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Derivation and validation of a risk assessment model for drug-resistant pathogens in hospitalized patients with community-acquired pneumonia

Published online by Cambridge University Press:  29 September 2022

Michael B. Rothberg Open the ORCID record for Michael B. Rothberg [Opens in a new window] ,
Sarah Haessler ,
Abhishek Deshpande Open the ORCID record for Abhishek Deshpande [Opens in a new window] ,
Pei-Chun Yu ,
Peter K. Lindenauer ,
Marya D. Zilberberg Open the ORCID record for Marya D. Zilberberg [Opens in a new window] ,
Thomas L. Higgins Open the ORCID record for Thomas L. Higgins [Opens in a new window]  and
Peter B. Imrey
Michael B. Rothberg*
Affiliation:
Center for Value-Based Care Research, Cleveland Clinic Community Care, Cleveland Clinic, Cleveland, Ohio
Sarah Haessler
Affiliation:
Division of Infectious Diseases, University of Massachusetts Medical School – Baystate, Springfield, Massachusetts
Abhishek Deshpande
Affiliation:
Center for Value-Based Care Research, Cleveland Clinic Community Care, Cleveland Clinic, Cleveland, Ohio Department of Infectious Disease, Respiratory Institute, Cleveland Clinic, Cleveland, Ohio
Pei-Chun Yu
Affiliation:
Department of Quantitative Health Sciences, Cleveland Clinic, Cleveland, Ohio
Peter K. Lindenauer
Affiliation:
Institute for Healthcare Delivery and Population Science and Department of Medicine, University of Massachusetts Medical School–Baystate, Springfield, Massachusetts
Marya D. Zilberberg
Affiliation:
University of Massachusetts, Amherst, Massachusetts, and EviMed Research Group, Goshen, Massachusetts
Thomas L. Higgins
Affiliation:
Division of Pulmonary and Critical Care Medicine, University of Massachusetts Medical School–Baystate, Springfield, Massachusetts The Center for Case Management, Natick, Massachusetts
Peter B. Imrey
Affiliation:
Department of Quantitative Health Sciences, Cleveland Clinic, Cleveland, Ohio Cleveland Clinic Lerner College of Medicine of Case Western Reserve University, Cleveland, Ohio
*
Author for correspondence: Michael B. Rothberg, E-mail: rothbem@ccf.org
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Abstract

Objective:

To derive and validate a model for risk of resistance to first-line community-acquired pneumonia (CAP) therapy.

Design:

We developed a logistic regression prediction model from a large multihospital discharge database and validated it versus the Drug Resistance in Pneumonia (DRIP) score in a holdout sample and another hospital system outside that database. Resistance to first-line CAP therapy (quinolone or third generation cephalosporin plus macrolide) was based on blood or respiratory cultures.

Setting:

This study was conducted using data from 177 Premier Healthcare database hospitals and 11 Cleveland Clinic hospitals.

Participants:

Adults hospitalized for CAP.

Exposure:

Risk factors for resistant infection.

Results:

Among 138,762 eligible patients in the Premier database, 12,181 (8.8%) had positive cultures and 5,200 (3.8%) had organisms resistant to CAP therapy. Infection with a resistant organism in the previous year was the strongest predictor of resistance; markers of acute illness (eg, receipt of mechanical ventilation or vasopressors) and chronic illness (eg, pressure ulcer, paralysis) were also associated with resistant infections. Our model outperformed the DRIP score with a C-statistic of 0.71 versus 0.63 for the DRIP score (P < .001) in the Premier holdout sample, and 0.65 versus 0.58 (P < .001) in Cleveland Clinic hospitals. Clinicians at Premier facilities used broad-spectrum antibiotics for 20%–30% of patients. In discriminating between patients with and without resistant infections, physician judgment slightly outperformed the DRIP instrument but not our model.

Conclusions:

Our model predicting infection with a resistant pathogen outperformed both the DRIP score and physician practice in an external validation set. Its integration into practice could reduce unnecessary use of broad-spectrum antibiotics.

Type
Original Article
Information
Infection Control & Hospital Epidemiology , Volume 44 , Issue 7 , July 2023 , pp. 1143 - 1150
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Copyright
© The Author(s), 2022. Published by Cambridge University Press on behalf of The Society for Healthcare Epidemiology of America

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