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Record W2163322983

Antimicrobial Susceptibility Pattern of Pseudomonas aeruginosa Isolated from Patients Referring to Hospitals

2012· article· en· W2163322983 on OpenAlexaboutno aff
Zeynab Golshani, Ali Mohammad Ahadi, Ali Sharifzadeh

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAntibiotic Resistance in Bacteria
Canadian institutionsnot available
Fundersnot available
KeywordsPseudomonas aeruginosaAntimicrobialMicrobiologyHygieneCross infectionMedicineIntensive care medicineBiologyBacteriaPathologyGenetics
DOInot available

Abstract

fetched live from OpenAlex

Please cite this article as: Golshani Z, Ahadi AM, Sharifzadeh A. Antimicrobial Susceptibility Pattern of Pseudomonas aeruginosa Isolated from Patients Referring to Hospitals. Arch Hyg Sci 2012;1(2):48-53. Abstract: Background & Aims of the Study: The aim of this study was to detect and survey the antibiotic resistance pattern of Pseudomonas (P.) aeruginosa isolated from patients in Isfahan (located in central Iran) hospitals. Materials & Methods : A Total of 50 clinical isolates of P. aeruginosa were collected from urine, wound, trachea, ear swab, and pus, and then were confirmed by standard tests. Antibiotic susceptibility was determined by the Kirby-Bauer disc diffusion method. Susceptibility data were compared by chi-square test using SPSS version 15. Results: Among the isolated strains, resistance to oxacillin was seen in 100%, ceftriaxone in 76%, amikacin in 70%, ceftazidime in 68%, cefepime in 68%, tobramycin in 62%, gentamicin in 60%, ciprofloxacin in 58%, and imipenem in 58% of the isolates. Conclusions: Comparison of the results showed that, patterns of antibiotic resistance are different from one hospital to another in various areas. Therefore, it is suggested that such studies should be performed in different hospitals. Also, prescribing correct medications is essential to prevent further increases in resistant bacteria. References: 1. Pagani L, Mantengoli E, Migliavacca R, Nucleo E, Pollini S, Spalla M, et al. Multifocal Detection of Multidrug-Resistant Pseudomonas aeruginosa Producing the PER-1 Extended- Spectrum β-Lactamase in Northern Italy. J Clin Microbiol 2004;42(6):2523–9. 2. Ling TKW, Xiong J, Yu Y, Lee CC, Ye H, Hawkey PM, et al. Multicenter Antimicrobial Susceptibility Survey of Gram-Negative Bacteria Isolated from Patients with Community-Acquired Infections in the People's Republic of China. Antimicrob Agents Chemother 2006;50(1):374–8. 3. Gupta V, Datta P, Agnihotri N, Chander J. Comparative in vitro Activities of Seven New beta-Lactams, Alone and in Combination with beta-Lactamase Inhibitors, Against Clinical Isolates Resistant to Third Generation Cephalosporins. Braz J Infect Dis 2006;10(1):22-5. 4. Lister PD, Wolter DJ, Hanson ND. Antibacterial-Resistant Pseudomonas aeruginosa : Clinical Impact and Complex Regulation of Chromosomally Encoded Resistance Mechanisms. Clin Microbiol Rev 2009;22(4):582–610. 5. Shahid M, Malik A. Plasmid mediated amikacin resistance in clinical isolates of Pseudomonas aeruginosa . Indian J Med Microbiol 2004;22(3):182-4. 6. Song W, Woo HJ, Kim JS, Lee KM. In vitro activity of beta-lactams in combination with other antimicrobial agents against resistant strains of Pseudomonas aeruginosa . Int J Antimicrobiol Agents 2003;21(1):8-12. 7. Brown PD, Izundu A. Antibiotic resistance in clinical isolates of Pseudomonas aeruginosa in Jamaica. Rev Panam Salud Publica/Pan Am J Public Health 2004;16(2):125-30. 8. Dundar D, Otkun M. In-Vitro Efficacy of Synergistic Antibiotic Combinations in Multidrug Resistant Pseudomonas Aeruginosa Strains. Yonsei Med J 2010;51(1):111-6. 9. Tam VH, Chang KT, Abdelraouf K, Brioso CG, Ameka M, McCaskey LA, et al. Prevalence, Resistance Mechanisms, and Susceptibility of Multidrug-Resistant Bloodstream Isolates of Pseudomonas aeruginosa . Antimicrob Agents Chemother 2010;54(3):1160-4. 10. Mirsalehian A, Feizabadi M, Nakhjavani FA, Jabalameli F, Goli H, Kalantari N. Detection of VEB-1, OXA-10 and PER-1genotypes in extended-spectrum beta-lactamase- producing Pseudomonas aeruginosa strains isolated from burn patients. Burns.2010;36(1):70-4. 11. Patzer JA, Dzierzanowska D. Increase of imipenem resistance among Pseudomonas aeruginosa isolates from a Polish paediatric hospital (1993-2002). Int J Antimicrob Agents 2007;29(2):153-8. 12. Walkty A, Decorby M, Nichol K, Mulvey MR, Hoban D, Zhanel G; Canadian Antimicrobial Resistance Alliance. Antimicrobial susceptibility of Pseudomonas aeruginosa isolates obtained from patients in Canadian intensive care units as part of the Canadian National Intensive Care Unit study. Diagn Microbiol Infect Dis 2008;61(2):217-21. 13. Livermore DM. Of Pseudomonas , porins, pumps and carbapenems. J Antimicrob Chemother 2001;47(3):247-50. 14. Navneeth BV, Sridaran D, Sahay D, Belwadi MR. A preliminary study on metalloβ- lactamase producing Pseudomonas aeruginosa in hospitalized patients. Indian J Med Res 2002;116:26, 4-7. 15. Büscher KH, Cullmann W, Dick W, Opferkuch W. Imipenem resistance in Pseudomonas aeruginosa resulting from diminished expression of an outer membrane protein. Antimicrob Agents Chemother 1987;31(5):703–8. 16. Strateva T, Ouzounova-Raykova V, Markova B, Todorova A, Marteva-Proevska Y, Mitov I. Problematic clinical isolates of Pseudomonas aeruginosa from the university hospitals in Sofia, Bulgaria: current status of antimicrobial resistance and prevailing resistance mechanisms. J Med Microbiol 2007;56(7):956-63. 17. Mohajeri P. Antibiotic susceptibility and resistance patterns of pseudomonas aeruginosa strains isolated from different clinical specimens in patients referred to the teaching hospitals in Kermanshah (2001-2). Behbood Res J Kermanshah Univ Med Sci 2004;7(4):11-20. (Full Text in Persian) 18. Streit JM, Jones RN, Sader HS, Fritsche TR. Assessment of pathogen occurrences and resistance profiles among infected patients in the intensive care unit: report from the Sentry Antimicrobial Surveillance Program (North America, 2001). Int J Antimicrob Agents 2004;24(2):111-8. 19. Shacheraghi F, Shakibaie MR, Noveiri H. Molecular Identification of ESBL Genes blaGES-1, blaVEB-1, blaCTX-M blaOXA-1, blaOXA-4, blaOXA-10 and blaPER-1 in Pseudomonas aeruginosa Strains Isolated from Burn Patients by PCR, RFLP and Sequencing Techniques. Int J Biol life Sci 2010;3(6):138-42. 20. Fazeli H, Moslehi Tekantapeh Z, Irajian GHR, Salehi M. Determination of drug resistance patterns and detection of bla-vim gene in pseudomonas aeruginosa strains isolated from burned patients in the Imam Mosa Kazem Hospital, Esfahan, Iran (2008-9). Iran J Med Microbiol 2010;3(4);1-8. (Full Text in Persian) 21. Rahimi B, Shojapour M, Sadeghi A, Pourbabayi A. The study of the antibiotic resistance pattern of Pseudomonas aeruginosa strains isolated from hospitalized patients in Arak. Arak Univ Med Sci J 2012;15(3):8-14. (Full Text in Persian) 22. Forozesh Fard M, Irajian G, Moslehi Takantape Z, Fazeli H, Salehi M, Rezania S. Drug resistance pattern of Pseudomonas aeruginosa strains isolated from cystic fibrosis patients at Isfahan AL Zahra hospital, Iran (2009-2010). Iran J Microbiol 2012;4(2):94-7. (Full Text in Persian) 23. Rajat Rakesh M, Ninama Govind L, Mistry K, Parmar R, Patel K, Vegad MM, Antibiotic resistance pattern in Pseudomonas aeruginosa species isolated at a tertiary care hospital, Ahmadabad. Natl J Med Res 2012;2(2):156-9.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.081
GPT teacher head0.454
Teacher spread0.373 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations13
Published2012
Admission routes1
Has abstractyes

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