Brandon J Webb1, Kristin Dascomb2, Edward Stenehjem2, Nathan Dean3. 1. Division of Infectious Diseases, University of Utah, Salt Lake City, UT, USA; Division of Clinical Epidemiology and Infectious Diseases, Intermountain Medical Center, Salt Lake City, UT, USA. Electronic address: Brandon.webb@imail.org. 2. Division of Infectious Diseases, University of Utah, Salt Lake City, UT, USA; Division of Clinical Epidemiology and Infectious Diseases, Intermountain Medical Center, Salt Lake City, UT, USA. 3. Division of Pulmonary and Critical Care Medicine, at Intermountain Medical Center and the University of Utah, Salt Lake City, UT, USA.
Abstract
BACKGROUND: Clinical management of community-acquired pneumonia (CAP) is increasingly complicated by antibiotic resistance. CAP due to pathogens resistant to guideline-recommended drugs (CAP-DRP) has increased. 2005 ATS/IDSA guidelines introduced a new category, healthcare-associated pneumonia (HCAP), and recommend extended-spectrum antibiotic treatment for patients meeting HCAP criteria. However, the predictive value of the HCAP model is limited and data suggest that outcomes are not improved using HCAP guideline-concordant therapy. Better methods to predict risk of CAP-DRP are needed. METHODS: We reviewed currently published literature on the performance status of HCAP as a predictive tool and studies describing additional risk factors for CAP-DRP. We also summarize the performance characteristics of the currently published alternative clinical prediction scores and compare them to that of the HCAP model. RESULTS: In addition to the five risk factors incorporated in HCAP, at least 13 other factors have been identified. The independent predictive value of any single factor is low, but accumulating factors results in increased risk of CAP-DRP. The performance characteristics of 9 clinical prediction scores are reviewed. Nearly all of the scores outperformed HCAP in their study populations. However, no single model has yet demonstrated adequate specificity to minimize unnecessary antibiotic use, while retaining sufficient sensitivity to prevent inadequate initial empiric antibiotic therapy when validated across a wide range of CAP-DRP prevalence. CONCLUSIONS: Additional development and validation of prediction scores based upon more refined risk factors for CAP-DRP is needed. Once an accurate, adequately validated prediction score is available, an interventional trial will be needed to determine clinical impact.
BACKGROUND: Clinical management of community-acquired pneumonia (CAP) is increasingly complicated by antibiotic resistance. CAP due to pathogens resistant to guideline-recommended drugs (CAP-DRP) has increased. 2005 ATS/IDSA guidelines introduced a new category, healthcare-associated pneumonia (HCAP), and recommend extended-spectrum antibiotic treatment for patients meeting HCAP criteria. However, the predictive value of the HCAP model is limited and data suggest that outcomes are not improved using HCAP guideline-concordant therapy. Better methods to predict risk of CAP-DRP are needed. METHODS: We reviewed currently published literature on the performance status of HCAP as a predictive tool and studies describing additional risk factors for CAP-DRP. We also summarize the performance characteristics of the currently published alternative clinical prediction scores and compare them to that of the HCAP model. RESULTS: In addition to the five risk factors incorporated in HCAP, at least 13 other factors have been identified. The independent predictive value of any single factor is low, but accumulating factors results in increased risk of CAP-DRP. The performance characteristics of 9 clinical prediction scores are reviewed. Nearly all of the scores outperformed HCAP in their study populations. However, no single model has yet demonstrated adequate specificity to minimize unnecessary antibiotic use, while retaining sufficient sensitivity to prevent inadequate initial empiric antibiotic therapy when validated across a wide range of CAP-DRP prevalence. CONCLUSIONS: Additional development and validation of prediction scores based upon more refined risk factors for CAP-DRP is needed. Once an accurate, adequately validated prediction score is available, an interventional trial will be needed to determine clinical impact.
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