Attributable deaths caused by infections with antibiotic-resistant bacteria in France

Raoult, Didier; Léone, Marc; Roussel, Yanis; Rolain, Jean‐Marc

doi:10.1016/s1473-3099(18)30800-4

Cited by 25 publications

(20 citation statements)

References 6 publications

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“…17 However, the accuracy of these estimates has been challenged by the scientific community. 4,18 Notably, the U.S. estimate of deaths is derived from a CDC point prevalence study where all antibiotic-resistant infections were assumed to carry the same mortality risk of 6.5%, which we believe not to be true. 19,20 Not only does attributable mortality vary by pathogen, it also varies by site of infection and virulence as suggested by severity of illness at presentation.…”

Section: Global and Regional Burden Of Antimicrobial Resistance-relatmentioning

confidence: 99%

Difficult-to-Treat Antibiotic-Resistant Gram-Negative Pathogens in the Intensive Care Unit: Epidemiology, Outcomes, and Treatment

Strich

Kadri

2019

Semin Respir Crit Care Med

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Antibiotic resistance among gram-negative pathogens is a world-wide problem that poses a constant threat to patients in the intensive care unit and a therapeutic challenge for the intensivist. Furthermore, the substantial economic burden and increased mortality associated with infections due to highly resistant gram-negative pathogens exacerbate these challenges. Understanding the mechanisms, epidemiology, and risk factors for these infections is paramount to the successful control of outbreaks and for guiding therapy which often entails use of antibiotics with suboptimal efficacy and/or toxicity profiles. In this review we will discuss the global epidemiology, burden, risk factors, and treatment of highly resistant gram-negative infections as they apply to the intensive care population.

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Section: Global and Regional Burden Of Antimicrobial Resistance-relatmentioning

confidence: 99%

Difficult-to-Treat Antibiotic-Resistant Gram-Negative Pathogens in the Intensive Care Unit: Epidemiology, Outcomes, and Treatment

Strich

Kadri

2019

Semin Respir Crit Care Med

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“…This disparity between reality and the myth of antibiotic resistance could only be resolved by implementing efficient antibiotic resistance surveillance systems that observe in real or nearreal-time the results of susceptibility testing in deceased and survivors patients, as it is already the case in our institution 6 . Therefore, at the Marseille University Hospital Institute, using the monitoring systems implemented BALYSES (Bacterial real-time Laboratory-based Surveillance) 15 , MARSS (Marseille Antibiotic Resistance Surveillance System) and PACASurvE (PACA Surveillance Epidemiologic System) 16 , we monitor weekly the results of all strains isolated in the 4…”

Section: Introductionmentioning

confidence: 99%

“…University Hospitals of Marseille (Assistance Publique Hôpitaux de Marseille) and in laboratories of the region which participate to this surveillance system for which antibiotic susceptibility testing (AST) results are available 6,15,16 .…”

Section: Introductionmentioning

confidence: 99%

Major discrepancy between factual antibiotic resistance and consumption in South of France: analysis of 539,037 bacterial strains

Diallo

Baron

Dubourg

et al. 2020

Preprint

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Introduction: The burden of antibiotic resistance is currently estimated by mathematical modeling, without real count of resistance to key antibiotics. Here we report the real rate of resistance to key antibiotics in bacteria isolated from humans during a 5 years period in a large area in southeast in France. Methods: We conducted a retrospective study on antibiotic susceptibility of 539,107 clinical strains isolated from hospital and private laboratories in south of France area from January 2014 to January 2019. The resistance rate to key antibiotics as well as the proportion of bacteria classified as Difficult-to-Treat (DTR) were determined and compared with the Mann-Whitney U test, the Chi-test or the Fisher's exact test. Results: Among 539,037 isolates, we did not observe any significant increase or decrease in resistance to key antibiotics for 5 years, (oxacillin resistance in Staphylococcus aureus, carbapenem resistance in enterobacteria and Pseudomonas aeruginosa and 3rd generation cephalosporin resistance in Escherichia coli and Klebsiella pneumoniae). However, we observed a significant decrease in imipenem resistance for Acinetobacter baumannii from 2014 to 2018 (24.19% to 12.27%; p=0.005) and a significant increase of ceftriaxone resistance in Klebsiella pneumoniae (9.9% to 24,03%; p=0.001) and Enterobacter cloacae (24,05% to 42,05%; p=0.004). Of these 539,037 isolates, 1,604 (0.3%) had a DTR phenotype. Conclusion: Over a 5-year period, we did not observe a burden of AR in our region despite a high rate of antibiotic consumption in our country. These results highlight the need for implementation of real-time AR surveillance systems which use factual data.

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“…The most recent study from Cassini et al estimated that antibiotic resistance was responsible for 33,110 deaths per year in Europe 5 . However, this report uses mathematical models that does not represent factually resistance to several classes of antibiotics in a given bacterial species or the real cost of antibiotic resistance on mortality 3,[6][7][8] . These mathematical models, depending on the prevalence of antibiotic resistance in some countries, also use incidence ratios of a given infection to an invasive infection, and then mortality ratios, all from different literature reviews that could not be accurate to definitively estimate the number of extra deaths due to multidrug-resistance (MDR) 9 (https ://refle ction sipc.com/2018/11/07/ amr-death s-in-europ e/).…”

mentioning

confidence: 99%

“…This disparity between reality and the myth of antibiotic resistance could only be resolved by implementing efficient antibiotic resistance surveillance systems that observe in real or near-real-time the results of susceptibility testing in deceased and survivors patients, as it is already the case in our institution 6 . Therefore, at the Marseille University Hospital Institute, using the monitoring systems implemented BALYSES (Bacterial real-time Laboratory-based Surveillance) 15 , MARSS (Marseille Antibiotic Resistance Surveillance System) and PACASurvE (PACA Surveillance Epidemiologic System) 16 , we monitor weekly the results of all strains isolated in the 4 University Hospitals of Marseille (Assistance Publique Hôpitaux de Marseille) and in laboratories of the region which participate to this surveillance system for which antibiotic susceptibility testing (AST) results are available 6,15,16 .…”

mentioning

confidence: 99%

Major discrepancy between factual antibiotic resistance and consumption in South of France: analysis of 539,037 bacterial strains

Diallo

Baron

Dubourg

et al. 2020

Sci Rep

Self Cite

View full text Add to dashboard Cite

The burden of antibiotic resistance is currently estimated by mathematical modeling, without real count of resistance to key antibiotics. Here we report the real rate of resistance to key antibiotics in bacteria isolated from humans during a 5 years period in a large area in southeast in France. We conducted a retrospective study on antibiotic susceptibility of 539,107 clinical strains isolated from hospital and private laboratories in south of France area from January 2014 to January 2019. The resistance rate to key antibiotics as well as the proportion of bacteria classified as Difficult-to-Treat (DTR) were determined and compared with the Mann–Whitney U test, the χ2 test or the Fisher’s exact test. Among 539,037 isolates, we did not observe any significant increase or decrease in resistance to key antibiotics for 5 years, (oxacillin resistance in Staphylococcus aureus, carbapenem resistance in enterobacteria and Pseudomonas aeruginosa and 3rd generation cephalosporin resistance in Escherichia coli and Klebsiella pneumoniae). However, we observed a significant decrease in imipenem resistance for Acinetobacter baumannii from 2014 to 2018 (24.19–12.27%; p = 0.005) and a significant increase of ceftriaxone resistance in Klebsiella pneumoniae (9.9–24.03%; p = 0.001) and Enterobacter cloacae (24.05–42.05%; p = 0.004). Of these 539,037 isolates, 1604 (0.3%) had a DTR phenotype. Over a 5-year period, we did not observe a burden of AR in our region despite a high rate of antibiotic consumption in our country. These results highlight the need for implementation of real-time AR surveillance systems which use factual data.

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Attributable deaths caused by infections with antibiotic-resistant bacteria in France

Cited by 25 publications

References 6 publications

Difficult-to-Treat Antibiotic-Resistant Gram-Negative Pathogens in the Intensive Care Unit: Epidemiology, Outcomes, and Treatment

Difficult-to-Treat Antibiotic-Resistant Gram-Negative Pathogens in the Intensive Care Unit: Epidemiology, Outcomes, and Treatment

Major discrepancy between factual antibiotic resistance and consumption in South of France: analysis of 539,037 bacterial strains

Major discrepancy between factual antibiotic resistance and consumption in South of France: analysis of 539,037 bacterial strains

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