitted due to ARDS related to COVID-19 infection in Spain. Patients were grouped according to a clustering mixed-type data algorithm (k-prototypes) using continuous and categorical readily available variables at baseline and day 3.Results Of 6205 patients, 3743 (60%) were included in the study. According to silhouette analysis, patients were grouped in two clusters. At baseline, 1402 (37%) patients were included in cluster 1 and 2341(63%) in cluster 2. On day 3, 1557(42%) patients were included in cluster 1 and 2086 (57%) in cluster 2. The patients included in cluster 2 were older and more frequently hypertensive and had a higher prevalence of shock, organ dysfunction, inflammatory biomarkers, and worst respiratory indexes at both time points. The 90-day mortality was higher in cluster 2 at both clustering processes (43.8% [n = 1025] versus 27.3% [n = 383] at baseline, and 49% [n = 1023] versus 20.6% [n = 321] on day 3). Four hundred and fifty-eight (33%) patients clustered in the first group were clustered in the second group on day 3. In contrast, 638 (27%) patients clustered in the second group were clustered in the first group on day 3.Conclusions During the first days, patients can be clustered into two groups and the process of clustering patients may change as they continue to evolve. This means that despite a vast majority of patients remaining in the same cluster, a minority reaching 33% of patients analyzed may be re-categorized into different clusters based on their progress. Such changes can significantly impact their prognosis