RESUMEN
BACKGROUND: To date, there is a lack of standardization and consensus on which outcomes are central to assess the care provided to patients in the last month of life. Therefore, we aimed to conduct a systematic review to identify relevant outcomes to inform the development of a core outcome set for the best care for the dying person. METHODS: We conducted a systematic review of outcomes reported in the scientific literature about the care for the dying person in the last month of life. We searched for peer-reviewed studies published before February 2022 in four electronic databases. To categorise the outcomes, we employed the taxonomy developed by the "Core Outcome Measures in Effectiveness Trials" collaboration. RESULTS: Out of the 2,933 articles retrieved, 619 were included for analyses. The majority of studies (71%) were retrospective and with data extracted from chart reviews (71%). We extracted 1,951 outcomes in total, from which, after deletion of repeated outcomes, we identified 256 unique ones. The most frequently assessed outcomes were those related to medication or therapeutic interventions and those to hospital/healthcare use. Outcomes related to psychosocial wellbeing were rarely assessed. The closer to death, the less frequently the outcomes were studied. CONCLUSIONS: Most outcomes were related to medical interventions or to hospital use. Only a few studies focused on other components of integrated care such as psychosocial aspects. It remains to be defined which of these outcomes are fundamental to achieve the best care for the dying.
Asunto(s)
Evaluación de Resultado en la Atención de Salud , Cuidado Terminal , Humanos , Cuidado Terminal/normas , Cuidados PaliativosRESUMEN
RESUMEN Objetivo Este estudio tiene como primer objetivo: realizar predicciones del curso de la infección en el horizonte temporal desde marzo 18 a abril 18 del 2020, según diferentes medidas de aislamiento aplicadas. Las predicciones incluyen, población total contagiada, mortalidad y necesidad de recursos hospitalarios. Segundo objetivo: modelar la mortalidad y la necesidad de recursos hospitalarios, estratificando por edad el escenario de contagio del 70% de la población. Métodos Para el primer objetivo, nos basamos en el número de casos confirmados en el país hasta marzo 18, 2020 (n=93). Como suposiciones para el modelo, incluimos un índice de contagio R0=2,5 y el índice de casos reales por cada caso confirmado. Para la proporción de pacientes que necesitarían cuidados intensivos u otros cuidados intrahospitalarios, nos basamos en datos aportados por el Imperial College of London. Para el segundo objetivo usamos como tasa de mortalidad por edad, datos aportados por el Instituto Superiore di Sanità en Italia. Resultados Basándonos en los 93 casos reportados al 18 de marzo, si no se aplicase ninguna medida de mitigación, para el 18 de abril el país tendría un total de 613 037 casos. Medidas de mitigación que reduzcan el R0 en un 10%, generan una reducción del 50% del número de casos. Sin embargo, a pesar de reducirse los casos a la mitad, todavía habría un déficit en el número de camas requeridas y sólo uno de cada dos pacientes tendría acceso a dicho recurso. Conclusión En nuestro modelo encontramos que las medidas de mitigación que han sido implementadas hasta la fecha por el gobierno colombiano, se fundamentan en evidencia suficiente para pensar que es posible reducir significativamente el número de casos contagiados y con esto, el número de pacientes que requerirán manejo hospitalario.(AU)
ABSTRACT Introduction First case of COVID-19 in Colombia was diagnosed on March 6th. Two weeks later, cases have rapidly increased, leading the government to establish some mitigation measures. Objectives The first objective is to estimate and model the number of cases, use of hospital resources and mortality by using different R0 scenarios in a 1-month scenario (from March 18 to April 18, 2020), based on the different isolation measures applied. This work also aims to model, without establishing a time horizon, the same outcomes given the assumption that eventually 70% of the population will be infected. Materials and Methods Data on the number of confirmed cases in the country as of March 18, 2020 (n=93) were taken as the basis for the achievement of the first objective. An initial transmission rate of R0= 2.5 and a factor of 27 for undetected infections per each confirmed case were taken as assumptions for the model. The proportion of patients who may need intensive care or other in-hospital care was based on data from the Imperial College of London. On the other hand, an age-specific mortality rate provided by the Instituto Superiore di Sanità in Italy was used for the second objective. Results Based on the 93 cases reported as of March 18, if no mitigation measures were applied, by April 18, the country would have 613 037 cases. Mitigation measures that reduce R0 by 10% generate a 50% reduction in the number of cases. However, despite halving the number of cases, there would still be a shortfall in the number of beds required and only one in two patients would have access to this resource. Conclusion This model found that the mitigation measures implemented to date by the Colombian government and analyzed in this article are based on sufficient evidence and will help to slow the spread of SARS-CoV-2 in Colombia. Although a time horizon of one month was used for this model, it is plausible to believe that, if the current measures are sustained, the mitigation effect will also be sustained over time.(AU)