Skip to main content Skip to main navigation menu Skip to site footer

The surveillance of antibiotics resistance in Indonesia: a current reports

  • Andaru Dahesihdewi ,
  • Adhi Kristianto Sugianli ,
  • Ida Parwati ,

Abstract

Background. Antimicrobial resistance (AMR) has become serious problem globally. Surveillance AMR is important to be part of quality indicator in antimicrobial stewardship program (ASP).

Method. Surveillance of microbial pattern and their antibiotics susceptibility in Indonesia 2017 were developed by Indonesian Association of Clinical Pathology and Laboratory Medicine. Data aggregation was sourced from 31 hospitals antibiogram report which were joined the system of national data collection in forlabinfeksi.or.id. with standardized inclusion criteria. Data was analyzed descriptively, based on hospital type-A-B-C.    

Result. There were 15.302 isolates included, 4.761 (31,1%) were positive Gram and 10.541 (68,9%) were negative Gram, 61,6% reported by type-A hospital, 16,4% by type-B and 22% by type-C. Positive and negative Gram patterns respectively were E. faecalis and E.coli  (blood and urine), Streptococcus spp and K. pneumoniae (sputum), S. aureus and E.coli (pus), E. faecalis and E.coli  (wound), coagulase negative Staphylococcus and Enterobacteriaceae (CSF). Antibiotic susceptibility pattern was slightly different among various types of hospital and among various clinical specimens. Positive Gram bacteria had good vancomycin susceptibility in all hospital types, except in sputum from Type-A and B hospital, also in blood and urine from Type-C hospital, similarly with linezolide susceptibility. Susceptibility pattern among Gram negative- bacteria for carbapenem and amikacin was good, in all hospital types, except on A. baumannii.  For A. baumannii, antibiotic carbapenem, amikacin and ceftazidime susceptibility were 20-66%, 35-80%, and up to 83%, respectively. For P. aeruginosa, antibiotic susceptibility pattern was equal among all hospital types. Their susceptibility against cephalosporin (ceftazidime), fluoroquinolone (ciprofloxacin) and aminoglycoside (amikacin) were better in higher type-hospital.

Conclusion. This result may become part of national epidemiological data for ASP program evaluation. This data may also be referred for local empirical antibiotic guideline among limited resources appropriate hospital. There will be improvement forward for more representative beneficial data.

References

  1. Akova M. Epidemiology of antimicrobial resistance in bloodstream infections. Virulence. 2016 Apr; 7(3): 252–266.
  2. World Health Organization Antimicrobial resistance: global report on surveillance 2014. Geneva, Switzerland: WHO; 2014.
  3. Kakkar M, Chatterjee P, Chauhan AS, Grace D, Lindahl J, Beeche A et al. Antimicrobial resistance in South East Asia: time to ask the rightquestions. Glob Health Action. 2018;11(1):1483637
  4. Dahesihdewi A, Sugianli AK, Parwati I, et al. Surveilans Pola Mikroba dan Kepekaannya terhadap Antibiotik Berdasarkan Tipe Rumah Sakit di Indonesia Tahun 2017, Perhimpunan Dokter Spesialis Patologi Klinik dan Kedokteran Laboratorium Indonesia. 2018
  5. Komite Pengendalian Resistensi Antimikroba. Modul Workshop Implementasi PPRA di Rumah Sakit, edisi-3. Direktorat Jenderal Pelayanan Kesehatan Kementerian Kesehatan RI. 2016
  6. World Health Organization. Global Action Plan on Antimicrobial Resistance, 2015
  7. Kohlmann R, Gatermann SG. Analysis and Presentation of Cumulative Antimicrobial Susceptibility Test Data – The Influence of Different Parameters in a Routine Clinical Microbiology Laboratory. PLoS One. 2016; 11(1): e0147965
  8. Ministry of Health. National Action Plan on Antimicrobial Resistance Indonesia. Jakarta: Ministry of Health. 2017. Available from: http://www.kemenkes.or.id
  9. WHO. Guide for establishing laboratory-based surveillance for antimicrobial resistance. Brazzaville, Congo: WHO Regional Office for Africa; 2013
  10. WHO. Laboratory-based surveillance of antimicrobial resistance: Report of a biregional workshp Chennai, India, New Delhi, KIndia. 2011
  11. Grundmann H, Klugman KP, Walsh T, Ramon-Pardo P, Sigauque B, Khan W, et al. A framework for global surveillance of antibiotic resistance. Drug Resist Update. 2011; 14(2):79-87
  12. Clinical and Laboratory Standard Institute (CLSI). Performance standards for antimicrobial susceptibility testing; Twenty-sixth informational supplement. CLSI document M100-S26. Wayne,PA: Clinical and Laboratory Standards Institute. 2016

How to Cite

Dahesihdewi, A., Sugianli, A. K., & Parwati, I. (2019). The surveillance of antibiotics resistance in Indonesia: a current reports. Bali Medical Journal, 8(2), 565–570. https://doi.org/10.15562/bmj.v8i2.1386

HTML
2

Total
5

Share

Search Panel

Andaru Dahesihdewi
Google Scholar
Pubmed
BMJ Journal


Adhi Kristianto Sugianli
Google Scholar
Pubmed
BMJ Journal


Ida Parwati
Google Scholar
Pubmed
BMJ Journal