1371. Identification of Risk Factors to Predict Gram negative bacteria in Patients with Upper Extremity Infections

Abstract Background Gram negative bacteria (GNB) have been identified as a cause of upper extremity infections and empiric treatment directed to both gram positive and negative organisms is often recommended. Risk-based approaches to establish need for gram-negative coverage may help to minimize unnecessary drug exposure, but further information on such methods are currently lacking. The aim of this study was to identify risk factors associated with the isolation of GNB in patients with upper extremity infections. Methods We reviewed records of patients with upper extremity infections treated in two urban hospitals between March 2018 and July 2020. Prosthetic joint infections were excluded. Baseline demographic, clinical, surgical and microbiology data was collected. Multivariable logistic regression models were screened using Akaike Information Criterion to establish the best model and risk factors associated with isolation of a GNB. Results We identified 111 patients, the majority of whom were male with frequent history of IV drug use. Deep wound cultures in 30 (33.3%) individuals yielded a GNB, and 80% of these cases were polymicrobial. Among the GNB, most prevalent were Enterobacterales (10.4%), HACEK group (6.39%), and Pseudomonas spp. (4.5%) (Tables 1. and 2.). Infections were mostly limited to the soft tissue structures of the hand and the forearm, with involvements of the joint and bone being second and third most common. The final model identified the use of IV medications (OR 4.14, 95% CI 1.3 - 14.46) together with prior surgery at the site of infection within the last year (OR 5.56, 95% CI 1.06 - 30.98), and having an open wound on presentation (OR 3.03, 95% CI 1.04 - 9.47) as factors independently associated with isolation of a GNB (Table 3). AUROC of 0.702 indicates acceptable model discrimination. Table 1: Baseline characteristics Table 2: Bacterial isolates Table 3: Final model Conclusion Our logistic regression model identified significant predictors for isolation of GNB in upper extremity infections within this population. Results of this study will assist clinicians in making a better informed decision for the need of empiric gram negative coverage aimed to support the reduction of patient exposure to unnecessary antimicrobial coverage. External validation of the model is warranted prior to application to clinical care. Figure 1: AUROC Disclosures All Authors: No reported disclosures


Role of Clindamycin Versus Linezolid for Serious Group A Streptococcal Infections
Emily Heil, PharmD, MS, BCIDP 1 ; Emily Heil, PharmD, MS, BCIDP 1 ; Sapna Basappa, n/a 2 ; 1 University of Maryland School of Pharmacy; University of Maryland Medical Center, Baltimore, MD; 2 University of Maryland School of Pharmacy, Baltimore, Maryland

Session: P-76. Skin and Soft Tissue
Background. Streptococcus pyogenes can cause severe illnesses such as toxic-shock syndrome and necrotizing fasciitis due to pyrogenic exotoxins. Clindamycin is added to penicillin for treatment of severe S. pyogenes infections as it is a bacterial protein synthesis inhibitor which reduces toxin production. However, clindamycin is associated with several adverse effects including C. difficile infection. Linezolid is a bacterial protein synthesis inhibitor that has been shown to provide excellent coverage of S. pyogenes including toxin inhibition in vitro, but clinical evidence is lacking. We compared outcomes of patients treated with linezolid versus clindamycin for serious S. pyogenes infections.
Methods. This was a retrospective study of patients with necrotizing fasciitis or toxic shock syndrome caused by S. pyogenes admitted to the Shock Trauma Center at University of Maryland Medical Center treated with at least 48 hours of either clindamycin or linezolid. Data collected included Sequential Organ Failure Assessment (SOFA) and Laboratory Risk Indicator for Necrotizing Fasciitis (LRINEC) severity scores, time to resolution of infection, number of surgeries, C. difficile infection, other antibiotic associated adverse effects, and mortality. Associations between patient characteristics, antibiotic groups, and outcomes were analyzed using the chi-square test, Fisher's exact test and t-test or Wilcoxon rank-sum test as appropriate (SAS v 9.4).
Conclusion. Linezolid could be an alternate to clindamycin for the treatment of serious toxin producing S. pyogenes infections. Further prospective studies are needed.
Disclosures. Emily Heil, PharmD, MS, BCIDP, Nothing to disclose Background. Gram negative bacteria (GNB) have been identified as a cause of upper extremity infections and empiric treatment directed to both gram positive and negative organisms is often recommended. Risk-based approaches to establish need for gram-negative coverage may help to minimize unnecessary drug exposure, but further information on such methods are currently lacking. The aim of this study was to identify risk factors associated with the isolation of GNB in patients with upper extremity infections.

Identification of Risk Factors to Predict Gram negative bacteria in Patients with Upper Extremity Infections
Methods. We reviewed records of patients with upper extremity infections treated in two urban hospitals between March 2018 and July 2020. Prosthetic joint infections were excluded. Baseline demographic, clinical, surgical and microbiology data was collected. Multivariable logistic regression models were screened using Akaike Information Criterion to establish the best model and risk factors associated with isolation of a GNB.
Results. We identified 111 patients, the majority of whom were male with frequent history of IV drug use. Deep wound cultures in 30 (33.3%) individuals yielded a GNB, and 80% of these cases were polymicrobial. Among the GNB, most prevalent were Enterobacterales (10.4%), HACEK group (6.39%), and Pseudomonas spp. (4.5%) (Tables 1. and 2.). Infections were mostly limited to the soft tissue structures of the hand and the forearm, with involvements of the joint and bone being second and third most common. The final model identified the use of IV medications (OR 4.14, 95% CI 1.3 -14.46) together with prior surgery at the site of infection within the last year (OR 5.56, 95% CI 1.06 -30.98), and having an open wound on presentation (OR 3.03, 95% CI 1.04 -9.47) as factors independently associated with isolation of a GNB (Table 3). AUROC of 0.702 indicates acceptable model discrimination.   Conclusion. Our logistic regression model identified significant predictors for isolation of GNB in upper extremity infections within this population. Results of this study will assist clinicians in making a better informed decision for the need of empiric gram negative coverage aimed to support the reduction of patient exposure to unnecessary antimicrobial coverage. External validation of the model is warranted prior to application to clinical care. Background. Assess 30-day real-world outcomes associated with OMC for the treatment of adults with ABSSSI or CABP. Thirty-day outcomes are an important quality metric for both private and public payers. This retrospective study compared HRU among adult pts treated with OMC for ABSSSI or CABP in the 30-day pre-and post-OMC Rx periods. The pre-post study design was selected to assess how 30-day HRU changed post-OMC RX (proxy for treatment response).