title: Predicting Antimicrobial Resistance Prevalence and Incidence from Indicators of Antimicrobial Use: What Is the Most Accurate Indicator for Surveillance in Intensive Care Units?
abstract: OBJECTIVE
  The optimal way to measure antimicrobial use in hospital populations, as a complement to surveillance of resistance is still unclear. Using respiratory isolates and antimicrobial prescriptions of nine intensive care units (ICUs), this study aimed to identify the indicator of antimicrobial use that predicted prevalence and incidence rates of resistance with the best accuracy.
  
  
  METHODS
  Retrospective cohort study including all patients admitted to three neonatal (NICU), two pediatric (PICU) and four adult ICUs between April 2006 and March 2010. Ten different resistance/antimicrobial use combinations were studied. After adjustment for ICU type, indicators of antimicrobial use were successively tested in regression models, to predict resistance prevalence and incidence rates, per 4-week time period, per ICU. Binomial regression and Poisson regression were used to model prevalence and incidence rates, respectively. Multiplicative and additive models were tested, as well as no time lag and a one 4-week-period time lag. For each model, the mean absolute error (MAE) in prediction of resistance was computed. The most accurate indicator was compared to other indicators using t-tests.
  
  
  RESULTS
  Results for all indicators were equivalent, except for 1/20 scenarios studied. In this scenario, where prevalence of carbapenem-resistant Pseudomonas sp. was predicted with carbapenem use, recommended daily doses per 100 admissions were less accurate than courses per 100 patient-days (p = 0.0006).
  
  
  CONCLUSIONS
  A single best indicator to predict antimicrobial resistance might not exist. Feasibility considerations such as ease of computation or potential external comparisons could be decisive in the choice of an indicator for surveillance of healthcare antimicrobial use.
authors.affiliation: Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montréal, Québec, Canada.|Direction des risques biologiques et de la santé au travail, Institut national de santé publique du Québec, Québec and Montréal, Québec, Canada.
authors.forename: Élise
authors.initials: É
authors.lastname: Fortin
authors.affiliation: Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montréal, Québec, Canada.
authors.forename: Robert W
authors.initials: RW
authors.lastname: Platt
authors.affiliation: Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montréal, Québec, Canada.|Department of Pediatrics, The Montréal Children's Hospital, McGill University, Montréal, Québec, Canada.
authors.forename: Patricia S
authors.initials: PS
authors.lastname: Fontela
authors.affiliation: Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montréal, Québec, Canada.
authors.forename: David L
authors.initials: DL
authors.lastname: Buckeridge
authors.affiliation: Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montréal, Québec, Canada.|Direction des risques biologiques et de la santé au travail, Institut national de santé publique du Québec, Québec and Montréal, Québec, Canada.|Department of Pediatrics, The Montréal Children's Hospital, McGill University, Montréal, Québec, Canada.
authors.forename: Caroline
authors.initials: C
authors.lastname: Quach
mesh_terms: D000900:Anti-Bacterial Agents / Q000627:therapeutic use; D015780:Carbapenems / Q000627:therapeutic use; D015331:Cohort Studies; D003428:Cross Infection / Q000453:epidemiology*; D024881:Drug Resistance, Bacterial; D004755:Enterobacteriaceae / Q000187:drug effects; D004756:Enterobacteriaceae Infections / Q000188:drug therapy; D062665:Epidemiological Monitoring; D006801:Humans; D007363:Intensive Care Units, Neonatal; D011549:Pseudomonas / Q000187:drug effects; D011552:Pseudomonas Infections / Q000188:drug therapy; D012189:Retrospective Studies
chemical_list: D000900:Anti-Bacterial Agents; D015780:Carbapenems