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https://www.arca.fiocruz.br/handle/icict/36065
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ArticleCopyright
Open access
Embargo date
2020-10-02
Sustainable Development Goals
03 Saúde e Bem-EstarCollections
- INI - Artigos de Periódicos [3645]
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PREDICTING ACQUISITION OF CARBAPENEM-RESISTANT GRAM-NEGATIVE PATHOGENS IN INTENSIVE CARE UNITS
Multi-drug resistance
Gram-negative
Healthcare-associated infection
Predictive models
Intensive care units
Affilliation
Pontifical Catholic University of Rio de Janeiro. Industrial Engineering Department. Rio de Janeiro, RJ, Brazil.
Université Clermont Auvergne. Clermont-Ferrand, France / École de Mines Saint-Etienne. CNRS. UMR 6158 LIMOS. Centre CIS. Saint-Etienne, France.
Copa D’Or Hospital. Rio de Janeiro, RJ, Brazil / Federal University of the State of Rio de Janeiro. Department of General Medicine. Rio de Janeiro, RJ, Brazil.
Pontifical Catholic University of Rio de Janeiro. Industrial Engineering Department. Rio de Janeiro, RJ, Brazil.
D’Or Institute for Research and Education. Rio de Janeiro, RJ, Brazil / Fundação Oswaldo Cruz. Instituto Nacional de Infectologia Evandro Chagas. Rio de Janeiro, RJ, Brasil.
Université Clermont Auvergne. Clermont-Ferrand, France / École de Mines Saint-Etienne. CNRS. UMR 6158 LIMOS. Centre CIS. Saint-Etienne, France.
Copa D’Or Hospital. Rio de Janeiro, RJ, Brazil / Federal University of the State of Rio de Janeiro. Department of General Medicine. Rio de Janeiro, RJ, Brazil.
Pontifical Catholic University of Rio de Janeiro. Industrial Engineering Department. Rio de Janeiro, RJ, Brazil.
D’Or Institute for Research and Education. Rio de Janeiro, RJ, Brazil / Fundação Oswaldo Cruz. Instituto Nacional de Infectologia Evandro Chagas. Rio de Janeiro, RJ, Brasil.
Abstract
Background: Infections by multidrug-resistant Gram-negative (MDRGN) bacteria are among the greatest contemporary health concerns, especially in intensive care units (ICUs), and may be associated with increased hospitalization time, morbidity, costs, and mortality. Aim: The study aimed to predict carbapenem-resistant MDRGN acquisition in ICUs, to determine its risk factors, and to assess the impact of this acquisition on mortality rate. Methods: A matched caseecontrol study was performed in patients admitted to the ICU at a large Brazilian hospital over a five-year period. Cases were defined as patients who acquired carbapenem-resistant MDRGN bacteria during hospitalization. Controls were defined as patients who had no detection of carbapenem-resistant MDRGN bacteria. Cases were matched to controls according to the admission period. Risk factors were identified by multiple logistic regression using a stepwise selection method. Findings: In total, 343 cases and 1029 controls were analysed. The 30-day mortality rate for subjects with ICU-associated carbapenem-resistant MDRGN was 37.6%. Five variables were identified as statistically significant and more relevant for the acquisition of multidrug-resistant strains: increased Simplified Acute Physiology Score 3, patients with severe chronic obstructive pulmonary disease and exposure to haemodialysis catheter, central venous catheter, or mechanical ventilation. Models developed displayed good results with an accuracy of w90%. Patients who acquired MDRGN were 2.72 times more likely to die than non-MDRGN acquisition patients. Conclusion: Finding risk factors and developing predictive models may benefit patients through early detection and by controlling the spread of MDR. The presence of mechanical ventilation and central venous catheter were the main risk factors demonstrated, and their use requires special attention.
Keywords
Carbapenem resistanceMulti-drug resistance
Gram-negative
Healthcare-associated infection
Predictive models
Intensive care units
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