RESUMEN
The Birmingham Hip Resurfacing procedure (BHR) is metal-on-metal resurfacing procedure for hip arthritis. BHR was associated with low risk of surgical site infection (SSI; 0.6%). In addition to antimicrobials, superficial SSIs were treated with incision and drainage, whereas deep incisional or organ-space SSIs required removal of prosthesis. Infect Control Hosp Epidemiol 2016;1-4.
Asunto(s)
Artroplastia de Reemplazo de Cadera/métodos , Infección Hospitalaria/epidemiología , Infección Hospitalaria/etiología , Infección de la Herida Quirúrgica/epidemiología , Anciano , Profilaxis Antibiótica , Infección Hospitalaria/microbiología , Bases de Datos Factuales , Femenino , Humanos , Masculino , Michigan/epidemiología , Persona de Mediana Edad , Osteoartritis de la Cadera/cirugía , Estudios Retrospectivos , Factores de Riesgo , Infecciones Estafilocócicas/epidemiología , Infecciones Estafilocócicas/etiología , Staphylococcus aureus/aislamiento & purificación , Infección de la Herida Quirúrgica/microbiologíaRESUMEN
OBJECTIVE: To develop an automated method for ventilator-associated condition (VAC) surveillance and to compare its accuracy and efficiency with manual VAC surveillance SETTING: The intensive care units (ICUs) of 4 hospitals METHODS: This study was conducted at Detroit Medical Center, a tertiary care center in metropolitan Detroit. A total of 128 ICU beds in 4 acute care hospitals were included during the study period from August to October 2013. The automated VAC algorithm was implemented and utilized for 1 month by all study hospitals. Simultaneous manual VAC surveillance was conducted by 2 infection preventionists and 1 infection control fellow who were blinded to each another's findings and to the automated VAC algorithm results. The VACs identified by the 2 surveillance processes were compared. RESULTS: During the study period, 110 patients from all the included hospitals were mechanically ventilated and were evaluated for VAC for a total of 992 mechanical ventilation days. The automated VAC algorithm identified 39 VACs with sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of 100%. In comparison, the combined efforts of the IPs and the infection control fellow detected 58.9% of VACs, with 59% sensitivity, 99% specificity, 91% PPV, and 92% NPV. Moreover, the automated VAC algorithm was extremely efficient, requiring only 1 minute to detect VACs over a 1-month period, compared to 60.7 minutes using manual surveillance. CONCLUSIONS: The automated VAC algorithm is efficient and accurate and is ready to be used routinely for VAC surveillance. Furthermore, its implementation can optimize the sensitivity and specificity of VAC identification.