Analysis of transmission-related third-generation cephalosporin-resistant Enterobacterales by electronic data mining and core genome multi-locus sequence typing

Comparing automated surveillance systems for detection of pathogen-related clusters in healthcare settings

BACKGROUND

Detection of pathogen-related clusters within a hospital is key to early intervention to prevent onward transmission. Various automated surveillance methods for outbreak detection have been implemented in hospital settings. However, direct comparison is difficult due to heterogenicity of data sources and methodologies. In the hospital setting, we assess the performance of three different methods for identifying microbiological clusters when applied to various pathogens with distinct occurrence patterns.

METHODS

In this retrospective cohort study we use WHONET-SaTScan, CLAR (CLuster AleRt system) and our currently used percentile-based system (P75) for the means of cluster detection. The three methods are applied to the same data curated from 1st January 2014 to 31st December 2021 from a tertiary care hospital. We show the results for the following case studies: the introduction of a new pathogen with subsequent endemicity, an endemic species, rising levels of an endemic organism, and a sporadically occurring species.

RESULTS

All three cluster detection methods showed congruence only in endemic organisms. However, there was a paucity of alerts from WHONET-SaTScan (n = 9) compared to CLAR (n = 319) and the P75 system (n = 472). WHONET-SaTScan did not pick up smaller variations in baseline numbers of endemic organisms as well as sporadic organisms as compared to CLAR and the P75 system. CLAR and the P75 system revealed congruence in alerts for both endemic and sporadic organisms.

CONCLUSIONS

Use of statistically based automated cluster alert systems (such as CLAR and WHONET-Satscan) are comparable to rule-based alert systems only for endemic pathogens. For sporadic pathogens WHONET-SaTScan returned fewer alerts compared to rule-based alert systems. Further work is required regarding clinical relevance, timelines of cluster alerts and implementation.

Identification of a novel CG307 sub-clade in third-generation-cephalosporin-resistant Klebsiella pneumoniae causing invasive infections in the USA

Despite the notable clinical impact, recent molecular epidemiology regarding third-generation-cephalosporin-resistant (3GC-R) Klebsiella pneumoniae in the USA remains limited. We performed whole-genome sequencing of 3GC-R K. pneumoniae bacteraemia isolates collected from March 2016 to May 2022 at a tertiary care cancer centre in Houston, TX, USA, using Illumina and Oxford Nanopore Technologies platforms. A comprehensive comparative genomic analysis was performed to dissect population structure, transmission dynamics and pan-genomic signatures of our 3GC-R K. pneumoniae population. Of the 178 3GC-R K. pneumoniae bacteraemias that occurred during our study time frame, we were able to analyse 153 (86 %) bacteraemia isolates, 126 initial and 27 recurrent isolates. While isolates belonging to the widely prevalent clonal group (CG) 258 were rarely observed, the predominant CG, 307, accounted for 37 (29 %) index isolates and displayed a significant correlation (Pearson correlation test P value=0.03) with the annual frequency of 3GC-R K. pneumoniae bacteraemia. Interestingly, only 11 % (4/37) of CG307 isolates belonged to the commonly detected 'Texas-specific' clade that has been observed in previous Texas-based K. pneumoniae antimicrobial-resistance surveillance studies. We identified nearly half of our CG307 isolates (n=18) belonged to a novel, monophyletic CG307 sub-clade characterized by the chromosomally encoded bla SHV-205 and unique accessory genome content. This CG307 sub-clade was detected in various regions of the USA, with genome sequences from 24 additional strains becoming recently available in the National Center for Biotechnology Information (NCBI) SRA database. Collectively, this study underscores the emergence and dissemination of a distinct CG307 sub-clade that is a prevalent cause of 3GC-R K. pneumoniae bacteraemia among cancer patients seen in Houston, TX, and has recently been isolated throughout the USA.