Permisos Laborales en la Ley Federal de los Trabajadores al Servicio del Estado para el Cumplimiento de Funciones Electorales.

Este trabajo de investigación contiene tablas comparativas.El desarrollo de la presente investigación, se fundamenta en analizar mediante un proceso histórico y legal, el origen, así como la evolución del Derecho del Trabajo Burocrático, la evolución del Servidor Público a través del tiempo, las diferentes formas de relaciones individuales y colectivas de Trabajo, instituyendo la presencia del artículo 123 Constitucional, la razón de su existencia, así mismo la necesidad de las constantes reformas al citado artículo constitucional, derivado del carácter expansivo del Derecho del Trabajo en y las nuevas formas de evolución de las sociedades moderna

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

A novel scale based on biomarkers associated with COVID-19 severity can predict the need for hospitalization and intensive care, as well as enhanced probabilities for mortality

Abstract Prognostic scales may help to optimize the use of hospital resources, which may be of prime interest in the context of a fast spreading pandemics. Nonetheless, such tools are underdeveloped in the context of COVID-19. In the present article we asked whether accurate prognostic scales could be developed to optimize the use of hospital resources. We retrospectively studied 467 files of hospitalized patients after COVID-19. The odds ratios for 16 different biomarkers were calculated, those that were significantly associated were screened by a Pearson’s correlation, and such index was used to establish the mathematical function for each marker. The scales to predict the need for hospitalization, intensive-care requirement and mortality had enhanced sensitivities (0.91 CI 0.87–0.94; 0.96 CI 0.94–0.98; 0.96 CI 0.94–0.98; all with p < 0.0001) and specificities (0.74 CI 0.62–0.83; 0.92 CI 0.87–0.96 and 0.91 CI 0.86–0.94; all with p < 0.0001). Interestingly, when a different population was assayed, these parameters did not change considerably. These results show a novel approach to establish the mathematical function of a marker in the development of highly sensitive prognostic tools, which in this case, may aid in the optimization of hospital resources. An online version of the three algorithms can be found at: http://benepachuca.no-ip.org/covid/index.ph

Tiempo e historia en el teatro del Siglo de Oro

Aprovechar las enseñanzas de la Historia, recurrir al pasado remoto o reciente para mostrar en sus héroes, recreados por el teatro, su dimensión arquetípica y modélica, tales son los propósitos de la dramatización de la materia histórica durante el Siglo de Oro español. La Historia no sólo sirvió de mero marco temporal para ubicar la acción dramática de las piezas en un contexto preciso. Las variaciones, anacronismos evidentes o sincronismos implícitos, a partir dde las fuentes manejadas deben leerse como verdaderas estrategias del dramaturgo. El anclaje histórico de los argumentos, mediante juegos de simetrías y contrastes entre realidad y ficción, enfoca la recepción ideológica de las obras. La poética del tiempo histórico en el teatro se pone al servicio de la emergencia de una conciencia nacional: representar el pasado supone mejor decir y cuestionar el presente. Este libro examina también la estética de la temporalidad que nace de las variaciones cronológicas en las obras contempladas. Las diferentes contribuciones de los autores revelan la distancia tomada por los dramaturgos del Siglo de Oro respecto a la preceptiva clásica. Semejante actitud no exenta de críticas en su época, demuestra la libertad con la que aquellos creadores supieron superar los apremios teóricos de la unidad de tiempo a favor de un dinamismo celebrado en su tiempo por el público heterogéneo y exigente de los corrales

Clinical characterization of data-driven diabetes subgroups in Mexicans using a reproducible machine learning approach

Introduction Previous reports in European populations demonstrated the existence of five data-driven adult-onset diabetes subgroups. Here, we use self-normalizing neural networks (SNNN) to improve reproducibility of these data-driven diabetes subgroups in Mexican cohorts to extend its application to more diverse settings.Research design and methods We trained SNNN and compared it with k-means clustering to classify diabetes subgroups in a multiethnic and representative population-based National Health and Nutrition Examination Survey (NHANES) datasets with all available measures (training sample: NHANES-III, n=1132; validation sample: NHANES 1999–2006, n=626). SNNN models were then applied to four Mexican cohorts (SIGMA-UIEM, n=1521; Metabolic Syndrome cohort, n=6144; ENSANUT 2016, n=614 and CAIPaDi, n=1608) to characterize diabetes subgroups in Mexicans according to treatment response, risk for chronic complications and risk factors for the incidence of each subgroup.Results SNNN yielded four reproducible clinical profiles (obesity related, insulin deficient, insulin resistant, age related) in NHANES and Mexican cohorts even without C-peptide measurements. We observed in a population-based survey a high prevalence of the insulin-deficient form (41.25%, 95% CI 41.02% to 41.48%), followed by obesity-related (33.60%, 95% CI 33.40% to 33.79%), age-related (14.72%, 95% CI 14.63% to 14.82%) and severe insulin-resistant groups. A significant association was found between the SLC16A11 diabetes risk variant and the obesity-related subgroup (OR 1.42, 95% CI 1.10 to 1.83, p=0.008). Among incident cases, we observed a greater incidence of mild obesity-related diabetes (n=149, 45.0%). In a diabetes outpatient clinic cohort, we observed increased 1-year risk (HR 1.59, 95% CI 1.01 to 2.51) and 2-year risk (HR 1.94, 95% CI 1.13 to 3.31) for incident retinopathy in the insulin-deficient group and decreased 2-year diabetic retinopathy risk for the obesity-related subgroup (HR 0.49, 95% CI 0.27 to 0.89).Conclusions Diabetes subgroup phenotypes are reproducible using SNNN; our algorithm is available as web-based tool. Application of these models allowed for better characterization of diabetes subgroups and risk factors in Mexicans that could have clinical applications