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Research Article Open access CC BY 4.0

Trends in Pseudomonas aeruginosa Antibiotic Resistance: Case Study from a Portuguese Central Hospital

Sónia Gonçalves Pereira, Margarida Marques, João Pereira, Olga Cardoso

Journal of Advances in Medicine and Medical Research · pp. 1–17 · Published 16 Mar 2016

10.9734/BJMMR/2016/23085

Abstract

Aims: P. aeruginosa antibiotic resistance is increasing worldwide, greatly limiting therapeutic options, and is mainly associated to nosocomial infections, relating to high morbidity and mortality outcomes. Frequently updated regional guidelines, supported in statistically valid longitudinal information, are mandatory. Methodology: Resistance to 11 antibiotics used to treat P. aeruginosa infections were surveyed in clinical isolates from a Portuguese central during 10 years (n=3778) using the MicroScan WalkAway system. Statistical analysis (Mann-Whitney tests and regression modeling) were used to determine its time evolution according to origin, specimen samples and hospital wards. Results: Total resistance rates fluctuated between 77.9% (ciprofloxacin), and 28.6% (amikacin and piperacillin with tazobactam). Statistical analysis revealed an increase over time for the majority of the resistance rates according to origin, specimen samples and wards of collection. Several trends were best fitted to positive power or quadratic regression models, predicting even higher overall resistance rates in the near future. Few resistance trends were best fitted to negative models, indicative of a possible decrease in the future, which is positive but reflects the discrepant success of empirical antibiotic prescription regimens in different wards from the same hospital. Conclusion: These results, apart from indicating that the studied hospital can significantly improve its prescription policy, prove the importance of specific and local longitudinal studies of resistance trends over time to further drug prescription strategies. Similar biostatistic analysis should be performed in other hospitals and regarding other pathogens to broaden this awareness, necessary for the improvement of empirical antibiotherapy regimens.

Resistance antibiotics surveillance Pseudomonas aeruginosa biostatistics logistic regression.

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