To support the global restart of elective surgery, data from an international prospective cohort study of 8492 patients (69 countries) was analysed using artificial intelligence (machine learning techniques) to develop a predictive score for mortality in surgical patients with SARS-CoV-2. We found that patient rather than operation factors were the best predictors and used these to create the COVIDsurg Mortality Score (https://covidsurgrisk.app). Our data demonstrates that it is safe to restart a wide range of surgical services for selected patients.
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El conocimiento, la ciencia y la información tienen una relación de interdependencia. Como su convergencia no cesa de producir cambios sustanciales en la historia de la humanidad, es de esperarse que la manera de concebirlos nunca haya sido estática. Por su parte, estas concepciones, que son fenómenos vivos, dinámicos e intangibles, erigen nuevas formas de ver y habitar el mundo. La información es un concepto revolucionario porque: primero, encierra los conceptos de masa y energía; segundo, tiene la capacidad para controlar diversas facetas de la humanidad, tales como: las elecciones, las decisiones de los consumidores, la balanza del mercado, etc. En la actualidad, el mundo está invadido por un enorme volumen de datos, que no deja de aumentar de manera exponencial todos los días y, por esto, es menesteroso que los usuarios desarrollen un pensamiento crítico en lo tocante con su tratamiento, su uso y el grado de representatividad que puede llegar a tener en distintos ámbitos.
Objective: To evaluate the association between the availability of GeneXpert ® MTB/RIF in municipalities and the proportion of people who have access to this diagnostic technology for tuberculosis (TB), as well as the resistance detected by the surveillance system in Brazil. Methods: We analyzed 4,998 Brazilian municipalities that reported 432,937 new TB cases between 2015 and 2020. We compared municipalities with and without the availability of GeneXpert ® MTB/RIF regarding the prevalence of effective access to GeneXpert ®MTB/RIF diagnosis and that of detected resistance. Results: Municipalities with at least one GeneXpert ®MTB/RIF system had three times (95%CI 2.9-3.0) the access to diagnostic tests and 80.4% (95%CI 70.6%-90.2%) higher detection of resistance, compared to municipalities without this technology. We estimate that there have been 2,110 cases of undetected resistance during this period in the country. Conclusions: The availability of GeneXpert ® MTB/RIF system in the municipality increased the sensitivity of the surveillance for detecting TB resistance. Public Health implications. It is a priority to strengthen laboratory networks and narrow the gap in access to rapid diagnosis in remote areas to improve the detection and control of drug-resistant tuberculosis. Keywords: GeneXpert MTB/RIF, tuberculosis, drug resistance, rapid diagnosis, access.
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