Association of ward-level antibiotic consumption with healthcare-associated Clostridioides difficile infections: an ecological study in five German university hospitals, 2017-2019.

OBJECTIVES: To analyse the influence of antibiotic consumption on healthcare-associated healthcare onset (HAHO) Clostridioides difficile infection (CDI) in a German university hospital setting. METHODS: Monthly ward-level antibiotic consumption measured in DDD/100 patient days (pd) and CDI surveillance data from five university hospitals in the period 2017 through 2019 were analysed. Uni- and multivariable analyses were performed with generalized estimating equation models. RESULTS: A total of 225 wards with 7347 surveillance months and 4 036 602 pd participated. With 1184 HAHO-CDI cases, there was a median incidence density of 0.17/1000 pd (IQR 0.03-0.43) across all specialties, with substantial differences among specialties. Haematology-oncology wards showed the highest median incidence density (0.67/1000 pd, IQR 0.44-1.01), followed by medical ICUs (0.45/1000 pd, IQR 0.27-0.73) and medical general wards (0.32/1000 pd, IQR 0.18-0.53). Multivariable analysis revealed carbapenem (mostly meropenem) consumption to be the only antibiotic class associated with increased HAHO-CDI incidence density. Each carbapenem DDD/100 pd administered increased the HAHO-CDI incidence density by 1.3% [incidence rate ratio (IRR) 1.013; 95% CI 1.006-1.019]. Specialty-specific analyses showed this influence only to be valid for haematological-oncological wards. Overall, factors like ward specialty (e.g. haematology-oncology ward IRR 2.961, 95% CI 2.203-3.980) or other CDI cases on ward had a stronger influence on HAHO-CDI incidence density (e.g. community-associated CDI or unknown association case in same month IRR 1.476, 95% CI 1.242-1.755) than antibiotic consumption. CONCLUSIONS: In the German university hospital setting, monthly ward-level carbapenem consumption seems to increase the HAHO-CDI incidence density predominantly on haematological-oncological wards. Furthermore, other patient-specific factors seem to be equally important to control HAHO-CDI.

Surveillance and Genomic Analysis of Third-Generation Cephalosporin-Resistant and Carbapenem-Resistant Klebsiella pneumoniae Complex in Germany.

To analyse the epidemiology and population structure of third-generation cephalosporin-resistant (3GCR) and carbapenem-resistant (CR) Klebsiella pneumoniae complex isolates, patients were screened for rectal colonisation with 3GCR/CR K. pneumoniae complex on admission to six German university hospitals (2016-2019). Also collected were 3GCR/CR and susceptible K. pneumoniae isolates from patients with bloodstream infections (2016-2018). Whole-genome sequencing was performed followed by multilocus sequencing typing (MLST), core-genome MLST, and resistome and virulome analysis. The admission prevalence of 3GCR K. pneumoniae complex isolates during the 4-year study period was 0.8%, and 1.0 bloodstream infection per 1000 patient admissions was caused by K. pneumoniae complex (3GCR prevalence, 15.1%). A total of seven K. pneumoniae complex bloodstream isolates were CR (0.8%). The majority of colonising and bloodstream 3GCR isolates were identified as K. pneumoniae, 96.7% and 98.8%, respectively; the remainder were K. variicola and K. quasipneumoniae. cgMLST showed a polyclonal population of colonising and bloodstream isolates, which was also reflected by MLST and virulome analysis. CTX-M-15 was the most prevalent extended-spectrum beta-lactamase, and 29.7% of the colonising and 48.8% of the bloodstream isolates were high-risk clones. The present study provides an insight into the polyclonal 3GCR K. pneumoniae population in German hospitals.

Vancomycin-resistant Enterococcus faecium colonizing patients on hospital admission in Germany: prevalence and molecular epidemiology.

OBJECTIVES: To analyse the rectal carriage rate and the molecular epidemiology of vancomycin-resistant Enterococcus faecium (VREfm) recovered from patients upon hospital admission. METHODS: Adult patients were screened at six German university hospitals from five different federal states upon hospital admission for rectal colonization with VREfm between 2014 and 2018. Molecular characterization of VREfm was performed by WGS followed by MLST and core-genome MLST analysis. RESULTS: Of 16350 patients recruited, 263 were colonized with VREfm, with increasing prevalence rates during the 5 year study period (from 0.8% to 2.6%). In total, 78.5% of the VREfm were vanB positive and 20.2% vanA positive, while 1.2% harboured both vanA and vanB. The predominant ST was ST117 (56.7%) followed by ST80 (15%), ST203 (10.9%), ST78 (5.7%) and ST17 (3.2%). ST117/vanB VREfm isolates formed a large cluster of 96 closely related isolates extending across all six study centres and four smaller clusters comprising 13, 5, 4 and 3 isolates each. In contrast, among the other STs inter-regional clonal relatedness was rarely observed. CONCLUSIONS: To our knowledge, this is the largest admission prevalence and molecular epidemiology study of VREfm. These data provide insight into the epidemiology of VREfm at six German university hospitals and demonstrate the remarkable inter-regional clonal expansion of the ST117/vanB VREfm clone.

Fourier-Transform Infrared (FTIR) Spectroscopy for Typing of Clinical Enterobacter cloacae Complex Isolates.

Members of the Enterobacter (E.) cloacae complex have emerged as important pathogens frequently encountered in nosocomial infections. Several outbreaks with E. cloacae complex have been reported in recent years, especially in neonatal units. Fast and reliable strain typing methods are crucial for real-time surveillance and outbreak analysis to detect pathogen reservoirs and transmission routes. The aim of this study was to evaluate the performance of Fourier-transform infrared (FTIR) spectroscopy as a fast method for typing of clinical E. cloacae complex isolates, when whole genome sequencing (WGS) analysis was used as reference. First, the technique was used retrospectively on 24 first isolates of E. cloacae complex strains from neonatal patients and showed good concordance with SNP-based clustering [adjusted rand index (ARI) = 0.818] and with the sequence type (ST) (ARI = 0.801). 29 consecutive isolates from the same patients were shown by WGS analysis to almost always belong to the same SNP cluster as the first isolates, which was only inconsistently recognized by FTIR spectroscopy. Training of an artificial neural network (ANN) with all FTIR spectra from sequenced strains markedly improved the recognition of related and unrelated isolate spectra. In a second step, FTIR spectroscopy was applied on 14 strains during an outbreak with E. cloacae complex and provided fast typing results that were confirmed by WGS analysis. In conclusion, FTIR spectroscopy is a promising tool for strain typing of clinical E. cloacae complex strains. Discriminatory power can be improved by implementing an ANN for spectrum analysis. Due to its low costs and fast turnaround times, the method presents a valuable tool for real-time surveillance as well as outbreak analysis.

Typing and Species Identification of Clinical Klebsiella Isolates by Fourier Transform Infrared Spectroscopy and Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry.

Klebsiella pneumoniae and related species are frequent causes of nosocomial infections and outbreaks. Therefore, quick and reliable strain typing is crucial for the detection of transmission routes in the hospital. The aim of this study was to evaluate Fourier transform infrared spectroscopy (FTIR) and matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) as rapid methods for typing clinical Klebsiella isolates in comparison to whole-genome sequencing (WGS), which was considered the gold standard for typing and identification. Here, 68 clinical Klebsiella strains were analyzed by WGS, FTIR, and MALDI-TOF MS. FTIR showed high discriminatory power in comparison to the WGS reference, whereas MALDI-TOF MS exhibited a low ability to type the isolates. MALDI-TOF mass spectra were further analyzed for peaks that showed high specificity for different Klebsiella species. Phylogenetic analysis revealed that the Klebsiella isolates comprised three different species: K. pneumoniae, K. variicola, and K. quasipneumoniae Genome analysis showed that MALDI-TOF MS can be used to distinguish K. pneumoniae from K. variicola due to shifts of certain mass peaks. The peaks were tentatively identified as three ribosomal proteins (S15p, L28p, L31p) and one stress response protein (YjbJ), which exhibit amino acid differences between the two species. Overall, FTIR has high discriminatory power to recognize the clonal relationship of isolates, thus representing a valuable tool for rapid outbreak analysis and for the detection of transmission events due to fast turnaround times and low costs per sample. Furthermore, specific amino acid substitutions allow the discrimination of K. pneumoniae and K. variicola by MALDI-TOF MS.

Genomic characterisation of clinical and environmental Pseudomonas putida group strains and determination of their role in the transfer of antimicrobial resistance genes to Pseudomonas aeruginosa.

BACKGROUND: Pseudomonas putida is a Gram-negative, non-fermenting bacterium frequently encountered in various environmental niches. P. putida rarely causes disease in humans, though serious infections and outbreaks have been reported from time to time. Some have suggested that P. putida functions as an exchange platform for antibiotic resistance genes (ARG), and thus represents a serious concern in the spread of ARGs to more pathogenic organisms within a hospital. Though poorly understood, the frequency of ARG exchange between P. putida and the more virulent Pseudomonas aeruginosa and its clinical relevance are particularly important for designing efficient infection control strategies, such as deciding whether high-risk patients colonized with a multidrug resistant but typically low pathogenic P. putida strain should be contact isolated or not. RESULTS: In this study, 21,373 screening samples (stool, rectal and throat swab) were examined to determine the presence of P. putida in a high-risk group of haemato-oncology patients during a 28-month period. A total of 89 P. putida group strains were isolated from 85 patients, with 41 of 89 (46.1%) strains harbouring the metallo-beta-lactamase gene bla VIM. These 41 clinical isolates, plus 18 bla VIM positive environmental P. putida isolates, and 17 bla VIM positive P. aeruginosa isolates, were characterized by whole genome sequencing (WGS). We constructed a maximum-likelihood tree to separate the 59 bla VIM positive P. putida group strains into eight distinct phylogenetic clusters. Bla VIM-1 was present in 6 clusters while bla VIM-2 was detected in 4 clusters. Five P. putida group strains contained both, bla VIM-1 and bla VIM-2 genes. In contrast, all P. aeruginosa strains belonged to a single genetic cluster and contained the same ARGs. Apart from bla VIM-2 and sul genes, no other ARGs were shared between P. aeruginosa and P. putida. Furthermore, the bla VIM-2 gene in P. aeruginosa was predicted to be only chromosomally located. CONCLUSION: These data provide evidence that no exchange of comprehensive ARG harbouring mobile genetic elements had occurred between P. aeruginosa and P. putida group strains during the study period, thus eliminating the need to implement enhanced infection control measures for high-risk patients colonized with a bla VIM positiv P. putida group strains in our clinical setting.

Positive impact of infection prevention on the management of nosocomial outbreaks at an academic hospital.

AIM: Infection prevention (IP) measures are vital to prevent (nosocomial) outbreaks. Financial evaluations of these are scarce. An incremental cost analysis for an academic IP unit was performed. MATERIAL & METHODS: On a yearly basis, we evaluated: IP measures; costs thereof; numbers of patients at risk for causing nosocomial outbreaks; predicted outbreak patients; and actual outbreak patients. RESULTS: IP costs rose on average yearly with €150,000; however, more IP actions were undertaken. Numbers of patients colonized with high-risk microorganisms increased. The trend of actual outbreak patients remained stable. Predicted prevented outbreak patients saved costs, leading to a positive return on investment of 1.94. CONCLUSION: This study shows that investments in IP can prevent outbreak cases, thereby saving enough money to earn back these investments.

Cost-Analysis of Seven Nosocomial Outbreaks in an Academic Hospital.

OBJECTIVES: Nosocomial outbreaks, especially with (multi-)resistant microorganisms, are a major problem for health care institutions. They can cause morbidity and mortality for patients and controlling these costs substantial amounts of funds and resources. However, how much is unclear. This study sets out to provide a comparable overview of the costs of multiple outbreaks in a single academic hospital in the Netherlands. METHODS: Based on interviews with the involved staff, multiple databases and stored records from the Infection Prevention Division all actions undertaken, extra staff employment, use of resources, bed-occupancy rates, and other miscellaneous cost drivers during different outbreaks were scored and quantified into Euros. This led to total costs per outbreak and an estimated average cost per positive patient per outbreak day. RESULTS: Seven outbreaks that occurred between 2012 and 2014 in the hospital were evaluated. Total costs for the hospital ranged between €10,778 and €356,754. Costs per positive patient per outbreak day, ranged between €10 and €1,369 (95% CI: €49-€1,042), with a mean of €546 and a median of €519. Majority of the costs (50%) were made because of closed beds. CONCLUSIONS: This analysis is the first to give a comparable overview of various outbreaks, caused by different microorganisms, in the same hospital and all analyzed with the same method. It shows a large variation within the average costs due to different factors (e.g. closure of wards, type of ward). All outbreaks however cost considerable amounts of efforts and money (up to €356,754), including missed revenue and control measures.