Journals / Journal of Health Sciences and Medicine / 2022 / Cilt: 5 - Sayı: 2

Comparison of respiratory tract pathogens and antibiotic susceptibility profiles of patients diagnosed with COVID-19 with pre-COVID-19

Pages
510–516
Publication Date
2022-03-15
DOI
—
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

It was determined that P. aeruginosa and A. baumannii, which were the most common isolates before the pandemic and showed high resistance rates against all antibiotic groups, were the most common bacteria during the pandemic period.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Objective: It is aimed to compare the respiratory tract agents and antibiotic resistance rates in patients with a diagnosis of COVID-19 with the non-COVID-19 period.
📊
Key Findings & Data:Material and Method: Patients diagnosed with bacterial respiratory tract infection between March 2019 and March 2021 were included in the study.
💡
Conclusion & Impact:It was determined that P. aeruginosa and A. baumannii, which were the most common isolates before the pandemic and showed high resistance rates against all antibiotic groups, were the most common bacteria during the pandemic period.
🔬Design:Research Article
📍Scope:2019 Verileri
⚙️Variables:Antibiotic Susceptibility · respiratory infection · respiratory infection

Abstract

Objective: It is aimed to compare the respiratory tract agents and antibiotic resistance rates in patients with a diagnosis of COVID-19 with the non-COVID-19 period. Material and Method: Patients diagnosed with bacterial respiratory tract infection between March 2019 and March 2021 were included in the study. Bacteria identification and antibiotic susceptibility were evaluated according to automated system and EUCAST standards. Results: Between March 2019-March 2020 (before the pandemic), the most common bacterium was Pseudomonas aeruginosa (P. aeruginosa) 280 (15.5%) second Acinetobacter baumannii (A. baumannii) in a total of 1797 patients hospitalized in the service and intensive care units, and the resistance rates were the same. Between March 2020 and 2021, a total of 1357 COVID -19 patients were found in clinical and intensive care units, and the most common reproducing agent was A. baumannii 168 (12.3%), the second P. aeruginosa 164, and resistance rates were found to invrease. Conclusion: The increase in the resistance rates of bacteria causing respiratory tract infection was remarkable. It was determined that P. aeruginosa and A. baumannii, which were the most common isolates before the pandemic and showed high resistance rates against all antibiotic groups, were the most common bacteria during the pandemic period.

🔖

Cite This Article

ŞENOL, F. F., BAHÇECİ, İ., ARSLAN, N., AYTAÇ, Ö., ÖNER, P., TORAMAN, Z. A. (2022). Comparison of respiratory tract pathogens and antibiotic susceptibility profiles of patients diagnosed with COVID-19 with pre-COVID-19. Journal of Health Sciences and Medicine, Cilt: 5 - Sayı: 2, 510–516. https://ajindex.com/articles/776600

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (10)

  1. Klein EY, Monteforte B, Gupta A, et al. The frequency of influenza and bacterial coinfection: a systematic review and meta-analysis. Influenza Other Respir Viruses 2016; 10: 394–403.
  2. Zhu N, Zhang D, Wang W, et al. A novel coronavirus from patients with pneumonia in China, 2019. N Engl J Med 2020; 382: 727-33.
  3. Cao Y, Liu X, Xiong L, Cai K. Imaging and clinical features of patients with 2019 novel coronavirus SARS-CoV-2: A systematic review and meta-analysis. J Med Virol 2020; 10.1002/jmv.25822. Guan WJ, Ni ZY, Hu Y, et al. Clinical characteristics of 2019 novel coronavirus infection in China. N Engl J Med 2020; 382: 1708-20.
  4. Li Z, Yi Y, Luo X, et al. Development and clinical application of a rapid IgM-IgG combined antibody test for SARS-CoV-2 infection diagnosis. J Med Virol 2020; 92: 1518-24.
  5. Claeys KC, Zasowski EJ, Trinh TD, Lagnf AM, Davis SL, Rybak MJ. Antimicrobial stewardship opportunities incritically ill patients with gram-negative lowerrespiratory tract infections: A multicenter crosssectionalanalysis. Infect Dis Ther 2018; 7: 135-46. EUCAST 2019. The European committee on antimicrobial susceptibility testing. Breakpoint tables for interpretation of MICs and zone diameters. Version 9.0, 2019. http: //www.eucast.org. Rothan HA, Byrareddy SN. The epidemiology and pathogenesis of coronavirus disease (COVID-19) outbreak. J Autoimmun 2020; 109: 102433. Team NCPERE. Vital surveillances: The epidemiological characteristics of an outbreak of 2019 novel coronavirus diseases (COVID-19) - China. China CDC Weekly 2020; 2: 113-22.
  6. Wu Z, McGoogan JM. Characteristics of and important lessons from the coronavirus disease 2019 (COVID-19) outbreak in China: summary of a report of 72 314 cases from the Chinese Center for Disease Control and Prevention. Jama 2020; 323: 1239-42.
  7. Zhou F, Yu T, Du R, et al. Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study. Lancet 2020; 395: 1054-62.
  8. Zhao Q, Meng M, Kumar R, et al. The impact of COPD and smoking history on the severity of COVID-19: a systemic review and meta-analysis. J Med Virol 2020; 92: 1915-21. Bahceci I. Distribution and antimicrobial susceptibility of Stenotrophomonas maltophilia strains isolated from various clinical specimens: an 8-year study. Dicle Med J 2021; 48: 147-52.
  9. Gedikli MA, Tuzun B, Sayin K, Ataseven H. Determination of inhibitor activity of drugs against the COVID-19. Bratisl Med J 2021; 122: 497-506.
  10. Rusell C, Fairfield C,