Validation of the prediction rules identifying drug-resistant pathogens in community-onset pneumonia

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ID: 6063
2018
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Abstract
Validation of the prediction rules identifying drug-resistant pathogens in community-onset pneumonia Daisuke Kobayashi,1,2 Yuichiro Shindo,2 Ryota Ito,2,3 Mai Iwaki,4,5 Junya Okumura,2,6 Toshihiro Sakakibara,2,7 Ikuo Yamaguchi,8 Tetsuya Yagi,9 Tomohiko Ogasawara,4 Yasuteru Sugino,6 Hiroyuki Taniguchi,7 Hiroshi Saito,10 Hideo Saka,11 Takashi Kawamura,1 Yoshinori Hasegawa2 On behalf of the Central Japan Lung Study Group 1Kyoto University Health Service, Kyoto, Japan; 2Department of Respiratory Medicine, Nagoya University Graduate School of Medicine, Nagoya, Japan; 3Division of Infectious Diseases, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA; 4Department of Respiratory Medicine, Nagoya Daini Red Cross Hospital, Nagoya, Japan; 5Department of Respiratory Medicine, Kasugai Municipal Hospital, Kasugai, Japan; 6Department of Respiratory Medicine, Toyota Memorial Hospital, Toyota, Japan; 7Department of Respiratory Medicine and Allergy, Tosei General Hospital, Seto, Japan; 8Department of Central Laboratory, Toyohashi Municipal Hospital, Toyohashi, Japan; 9Department of Infectious Diseases, Nagoya University Hospital, Nagoya, Japan; 10Department of Respiratory Medicine, Aichi Cancer Center Aichi Hospital, Okazaki, Japan; 11Department of Respiratory Medicine, National Hospital Organization, Nagoya Medical Center, Nagoya, Japan Background: Appropriate initial antibiotic treatment and avoiding administration of unnecessary broad-spectrum antibiotics are important for the treatment of pneumonia. To achieve this, assessment of risk for drug-resistant pathogens (DRPs) at diagnosis is essential.Purpose: The aim of this study was to validate a predictive rule for DRPs that we previously proposed (the community-acquired pneumonia drug-resistant pathogen [CAP-DRP] rule), comparing several other predictive methods.Patients and methods: A prospective observational study was conducted in hospitalized patients with community-onset pneumonia at four institutions in Japan. Pathogens identified as not susceptible to ceftriaxone, ampicillin–sulbactam, macrolides, and respiratory fluoroquinolones were defined as CAP-DRPs.Results: CAP-DRPs were identified in 73 (10.1%) of 721 patients analyzed. The CAP-DRP rule differentiated low vs high risk of CAP-DRP at the threshold of ≥3 points or 2 points plus any of methicillin-resistant Staphylococcus aureus specific factors with a sensitivity of 0.45, specificity of 0.87, positive predictive value of 0.47, negative predictive value of 0.87, and accuracy of 0.79. Its discrimination performance, area under the receiver operating characteristic curve, was 0.73 (95% confidence interval 0.66–0.79). Specificity of the CAP-DRP rule against CAP-DRPs was the highest among the six predictive rules tested.Conclusion: The performance of the predictive rules and criteria for CAP-DRPs was limited. However, the CAP-DRP rule yielded high specificity and could specify patients who should be treated with non-broad-spectrum antibiotics, eg, a non-pseudomonal β-lactam plus a macrolide, more precisely. Keywords: antibiotic resistance, algorithms, community-acquired pneumonia, healthcare-associated pneumonia 
Reference Key
daisuke2018validationinfection Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Daisuke Kobayashi;Yuichiro Shindo;Ryota Ito;Mai Iwaki;Junya Okumura;Toshihiro Sakakibara;Ikuo Yamaguchi;Tetsuya Yagi;Tomohiko Ogasawara;Yasuteru Sugino;Hiroyuki Taniguchi;Hiroshi Saito;Hideo Saka;Takashi Kawamura;Yoshinori Hasegawa and
Journal Infection and drug resistance
Year 2018
DOI
10.2147/IDR.S165669
URL
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