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Background: Management of complicated intraabdominal infections (cIAIs) requires containment of the source and appropriate initial antimicrobial therapy. Identifying the local data is important to guide the empirical selection of antimicrobial therapy. In this study, we aimed to describe the pathogen distribution and antimicrobial resistance of cIAI. Methods: In two major tertiary care hospitals in Egypt, we enrolled patients who met the case definition of cIAI from October 2022 to September 2023. Blood cultures were performed using the BACTAlert system (BioMerieux, Marcy l'Etoile, France). A culture of aspirated fluid, resected material, or debridement of the infection site was performed. Identification of pathogens and antimicrobial susceptibility testing were conducted by the VITEK-2 system (BioMerieux, Marcy l'Etoile, France). Gram-negative resistance genes were identified by PCR and confirmed by whole bacterial genome sequencing using the Nextera XT DNA Library Preparation Kit and sequencing with the MiSeq Reagent Kit 600 v3 (Illumina, USA) on the Illumina MiSeq. Results: We enrolled 423 patients, 275 (65.01%) males. The median age was 61.35 (range 25-72 years). We studied 452 recovered bacterial isolates. Gram-negative bacteria were the vast majority, dominated by E. coli, followed by Klebsiella pneumoniae, Pseudomonas aeruginosa, Acinetobacter baumannii, and Proteus mirabilis (33.6%, 30.5%, 13.7%, 13%, and 5.4%, respectively). High rates of resistance were detected to third- and fourth-generation cephalosporins and fluoroquinolones. No resistance was detected to colistin. Resistance to amikacin and tigecycline was low among all isolates. Resistance to meropenem and ceftazidime/avibactam was moderate. ESBL genes were common in E. coli and K. pneumoniae. CTX-M15 gene was the most frequent. Among Enterobacterales, blaOXA-48 and blaNDM were the most prevalent carbapenemase genes. Pseudomonas aeruginosa isolates harbored a wide variety of carbapenemase genes (OXA, NDM, VIM, SIM, GIM, SPM, IMP, AIM), dominated by metallo-beta-lactamases. In 20.6% of isolates, we identified two or more resistance genes. Conclusion: High resistance rates were detected to third- and fourth-generation cephalosporins and fluoroquinolones. Amikacin and tigecyclines were the most active antimicrobials. Our data call for urgent implementation of antimicrobial stewardship programs and reinforcement of infection control.
RESUMEN
OBJECTIVES: Bacteraemia during the course of neutropenia is often fatal. We aimed to identify factors predicting mortality to have an insight into better clinical management. METHODS: The study has a prospective, observational design using pooled data from febrile neutropenia patients with bacteraemia in 41 centres in 16 countries. Polymicrobial bacteraemias were excluded. It was performed through the Infectious Diseases-International Research Initiative platform between 17 March 2021 and June 2021. Univariate analysis followed by a multivariate binary logistic regression model was used to determine independent predictors of 30-d in-hospital mortality (sensitivity, 81.2%; specificity, 65%). RESULTS: A total of 431 patients were enrolled, and 85 (19.7%) died. Haematological malignancies were detected in 361 (83.7%) patients. Escherichia coli (n = 117, 27.1%), Klebsiellae (n = 95, 22% %), Pseudomonadaceae (n = 63, 14.6%), Coagulase-negative Staphylococci (n = 57, 13.2%), Staphylococcus aureus (n = 30, 7%), and Enterococci (n = 21, 4.9%) were the common pathogens. Meropenem and piperacillin-tazobactam susceptibility, among the isolated pathogens, were only 66.1% and 53.6%, respectively. Pulse rate (odds ratio [OR], 1.018; 95% confidence interval [CI], 1.002-1.034), quick SOFA score (OR, 2.857; 95% CI, 2.120-3.851), inappropriate antimicrobial treatment (OR, 1.774; 95% CI, 1.011-3.851), Gram-negative bacteraemia (OR, 2.894; 95% CI, 1.437-5.825), bacteraemia of non-urinary origin (OR, 11.262; 95% CI, 1.368-92.720), and advancing age (OR, 1.017; 95% CI, 1.001-1.034) were independent predictors of mortality. Bacteraemia in our neutropenic patient population had distinctive characteristics. The severity of infection and the way to control it with appropriate antimicrobials, and local epidemiological data, came forward. CONCLUSIONS: Local antibiotic susceptibility profiles should be integrated into therapeutic recommendations, and infection control and prevention measures should be prioritised in this era of rapidly increasing antibiotic resistance.