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Background Urinary tract infections (UTIs) are among the most common indications for antibiotic therapy. As antibiotic resistance continues to grow, it is critical to identify those at higher risk for drug-resistant (DR) UTIs to guide empiric therapy, improve clinical outcomes, and limit costs of care. The aim of this study was to identify risk factors for DR UTI and develop a risk scoring tool which could aid in empiric antibiotic prescribing. Methods Single-center retrospective pilot study of adult patients treated for UTI from August 1, 2015 to August 31, 2016. Patients who had asymptomatic bacteriuria, were pregnant within 4 months of admission, or had improperly collected urine cultures were excluded. DR was defined as phenotypic resistance to at least 1 agent in 3 or more antibiotic classes commonly used to treat UTIs. Risk factors for DR UTI were derived from previously published literature and multivariable logistic regression of individual patient data (IPD). Adjusted odds ratios (aORs) were developed by combining ORs from previous literature and IPD. A scoring tool was derived from weight-proportional integer-adjusted coefficients of the predictive model aORs. Results Risk factors were derived from 9 previously published studies and adapted using IPD (N = 77) and included: long-term care (aOR = 4.31), prior hospitalization (aOR = 1.8), previous antibiotics (aOR = 4.33), advanced age (aOR = 1.12), urinary catheterization (aOR = 2.2), immune suppression (aOR = 1.6), and male sex (aOR = 2.56). Previous DR UTI was forced into the model (OR = 1.1). Baseline incidence of DR UTI was 28.7%. A risk score from 1 to 20 was developed and applied to IPD and demonstrated an area under the receiver operator curve (AUROC) of 0.625 (95% CI 0.484–0.767). Removing sex from the score produced an AUROC of 0.64 (95% CI 0.497–783). A sensitivity analysis applying the score to only urinary isolates that exhibited resistance to third-generation cephalosporins (13.8%) produced similar results. Conclusion Residence in long-term care and previous antibiotics were among the risk factors most closely associated with DR UTI. Considering cumulative risk scores may be useful in predicting DR UTI however the current study was hindered by a large degree of heterogeneity in previous literature. Disclosures All authors: No reported disclosures.

1462. Derivation of a Prediction Model for Risk of Drug-Resistant Urinary Tract Infection