2467. Inferring Strain Type Attribution from Antibiotic Resistance Profiles among E. coli Causing Healthcare-Associated Infections in the United States, 2013–2017

Abstract

Abstract Background E. coli is a leading cause of healthcare-associated infections; clonal group ST131, which has expanded worldwide with notable increased severity of infections, is commonly resistant to extended-spectrum cephalosporins (ESC) and fluoroquinolones (FQ). Herein, we relate ESC and FQ resistance profiles from CDC’s National Healthcare Safety Network (NHSN) with specific strain types from CDC laboratory surveillance collections. Methods NHSN isolate and antibiotic susceptibility testing data were collected from all E. coli associated with central line-associated bloodstream infections, catheter-associated urinary tract infections, ventilator-associated events, or surgical site infections from 2013–2017. Resistance was scored as non-susceptibility to at least one drug per class [susceptible (S); resistant (R)]. ESC and FQ susceptibilities and multilocus sequence types (ST) using the Achtman 7 loci scheme were determined for a contemporaneous set of E. coli isolates collected through CDC laboratory surveillance. Results Of 96,672 E. coli infections reported to NHSN, 13% were ESC-R/FQ-R, 23% ESC-S/FQ-R, 4% ESC-R/FQ-S, and 60% were ESC-S/FQ-S. Among 105 ESC-R/FQ-R and 21 ESC-S/FQ-R laboratory isolates, the majority (67.6% and 52.4%, respectively) were ST131, whereas of 38 ESC-R/FQ-S and 53 ESC-S/FQ-S isolates, ST131 was a minority (18.4% and 7.5%, respectively). The odds of an isolate being ST131 were 10.5 if FQ-R (P < 0.001), 3.4 if ESC-R (P < 0.001), and 6.0 if ESC-R/FQ-R (P < 0.001). Using the national distribution of resistance combinations from NHSN, and assuming static ST-resistance distribution, we can infer that ST131 was responsible for 25.8% (95% CI, 23.9%-27.6%) of all E.coli healthcare-associated infections in the United States in 2013–2017. Conclusion Molecular inferences generated by applying laboratory data to resistance signature data in reportable datasets may make national E. coli ST burden estimates possible. Further characterization of resistance combinations with strain type, infection rates, and clinical outcomes may inform targeted prevention strategies at the local/regional level. Disclosures All authors: No reported disclosures.