Interplay between Phenotypic Resistance to Relevant Antibiotics in Gram-Negative Urinary Pathogens: A Data-Driven Analysis of 10 Years’ Worth of Antibiogram Data

Abstract

The global emergence of antimicrobial resistance (AMR) has become a critical issue for clinicians, as it puts the decades of developments in the medical field in jeopardy, by severely limiting the useful therapeutic arsenal of drugs, both in nosocomial and community-acquired infections. In the present study, a secondary analysis of taxonomic and resistance data was performed, corresponding to urinary tract infections (UTIs) caused by Gram-negative bacteria, detected between 1 January 2008 to 31 December 2017 at the Albert Szent-Györgyi Health Center, University of Szeged. The following were identifiable from the data collected: year of isolation; outpatient (OP)/inpatient (IP) origin of the isolate; taxonomy; and susceptibility/resistance to selected indicator antibiotics. Principal component analysis (PCA) and a correlation matrix were used to determine the association between the presences of resistance against indicator antibiotics in each taxonomic group. Overall, data from n = 16,240 outpatient and n = 13,964 inpatient Gram-negative UTI isolates were included in the data analyses. In E. coli, strong positive correlations were seen between resistance to ciprofloxacin (CIP) and gentamicin (GEN) resistance (OP: r = 0.6342, p = 0.049; IP: r = 0.9602, p < 0.001), whereas strong negative correlations were shown for fosfomycin (FOS) and nitrofurantoin (NIT) resistance (OP: r= −0.7183, p = 0.019; IP: r= −0.7437; p = 0.014). For Klebsiella spp. isolates, CIP resistance showed strong positive correlation with resistance to third-generation cephalosporins (3GC) and GEN (r = 0.7976, p = 0.006 and r = 0.7428, p = 0.014, respectively) in OP isolates, and with resistance to trimethoprim-sulfamethoxazole (SXT) and FOS (r = 0.8144, p = 0.004 and r = 0.7758, p < 0.001, respectively) in IP isolates. For members of the Citrobacter-Enterobacter-Serratia group, the resistance among indicator antibiotics showed a strong positive correlation, with the exception of FOS resistance. In the Proteus-Providencia-Morganella group, the strongest association was noted between CIP and SXT resistance (OP: r = 0.9251, p < 0.001; IP: r = 0.8007; p = 0.005). In the case of OP Acinetobacter spp., CIP showed strong and significant positive correlations with most indicator antibiotics, whereas for IP isolates, strong negative correlations arose among imipenem (IMI) resistance and resistance to other drugs. For Pseudomonas spp., strong and positive correlations were noted among resistance to β-lactam antibiotics and aminoglycosides, with the exception of ceftazidime (CEFT), showing strong, but negative correlations. Though molecular tests and sequencing-based platforms are now considered as the gold-standard for AMR surveillance, standardized collection of phenotypic resistance data and the introduction of Big Data analytic methods may be a viable alternative for molecular surveillance, especially in low-resource settings.

Predominance of multidrug-resistant (MDR) bacteria causing urinary tract infections (UTIs) among symptomatic patients in East Africa: a call for action

“…Further, approximately half of the bacterial pathogens isolated from UTIs have MDR. That rate was much higher among inpatients (which we assume are predominantly hospital-acquired UTI) than in outpatients (which we assume are predominantly community-acquired UTIs), as has been described previously [20,21]. These alarming data provide further empirical evidence to enrich the findings of recent studies describing the high morbidity and mortality burden from ABR in Eastern sub-Saharan Africa [2].…”

No Correlation between Biofilm-Forming Capacity and Antibiotic Resistance in Environmental Staphylococcus spp.: In Vitro Results

“…Isolates involved in our assays were re-identified to the species level before inclusion in further experiments. Identification was carried out using matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry (MALDI-TOF MS), using a Mi-croFlex MALDI Biotyper (Bruker Daltonics, Bremen, Germany), based on the previously described protocol [46]. Reliability of the identification was assessed based on log(score) values, using breakpoints described elsewhere [47].…”

Repurposing antibiotic resistance surveillance data to support treatment of recurrent infections in a remote setting

“…Knowledge of any previous antibiograms helps to inform subsequent treatment decisions. To this end, data such as those analysed in this study can be used to support real-time clinical decisions in under-resourced settings, in addition to acting as a traditional surveillance system that helps to optimise treatment guidelines and stewardship interventions 33 – 35 .…”