Outbreak of colistin resistant, carbapenemase (bla NDM, bla OXA-232) producing Klebsiella pneumoniae causing blood stream infection among neonates at a tertiary care hospital in India

Abstract

Infections caused by multi-drug resistant Klebsiella pneumoniae are a leading cause of mortality and morbidity among hospitalized patients. In neonatal intensive care units (NICU), blood stream infections by K. pneumoniae are one of the most common nosocomial infections leading to poor clinical outcomes and prolonged hospital stays. Here, we describe an outbreak of multi-drug resistant K. pneumoniae among neonates admitted at the NICU of a large tertiary care hospital in India. The outbreak involved 5 out of 7 neonates admitted in the NICU. The antibiotic sensitivity profiles revealed that all K. pneumoniae isolates were multi-drug resistant including carbapenems and colistin. The isolates belonged to three different sequence types namely, ST-11, ST-16 and ST-101. The isolates harboured carbapenemase genes, mainly bla _NDM-1, bla _NDM-5 and bla _OXA-232 besides extended-spectrum β-lactamases however the colistin resistance gene mcr-1, mcr-2 and mcr-3 could not be detected. Extensive environmental screening of the ward and healthcare personnel led to the isolation of K. pneumoniae ST101 from filtered incubator water, harboring bla _NDM-5, bla _OXA-232 and ESBL genes (bla _CTX-M) but was negative for the mcr genes. Strict infection control measures were applied and the outbreak was contained. This study emphasizes that early detection of such high-risk clones of multi-drug resistant isolates, surveillance and proper infection control practices are crucial to prevent outbreaks and further spread into the community.

Keywords: K. pneumoniae; antimicrobial stewardship; hospital infection control; multi-drug resistant; outbreak.

Figure 1

Dendrogram generated by Bionumerics software, showing results of the cluster analysis on the basis of PFGE fingerprinting of five clinical and one environmental isolate of Klebsiella pneumoniae. Similarity analysis was performed using Dice coefficient (optimization 1.5%, tolerance 1%) and clustering was done by the unweighted-pair group method (UPGMA). A similarity coefficient of 80% was chosen for cluster definition and grey dotted line shows the delineation line. The degree of similarity is shown in the scale.