Frank van Leth1, Casper den Heijer2,3, Mariëlle Beerepoot4, Ellen Stobberingh2, Suzanne Geerlings4, Constance Schultsz1,5. 1. Department of Global Health, Academic Medical Center, University of Amsterdam, Amsterdam Institute for Global Health & Development, Amsterdam, The Netherlands. 2. Department of Medical Microbiology, Maastricht University, School of Public Health & Primary Care, Maastricht, The Netherlands. 3. Department of Sexual Health, Infectious Diseases & Environmental Health, Public Health Service South Limburg, Geleen, The Netherlands. 4. Department of Internal Medicine, Division of Infectious Diseases, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands. 5. Department of Medical Microbiology, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands.
Abstract
AIM: Increasing antimicrobial resistance (AMR) requires rapid surveillance tools, such as Lot Quality Assurance Sampling (LQAS). MATERIALS & METHODS: LQAS classifies AMR as high or low based on set parameters. We compared classifications with the underlying true AMR prevalence using data on 1335 Escherichia coli isolates from surveys of community-acquired urinary tract infection in women, by assessing operating curves, sensitivity and specificity. RESULTS: Sensitivity and specificity of any set of LQAS parameters was above 99% and between 79 and 90%, respectively. Operating curves showed high concordance of the LQAS classification with true AMR prevalence estimates. CONCLUSION: LQAS-based AMR surveillance is a feasible approach that provides timely and locally relevant estimates, and the necessary information to formulate and evaluate guidelines for empirical treatment.
AIM: Increasing antimicrobial resistance (AMR) requires rapid surveillance tools, such as Lot Quality Assurance Sampling (LQAS). MATERIALS & METHODS: LQAS classifies AMR as high or low based on set parameters. We compared classifications with the underlying true AMR prevalence using data on 1335 Escherichia coli isolates from surveys of community-acquired urinary tract infection in women, by assessing operating curves, sensitivity and specificity. RESULTS: Sensitivity and specificity of any set of LQAS parameters was above 99% and between 79 and 90%, respectively. Operating curves showed high concordance of the LQAS classification with true AMR prevalence estimates. CONCLUSION: LQAS-based AMR surveillance is a feasible approach that provides timely and locally relevant estimates, and the necessary information to formulate and evaluate guidelines for empirical treatment.
Authors: Adhi Kristianto Sugianli; Franciscus Ginting; R Lia Kusumawati; Emmy Hermiyati Pranggono; Ayodhia Pitaloka Pasaribu; Firza Gronthoud; Suzanne Geerlings; Ida Parwati; Menno D De Jong; Frank Van Leth; Constance Schultsz Journal: J Antimicrob Chemother Date: 2017-05-01 Impact factor: 5.790
Authors: Cherry Lim; Elizabeth A Ashley; Raph L Hamers; Paul Turner; Thomas Kesteman; Samuel Akech; Alejandra Corso; Mayfong Mayxay; Iruka N Okeke; Direk Limmathurotsakul; H Rogier van Doorn Journal: Clin Microbiol Infect Date: 2021-06-07 Impact factor: 13.310
Authors: Franciscus Ginting; Adhi Kristianto Sugianli; Gidion Bijl; Restuti Hidayani Saragih; R Lia Kusumawati; Ida Parwati; Menno D de Jong; Constance Schultsz; Frank van Leth Journal: Am J Epidemiol Date: 2019-04-01 Impact factor: 4.897
Authors: Adhi Kristianto Sugianli; Franciscus Ginting; R Lia Kusumawati; Ida Parwati; Menno D de Jong; Frank van Leth; Constance Schultsz Journal: PLoS One Date: 2020-03-30 Impact factor: 3.240