Introduction: S. pneumoniae remains a leading cause of morbidity and mortality worldwide. The ARREST Program was established as a multidisciplinary, collaborative effort to use surveillance data and analytic techniques to better understand factors associated with antimicrobial resistance. The analyses presented herein were conducted to identify factors predictive of decreased susceptibility of pneumococci in hospitalized patients.
Methods: Five years (1997-2001) of North American SENTRY Program data were analyzed. MICs for amoxicillin-clavulanate (A-C), azithromycin (AZM), cefepime (CPM), ceftazidime (CTZ), ceftriaxone (CTX), clarithromycin (CLAR), erythromycin (ERY), and levofloxacin (LEV) versus patient-specific variables (e.g., age, specimen type) and hospital-specific variables (e.g., bed count, geographical region, study year) were analyzed using multivariable general linear modeling (GLM) for censored data with backwards stepwise elimination (at p > 0.1), yielding 1 model for each of these 8 agents.
Results: Of the 483 blood isolates from 29 hospitals, a range of 41-100% of MIC values were available for individual agents. Significant and frequently-identified factors included geographical region (6/8 models) and age (4/8 models). High predicted MICs resulted from combinations of these and other variables identified. Based on the model for CPM, factors predictive of high MICs were the following: geographical region = Southwest or Southeast, age ≤ 18 years, andspecimen type = lower respiratory. The observed % non-susceptible (NS) and MIC90 are compared for all agents for cohorts of patients with 2 to 3 versus those patients with 0 to1 of these variables (see table). The %NS was at least three times higher for patients with 2 to 3 versus 0 to 1 variables for 6/8 models.
European Congress of Clinical Microbiology and Infectious Disease (ECCMID), Glasgow, Scotland, May 2003
By SM Bhavnani, JP Hammel, PG Ambrose, A Forrest, RN Jones