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《Chinese Journal of Practical Pediatrics》 2007-01
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Building a dynamic surveillance system for the diversity of causative pathogens and antimicrobial resistance from neonatal bacterial infections by using PowerBuilder

GU Rui,YU Jia-lin.Department of Neonatology,Children's Hospital,Chongqing University of Medical Sciences,Chongqing 400014,China  
Objective To create a dynamic surveillance system for implying a real time surveillance of the change of causative pathogens and antimicrobial resistance in neonatal bacterial infections,find out their current patterns and the transition,forecast their short-term trends,build up a foundation for tracking and forecasting in a long-term and grasp the epidemiological features of the patterns and the transition,and provide the information for empirical administration of antimicrobial agents.Methods A total of 2 strains of bacteria were isolated from hospitalized neonates and detected for antimicrobial susceptibility.All data were built up 12 tables of a database with full functions by structured query language(SQL).The surveillance system was programmed by using PowerScript and embedding Statistical Package for the Social Science(SPSS)by object linking and embedding(OLE).Time series data were produced by our system and analyzed by embedded SPSS.Results Between 2000 to 2004,Klebsiella pneumoniae(20.7%),E coli(18.0%)and coagulase-negative staphylococci(CNS)(16.2%)were predominant causative pathogens in neonatal infections in our unit.The proportion of opportunistic pathogens was increasing in total causative pathogens annually.The patterns of causative pathogens were scatteringly distributed and had less and less difference between nosocomial infections and infections acquired outside of hospital(P0.05).The majority of antimicrobial agents had deterioration of susceptibility,especially cephalosporins.Extended spectrum β-lactamase(ESBL)(70.9%)and methicillin-resistant staphylococcus(MRS)(58.0%)were the prominent problem of antimicrobial resistance both gram-negative and gram-positive bacteria.There were no significant changes of total sensitive rates in most antimicrobial agents(P0.05);a lot of changes were slight decreasing,but some antimicrobial agents had increasing susceptibility in last two years.In time series,greater part of antimicrobial agents could be estimated and forecasted well with ordinary precision(MAPE50).Conclusion This system can successfully grasp the dynamic changes of causative pathogens and antimicrobial susceptibility,find out the changes in composition ratio of causative pathogens,find uncommon pathogens caused infections and emerging antimicrobial resistant strains,discover new variation of antimicrobial susceptibility,estimate and forecast future trends of antimicrobial sensitive rates well.
【CateGory Index】: R722.1
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