1254. Prediction Models of Drug-Resistant Pathogens in Patients with Pneumonia
Session: Poster Abstract Session: Clinical Infectious Diseases: Respiratory Infections
Friday, October 28, 2016
Room: Poster Hall
Posters
  • Prediction Models of Drug-Resistant Pathogens in Patients with Pneumonia.png (563.1 kB)
  • Background:

    The 2005 ATS/IDSA guidelines proposed the term healthcare-associated pneumonia (HCAP) and suggested broad-spectrum antibiotic therapy for these patients. However, no single model including the HCAP criteria has yet demonstrated sufficient predictive value for the presence of drug-resistant pathogens (DRPs). Recognition of patients with DRPs is crucial for treatment of pneumonia. The aim of this study was to validate a previously developed scoring model for determining the risk for DRPs and to compare it with currently published 8 clinical prediction models including HCAP criteria.

    Methods:

    We conducted a retrospective study of adult patients with culture-positive pneumonia at a tertiary academic medical center from January 1, 2013 to December 31, 2014. The scoring model consists of: nonambulatory status; previous episode of DRPs; and immunosuppression. Each risk factor had 1 point, resulting in a maximum of 3 possible points. We evaluated the screening value of the scores by determining their areas under the receiver-operating characteristic (AUROC) curves for predicting DPRs.

    Results:

    In total, 312 patients were analyzed and DRPs were isolated in 33.0%. The most common organisms included Pseudomonas aeruginosa (20.2%), Hemophilus influenza (15.7%), and Streptococcus pneumoniae (13.5%). The risk score was higher in those with DRPs than those without DRPs (mean±SD, 0.92±0.68 vs. 0.27±0.51; P<0.001). The AUROC curves were 0.78 (95% confidence interval [CI], 0.71–0.84) for the risk score and 0.66 (95% CI, 0.60–0.72) for HCAP criteria. A score of 0 had a high negative predictive value (85.9%).

    Conclusion:

    The new scoring model had better AUROC curve than the current HCAP criteria. This model had a high negative predictive value and could prevent unnecessary use of broad-spectrum antibiotics.

    Nobuhiro Ariyoshi, MD, Internal Medicine, John A. Burns School of Medicine, University of Hawaii at Manoa, Honolulu, HI, Ivy Melgarejo, MD, John A. Burns School of Medicine, University of Hawaii at Manoa, Honolulu, HI and Gehan Devendra, MD, Department of Pulmonary & Critical Care Medicine, The Queen’s Medical Center, Honolulu, HI

    Disclosures:

    N. Ariyoshi, None

    I. Melgarejo, None

    G. Devendra, None

    Findings in the abstracts are embargoed until 12:01 a.m. CDT, Wednesday Oct. 26th with the exception of research findings presented at the IDWeek press conferences.