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Individualizing Risk of Multidrug-Resistant Pathogens in Community-Onset Pneumonia
Authors:Marco Falcone  Alessandro Russo  Maddalena Giannella  Roberto Cangemi  Maria Gabriella Scarpellini  Giuliano Bertazzoni  José Martínez Alarcón  Gloria Taliani  Paolo Palange  Alessio Farcomeni  Annarita Vestri  Emilio Bouza  Francesco Violi  Mario Venditti
Abstract:

Introduction

The diffusion of multidrug-resistant (MDR) bacteria has created the need to identify risk factors for acquiring resistant pathogens in patients living in the community.

Objective

To analyze clinical features of patients with community-onset pneumonia due to MDR pathogens, to evaluate performance of existing scoring tools and to develop a bedside risk score for an early identification of these patients in the Emergency Department.

Patients and Methods

This was an open, observational, prospective study of consecutive patients with pneumonia, coming from the community, from January 2011 to January 2013. The new score was validated on an external cohort of 929 patients with pneumonia admitted in internal medicine departments participating at a multicenter prospective study in Spain.

Results

A total of 900 patients were included in the study. The final logistic regression model consisted of four variables: 1) one risk factor for HCAP, 2) bilateral pulmonary infiltration, 3) the presence of pleural effusion, and 4) the severity of respiratory impairment calculated by use of PaO2/FiO2 ratio. A new risk score, the ARUC score, was developed; compared to Aliberti, Shorr, and Shindo scores, this point score system has a good discrimination performance (AUC 0.76, 95% CI 0.71-0.82) and calibration (Hosmer-Lemeshow, χ2 = 7.64; p = 0.469). The new score outperformed HCAP definition in predicting etiology due to MDR organism. The performance of this bedside score was confirmed in the validation cohort (AUC 0.68, 95% CI 0.60-0.77).

Conclusion

Physicians working in ED should adopt simple risk scores, like ARUC score, to select the most appropriate antibiotic regimens. This individualized approach may help clinicians to identify those patients who need an empirical broad-spectrum antibiotic therapy.
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