Clinical Epidemiology (Dec 2022)
Antimicrobial Resistance and Mortality in Hospitalized Patients with Bacteremia in the Greater Paris Area from 2016 to 2019
Abstract
Salam Abbara,1,2 Didier Guillemot,1– 3 Salma El Oualydy,4 Maeva Kos,4 Cécile Poret,5 Stéphane Breant,5 Christian Brun-Buisson,1,2 Laurence Watier1,2 1Anti-Infective Evasion and Pharmacoepidemiology Team, Inserm, UVSQ, University Paris-Saclay, CESP, Montigny-Le-Bretonneux, France; 2Institut Pasteur, Epidemiology and Modelling of Antibiotic Evasion (EMAE), University Paris Cité, Paris, France; 3Public Health, Medical Information, Clinical Research, AP-HP, University Paris Saclay, Le Kremlin-Bicêtre, France; 4Plateforme des données de santé - Health Data Hub, Paris, France; 5AP-HP, Direction des Systèmes d’Information, Pôle Innovation et Données, Paris, FranceCorrespondence: Salam Abbara, Institut Pasteur, Epidemiology and Modelling of Antibiotic Evasion (EMAE) Unit, 25-28 rue du Docteur Roux, Paris, 75015, France, Tel +33 1 45 68 80 00, Email [email protected]: Antibiotic-resistant bacteremia is a leading global cause of infectious disease morbidity and mortality. Clinical data warehouses (CDWs) allow for the secure, real-time coupling of diverse data sources from real-world clinical settings, including care-based medical-administrative data and laboratory-based microbiological data. The main purpose of this study was to assess the contribution of CDWs in the epidemiological study of antibiotic resistance by constructing a database of bacteremia patients, BactHub, and describing their main clinico-microbiological features and outcomes.Patients and Methods: Adult patients with bacteremia hospitalized between January 1, 2016 and December 31, 2019 in 14 acute care university hospitals from the Greater Paris area were identified; their first bacteremia episode was included. Data describing patients, episodes of bacteremia, bacterial isolates, and antimicrobial resistance were structured.Results: Among 29,228 patients with bacteremia, 41% of episodes were community-onset (CO) and 59% were hospital-acquired (HA). Thirty-day and ninety-day mortality rates were 15% and 20% in CO episodes, and 18% and 36% in HA episodes. Overall resistance rates were high, including third-generation cephalosporin resistance among Klebsiella pneumoniae (CO 21%, HA 37%) and Escherichia coli (CO 13%, HA 17%), and methicillin resistance among Staphylococcus aureus (CO 11%, HA 14%). Annual incidence rates increased significantly from 2017 to 2019, from 20.0 to 20.9 to 22.1 stays with bacteremia per 1000 stays (p < 0.0001).Conclusion: The Bacthub database provides accurate clinico-microbiological data describing bacteremia across France’s largest hospital group. Data from Bacthub may inform surveillance and the clinical decision-making process for bacteremia patients, including choice of antimicrobial therapy. The database also offers opportunities for research, including analysis of hospital care pathways and significant patient outcomes such as mortality and recurrence of infection.Keywords: data warehousing, bacteremia, drug resistance, microbial, anti-bacterial agents, mortality, incidence