title: Validation of a scoring tool to predict drug-resistant pathogens in hospitalised pneumonia patients.
abstract: BACKGROUND
  Health care-associated pneumonia (HCAP) affects a heterogeneous group of patients in frequent contact with health care systems. However, HCAP criteria poorly predict infection with drug-resistant (DR) pathogens.
  
  
  OBJECTIVE
  To validate our previously reported risk-scoring model (predictive of DR pathogen infection) in patients admitted to hospital with pneumonia.
  
  
  METHODS
  We evaluated 580 patients admitted with culture-positive bacterial pneumonia. We identified risk factors, evaluated the risk-scoring model's capacity to predict infection by DR pathogens and compared the model's diagnostic accuracy with that of current HCAP criteria.
  
  
  RESULTS
  DR pathogens were observed in 227/580 patients (39.1%). Of 269 HCAP patients, 153 (56.9%) were infected with DR pathogens. Overtreatment was more common in HCAP than in community-acquired pneumonia (58.7% vs. 41.2%, P < 0.001). Recent hospitalisation, admission from a long-term care facility, recent antibiotic treatment and tube feeding were independently associated with DR pathogens. For pathogen prediction, the risk-scoring model showed better diagnostic accuracy than HCAP criteria (area under receiver operating-characteristic curve = 0.723 vs. 0.673, P < 0.001).
  
  
  CONCLUSIONS
  According to current HCAP criteria, half of the HCAP patients were treated unnecessarily with broad-spectrum antibiotics. Risk scoring by stratifying risk factors could improve the identification of patients likely to be infected with DR pathogens.
authors.affiliation: Division of Pulmonology, Department of Internal Medicine, Severance Hospital, Institute of Chest Disease, Yonsei University College of Medicine, Seoul, Republic of Korea.
authors.forename: S C
authors.initials: SC
authors.lastname: Park
authors.forename: E Y
authors.initials: EY
authors.lastname: Kim
authors.forename: Y A
authors.initials: YA
authors.lastname: Kang
authors.forename: M S
authors.initials: MS
authors.lastname: Park
authors.forename: Y S
authors.initials: YS
authors.lastname: Kim
authors.forename: S K
authors.initials: SK
authors.lastname: Kim
authors.forename: J
authors.initials: J
authors.lastname: Chang
authors.forename: J Y
authors.initials: JY
authors.lastname: Jung
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000900:Anti-Bacterial Agents / Q000627:therapeutic use*; D019540:Area Under Curve; D016009:Chi-Square Distribution; D003428:Cross Infection / Q000175:diagnosis / Q000188:drug therapy* / Q000382:microbiology* / Q000635:transmission; D003661:Decision Support Techniques; D024881:Drug Resistance, Bacterial; D005260:Female; D006801:Humans; D007297:Inpatients; D016015:Logistic Models; D008297:Male; D008826:Microbial Sensitivity Tests; D008875:Middle Aged; D015999:Multivariate Analysis; D018410:Pneumonia, Bacterial / Q000175:diagnosis / Q000188:drug therapy* / Q000382:microbiology* / Q000635:transmission; D011237:Predictive Value of Tests; D012372:ROC Curve; D015203:Reproducibility of Results; D012189:Retrospective Studies; D018570:Risk Assessment; D012307:Risk Factors; D017211:Treatment Failure; D019564:Unnecessary Procedures
chemical_list: D000900:Anti-Bacterial Agents