Objective: Hospitalized patients with community-acquired pneumonia (CAP) are at risk of developing Clostridioides difficile infection (CDI). We developed and tested clinical decision-rules for identifying CDI risk in this patient population. Methods: The study was a single-center retrospective, case-control analysis of hospitalized adult patients empirically treated for CAP between January 1, 2014 and March 3, 2018. Differences between cases (CDI diagnosed within 180 days following admission) and controls (no test result indicating CDI during the study period) with respect to pre-hospitalization variables were modeled to generate propensity scores. Post-admission variables were used to predict case status on each post-admission day where: a) ≥1 additional case was identified, and b) each model strata contained ≥15 subjects. Models were developed and tested using Optimal Discriminant Analysis and Classification Tree Analysis. Results: Forty-four cases and 181 controls were included. The median time to diagnosis was 50 days post-admission. After weighting, three models were identified (20-, 117-, and 165-days post-admission). The day 20 model yielded the greatest [weighted (w)] accuracy (wROC area=0.826) and the highest chance-corrected accuracy (wESS=65.3). Having a positive culture (odds 1:4, p=0.001), receipt of ceftriaxone + azithromycin for a defined infection (odds 3:5, p=0.006), and continuation of empiric broad-spectrum antibiotics with activity against P. aeruginosa when no pathogen was identified (odds 1:8, p=0.013) were associated with CDI on day 20. Conclusion: Three models were identified that accurately predicted CDI in hospitalized patients treated for CAP. Antibiotic use increased the risk of CDI in all models, underscoring the importance of antibiotic stewardship.

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Adults hospitalized with community-acquired pneumonia (CAP) typically receive antibiotics and thus are at increased risk of developing Clostridioides difficile infection (CDI), a disease of significant morbidity. We developed and validated a CAP-specific clinical decision algorithm to facilitate optimal diagnostic stewardship of C. difficile polymerase chain reaction (PCR) testing. The study was a single-center retrospective, case-control analysis of hospitalized adult patients empirically treated for CAP between January 1, 2014 and May 29, 2018. A series of predictive models and validity assessments were used to evaluate demographic and post-admission patient-specific risk factors as predictors of CDI case status among patients with CAP. Thirty-two PCR confirmed CDI cases were identified and 232 randomly selected controls were drawn from the total CAP population. After propensity score weighting, hospital-onset (HO) CDI was significantly associated with broad-spectrum Gram-negative antibiotic use (P=0.002) as was subsequent community-onset (CO) CDI (P=0.005). Modified-APACHE II > 8.5 (P=0.003) and broad-spectrum Gram-negative antibiotic use (P=0.002) were associated with healthcare-associated CDI and were robust in multiple validity analyses. Patients with m-APACHE II ≤ 8.5 who received broad-spectrum Gram-negative antibiotics were more likely (odds=1:2) to experience healthcare-associated CDI compared to those who did not receive these broad-spectrum agents (odds=1:125) and compared to those with m-APACHE II > 8.5 irrespective of treatment (odds=5:27). We conclude that broad-spectrum Gram-negative antibiotic use was the common factor in development of CDI in patients with CAP in all settings. Prospective studies are needed to confirm the reproducibility and clinical utility of our model when used for diagnostic test stewardship.

Background Patients with community-acquired pneumonia (CAP) who are hospitalized and treated with antibiotics may carry an increased risk for developing Clostridioides difficile infection (CDI). Accurate risk estimation tools are needed to guide monitoring and CDI mitigation efforts. We aimed to identify patient-specific risk factors associated with CDI among hospitalized patients with CAP. Methods Design: retrospective case-control study of hospitalized patients who received CAP-directed antibiotic therapy between 1/1/2014 and 5/29/2018. Cases were hospitalized CAP patients who developed CDI post-admission. Control patients did not develop CDI and were selected at random from CAP patients hospitalized during this period. Variables: comorbidities, laboratory results, vital signs, severity of illness, prior hospitalization, and past antibiotic use. Propensity-score weights: identified via structural decomposition analysis of pre-treatment variables. Analysis: weighted classification tree models that predicted any CDI, hospital-onset CDI, and any healthcare-associated CDI according to CAP antibiotic treatment. Performance: percent accuracy in classification (PAC) and weighted positive (PPV) and negative predictive values (NPV). Modeling: completed using the ODA package (v1.0.1.3) for R (v3.5.1). Results A total of 32 cases and 232 controls were identified. Sixty pre-treatment variables were screened. Structural decomposition analysis, completed in two stages, identified prior hospitalization (OR 6.56, 95% CI: 3.01-14.31; PAC: 80.3%) and BUN greater than 29 mg/dL (OR 11.67, 95% CI: 2.41-56.5; PAC: 80.8%) as propensity-score weights. With respect to CDI, receipt of broad-spectrum anti-pseudomonal antibiotics was significantly (all P’s< 0.05) associated with any CDI (NPV: 90.29%, PPV: 27.94%), hospital-onset CDI (NPV: 97.53%, PPV: 26.86%), and healthcare-associated CDI (NPV: 92.89%, PPV: 27.94%). Conclusion We identified risk factors available at hospital admission and empiric use of broad-spectrum Gram-negative antibiotics as being associated with the development of CDI. Model PPVs were over two-fold greater than our sample base rate. Increased monitoring and avoidance of overly broad antibiotic use in high-risk patients appears warranted. Disclosures All Authors: No reported disclosures