Riesgo de exposición a la transmisión cruzada de infecciones en una unidad de diálisis: análisis estructural de un modelo epidémico simulado / No disponible

El objeto de este trabajo es analizar la red de transmisión cruzada generada por la propagación de gérmenes capaces de contaminar las máquinas de diálisis. Métodos: La simulación se llevó a cabo en una Unidad de Diálisis con 19 máquinas y 62 pacientes. Se eligió aleatoriamente a un paciente, que se consideró portador de un agente infeccioso susceptible de transmitirse a los demás pacientes, mediante el empleo compartido de una máquina de diálisis. Durante 10 días se registraron parejas de asignación paciente-máquina. Las matrices de co-ocurrencia se procesaron con el programa UCINET 6.1(R) de análisis de redes sociales. Se elaboraron grafos para visualizar las redes de contagio generadas por el encadenamiento de sucesivas exposiciones de máquinas y pacientes y se calcularon las principales medidas de centralidad. Resultados: La simulación permite visualizar una rápida expansión del riesgo de contagio. En 10 días, 87,09% de pacientes podría haberse expuesto a la infección, y 68,42% de máquinas podría haberse contaminado. El hecho de que cada paciente requiera 3 sesiones de diálisis semanales, y de que en cada sesión pueda asignársele una máquina diferente explica la rapidez de la expansión del riesgo a la exposición y la dificultad que encuentran los investigadores para identificar un foco al que atribuir los brotes de seroconversiones en unidades de diálisis estudiados hasta el momento. Conclusiones: Si un germen puede transmitirse de paciente a paciente a través de la contaminación incidental de una máquina de diálisis, la presencia de un paciente infectado en una Unidad de Diálisis genera un riesgo de exposición que se extiende con rapidez entre otros pacientes. Pocos días después de que se dialice un paciente infectado, no podrá descartarse que la mayoría de pacientes se hayan expuesto al contagio, y que la mayoría de las máquinas se hayan expuesto a la contaminación (AU)

Several studies show that cross-transmission of germs among patients under dialysis can occur as a consequence of processes in which the dialysis machine participates. The need of vascular access and lengthy periods of extracorporeal circulation increases the vulnerability to infection from nearby microorganisms. This study is intended to analyze the structural and dynamic features of the cross-transmission network generated by the propagation of germs which are capable of contaminating the hemodialyzers. Methods: The simulation was carried out in a Dialysis Unit equipped with 19 machines for 62 patients. One of these patients was randomly chosen and considered as a carrier of an infectious agent capable of being transmitted to other patients, by means of the shared use of the same dialysis machine. For 10 days, the patient-machine allocation couples were registered. Co-occurrence matrices were elaborated and processed with the program UCINET 6.1(R) for social network analysis. Graphs were designed to visualize the networks of contagion, the centrality measures were calculated and the dynamic performance of the network generated by the chaining of the successive exposures of machines and patients was studied. Results: The simulation let us visualize a rapid expansion of the risk of contagion of patients and contamination of machines. In 10 days, 87,09% of patients could have been exposed to the infection, and 68,42% of the machines could have been contaminated. These figures supposes that 5,4 new patients and 1,3 new machines could be potentially exposed every day. Along the first 5 days, the daily rate of exposure for patients and machines remains relatively low (3 new exposed patients and 1,2 new exposed machines every day). But the speed with witch the risk of contagion spreads, increases drastically in the last 5 days (7,8 new exposed patients every day). The fact that each patient requires at least 3 weekly sessions of dialysis and that a different machine can be allocated to him in each session explains that the risk of exposure can spread in some few days to a lot of patients and machines. It can also explain the difficulties found by the researches in identifying the responsible source of the origin of the sero-conversion outbreaks studied by the moment. Conclusions: If a germ can be transmitted from patient to patient by means of the incidental contamination of a dialysis machine, the appearance of an infected patient in a dialysis unit generates a risk of exposition that spreads quickly among other patients. Few days after an infected patient gets a dialysis session, it cannot be ruled out that most of the patients have been exposed to contagion and most of the machines exposed to contamination (AU)

[Risk of exposure to cross-transmission of infections in a dialysis unit: structural analysis of a simulated epidemic model]. / Riesgo de exposición a la transmisión cruzada de infecciones en una unidad de diálisis: análisis estructural de un modelo epidémico simulado.

UNLABELLED: Several studies show that cross-transmission of germs among patients under dialysis can occur as a consequence of processes in which the dialysis machine participates. The need of vascular access and lengthy periods of extracorporeal circulation increases the vulnerability to infection from nearby microorganisms. This study is intended to analyze the structural and dynamic features of the cross-transmission network generated by the propagation of germs which are capable of contaminating the hemodialyzers. METHODS: The simulation was carried out in a Dialysis Unit equipped with 19 machines for 62 patients. One of these patients was randomly chosen and considered as a carrier of an infectious agent capable of being transmitted to other patients, by means of the shared use of the same dialysis machine. For 10 days, the patient-machine allocation couples were registered. Co-occurrence matrices were elaborated and processed with the program UCINET 6.1 for social network analysis. Graphs were designed to visualize the networks of contagion, the centrality measures were calculated and the dynamic performance of the network generated by the chaining of the successive exposures of machines and patients was studied. RESULTS: The simulation let us visualize a rapid expansion of the risk of contagion of patients and contamination of machines. In 10 days, 87,09% of patients could have been exposed to the infection, and 68,42% of the machines could have been contaminated. These figures supposes that 5,4 new patients and 1,3 new machines could be potentially exposed every day. Along the first 5 days, the daily rate of exposure for patients and machines remains relatively low (3 new exposed patients and 1,2 new exposed machines every day). But the speed with witch the risk of contagion spreads, increases drastically in the last 5 days (7,8 new exposed patients every day). The fact that each patient requires at least 3 weekly sessions of dialysis and that a different machine can be allocated to him in each session explains that the risk of exposure can spread in some few days to a lot of patients and machines. It can also explain the difficulties found by the researches in identifying the responsible source of the origin of the sero-conversion outbreaks studied by the moment. CONCLUSIONS: If a germ can be transmitted from patient to patient by means of the incidental contamination of a dialysis machine, the appearance of an infected patient in a dialysis unit generates a risk of exposition that spreads quickly among other patients. Few days after an infected patient gets a dialysis session, it cannot be ruled out that most of the patients have been exposed to contagion and most of the machines exposed to contamination.