Machine Learning To Stratify Methicillin-Resistant Staphylococcus aureus Risk among Hospitalized Patients with Community-Acquired Pneumonia

Author:

Rhodes Nathaniel J.123ORCID,Rohani Roxane123ORCID,Yarnold Paul R.4ORCID,Pawlowski Anna E.5,Malczynski Michael6,Qi Chao7,Sutton Sarah H.89,Zembower Teresa R.789,Wunderink Richard G.10ORCID

Affiliation:

1. Department of Pharmacy Practice, Midwestern University, Chicago College of Pharmacy, Downers Grove, Illinois, USA

2. Pharmacometrics Center of Excellence, Midwestern University, Downers Grove, Illinois, USA

3. Department of Pharmacy, Northwestern Memorial Hospital, Chicago, Illinois, USA

4. Optimal Data Analysis, LLC, Chicago, Illinois, USA

5. Clinical Translational Sciences Institute, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA

6. Department of Microbiology, Northwestern Memorial Hospital, Chicago, Illinois, USA

7. Department of Pathology, Northwestern Memorial Hospital, Chicago, Illinois, USA

8. Division of Infectious Diseases, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA

9. Healthcare Epidemiology and Infection Prevention, Northwestern Memorial Hospital, Chicago, Illinois, USA

10. Division of Pulmonary and Critical Care Medicine, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA

Abstract

Methicillin-resistant Staphylococcus aureus (MRSA) is an uncommon but serious cause of community-acquired pneumonia (CAP). A lack of validated MRSA CAP risk factors can result in overuse of empirical broad-spectrum antibiotics.

Funder

Division of Intramural Research, National Institute of Allergy and Infectious Diseases

HHS | NIH | National Center for Advancing Translational Sciences

American Association of Colleges of Pharmacy

Publisher

American Society for Microbiology

Subject

Infectious Diseases,Pharmacology (medical),Pharmacology

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