Prospective Evaluation Of A Novel Treatment Algorithm For Health Care-Associated Pneumonia

Roman Fazylov, Vincent Peyko, Sibte Burney,Henry Cohen

INFECTIOUS DISEASES IN CLINICAL PRACTICE(2017)

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摘要
Background: The current health care-associated pneumonia (HCAP) model may be too broad, leading to inappropriate use of broad-spectrum antibiotics. As a result, therapeutic algorithms, such aswhatMaruyama et al validated, have been developed for a more specific therapy. Our study aims to validate this algorithm in our patient population.Methods: This is a single-center, prospective, cohort study, with a historical control cohort. The prospective cohort followed an outlined algorithm to determine empiric therapy as compared with a historical cohort, which followed the standard of care. Prospective cohort patients were categorized as low versus high risk based on the algorithm and started on empiric community-acquired pneumonia (CAP) or HCAP regimens, respectively. Primary objectives included length of stay and initial empiric failure. Secondary objectives included patients treated with CAP versus HCAP regimens, intravenous to oral conversion time, antibiotic duration, and incidence of acute kidney injury.Results: There was no difference in the primary outcomes of length of stay and initial empiric regimen. Secondary outcomes were significant for elevated frequency of empiric CAP regimens compared with HCAP regimens and shorter antibiotic duration.Conclusions: The current definition of HCAP may be too expansive leading to the overuse of broad-spectrum antibiotics. Risk stratification based on the presence of multidrug-resistant risk factors and severity of illness may prove to be a useful assessment tool in determining targeted empiric therapy and limit the propagation of bacterial resistance.
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关键词
pneumonia, multidrug resistance, targeted empiric therapy, health care-associated pneumonia
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