1 Hospital General Universitario de Elche, S. de Microbiología, 03203-Elche-Alicante; 2 Hospital Vega Baja, S. Medicina Preventiva, Orihuela; 3 Universidad Miguel Hernandez, Spain
Received 5 February 2003; returned 2 April 2003; revised 23 April 2003; accepted 23 April 2003
![]() |
Abstract |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
Keywords: Pseudomonas aeruginosa, Acinetobacter baumannii, Staphylococcus aureus
![]() |
Introduction |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
![]() |
Materials and methods |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
Pseudomonas aeruginosa, Staphylococcus aureus and Acinetobacter baumannii.
Period studied
Clinical isolates from the University General Hospital of Elche (450 beds), covering a population of 250 000 inhabitants, on the Mediterranean coast in the Southeast of Spain, between 1 January 2000 and 31 December 2001.
Criteria applied
(i) Elimination of repeats by time. We calculated the effect on susceptibility frequencies of eliminating isolates obtained from the same patient in an interval of time of less or equal to 0, 7, 15, 21 and 30 days. For this calculation we used the Viresist software program, which uses the time series methodology (ARIMA models) to calculate the evolution of microbial susceptibility by analysing the monthly data on susceptibility, antibiotic consumption and hospital stays.2
(ii) Elimination of repeats by variation in antibiotic susceptibility. We calculated the effect on susceptibility frequencies of using the Wider system (Soria Melguizo, Spain), which is a microdilution system with lyophilized antibiotics, semi-automatic interpretation and ATCC strains for quality control. We eliminated isolates from the same patient that, irrespective of the time elapsed between isolations, had the same antibiogram against a group of important antibiotics selected specifically for each microorganism.3
Antibiotics selected
The following groups of antibiotics were selected. S. aureus: oxacillin, erythromycin, ciprofloxacin, fosfomycin, rifampicin, trimethoprim/sulfamethoxazole and vancomycin; P. aeruginosa: ceftazidime, cefepime, piperacillin/tazobactam, imipenem, ciprofloxacin and tobramycin; A. baumannii: ceftazidime, cefepime, piperacillin/tazobactam, imipenem, ciprofloxacin, tobramycin and ampicillin/sulbactam.
![]() |
Results |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
The relationship between the number of isolates and number of patients is shown in Table 1. It can be seen that the distribution for the three microorganisms is very similar.
|
|
Variation in the percentages of antibiotic susceptibility
(i) Elimination of repeats by time. When the period of time for eliminating isolates is increased, the percentage of susceptible strains also increases. This indicates that there are many more isolates when the patient is infected by microorganisms that are resistant to antibiotics. The data are shown in Table 2.
(ii) Elimination of repeats by variation in antibiotic susceptibility. Application of this criterion results in a decrease in the percentage of antibiotic susceptibility, since it detects the microorganisms that acquire resistance during treatment.
![]() |
Discussion |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
If we consider the criterion of time in the elimination of isolates, as the period of time for eliminating isolates from the same patient increases, there is a decrease in the number of isolates and an increase in the percentage of susceptibility, since there is a greater number of samples from patients with resistant microorganisms. This is an objective procedure that is reproducible in different laboratories, but it does not detect changes in antibiotic susceptibility caused by the generation of resistance during antibiotic treatments if they take place over a short period of time.
The criterion of variation in antibiotic susceptibility is more useful to detect changes in the susceptibility of resistant bacteria subjected to multiple antibiotic treatments, but it is less objective and less reproducible owing to methodological errors in determining the antibiotic susceptibility.
Use of these parameters as a complement to molecular biology techniques could be of value in the control of the transmission of resistant strains and detection of outbreaks.8 Although they are difficult to study, specialized systems2,3,5 capable of analysing a large number of data and applying complex statistical methodology have made this task easier, thereby enabling a better understanding of the resistance of the main pathogenic bacteria.9
![]() |
Acknowledgements |
---|
![]() |
Footnotes |
---|
![]() |
References |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
2 . Lopez Lozano, J. M., Monnet, D. L., Yague, A. et al. (2000). Modelling and forecasting antimicrobial resistance and its dynamic relationship to antimicrobial use: a time series analysis. International Journal of Antimicrobial Agents 14, 2131.[CrossRef][ISI][Medline]
3
.
Canton, R., Perez Vazquez, M., Oliver, A. et al. (2000). Evaluation of the Wider system, a new computer-assisted image-processing device for bacterial identification and susceptibility testing. Journal of Clinical Microbiology 38, 133946.
4 . Roberts, S. A., Findlay, R. & Lang, S. D. (2001). Investigation of an outbreak of multi-drug resistant Acinetobacter baumannii in an intensive care burns unit. Journal of Hospital Infection 48, 22832.[CrossRef][ISI][Medline]
5 . Nakano, M., Yasuda, M., Yokoi, S. et al. (2001). In vivo selection of Pseudomonas aeruginosa with decreased susceptibilities to fluoroquinolones during fluoroquinolone treatment of urinary tract infection. Urology 58, 1258.[CrossRef][ISI][Medline]
6
.
Dubois, V., Arpin, C., Melon, M. et al. (2001). Nosocomial outbreak due to a multiresistant strain of Pseudomonas aeruginosa P12: efficacy of cefepimeamikacin therapy and analysis of beta-lactam resistance. Journal of Clinical Microbiology 39, 20728.
7 . Blahova, J., Kralikova, K., Krcmery, V. et al. (2001). Transferable antibiotic resistance in multiresistant nosocomial Acinetobacter baumannii strains from seven clinics in the Slovak and Czech Republics. Journal of Chemotherapy 13, 1437.[ISI][Medline]
8 . Pfaller, M. A., Acar, J., Jones, R. N. et al. (2001). Integration of molecular characterization of microorganisms in a global antimicrobial resistance surveillance program. Clinical Infectious Diseases 32, S15667.[CrossRef][ISI][Medline]
9
.
Tenover, F. C., Mohammed, M. J., Stelling, J. et al. (2001). Ability of laboratories to detect emerging antimicrobial resistance: proficiency testing and quality control results from the World Health Organizations external quality assurance system for antimicrobial susceptibility testing. Journal of Clinical Microbiology 39, 24150.