High Prevalence of Fungal and NDM-OXA Producing Gram-Negative Bacterial Superinfections in the Second Wave of Coronavirus Disease 2019 in India: Experience from a Dedicated Coronavirus Disease 2019 Hospital in North India

Omika Katoch; Neha Sharad; Parul Singh; Sharad Srivastav; Richa Aggrawal; Rajesh Malhotra; Purva Mathur

doi:10.4103/jgid.jgid_238_21

High Prevalence of Fungal and NDM-OXA Producing Gram-Negative Bacterial Superinfections in the Second Wave of Coronavirus Disease 2019 in India: Experience from a Dedicated Coronavirus Disease 2019 Hospital in North India

J Glob Infect Dis. 2022 Nov 30;14(4):154-161. doi: 10.4103/jgid.jgid_238_21. eCollection 2022 Oct-Dec.

Authors

Omika Katoch¹, Neha Sharad², Parul Singh², Sharad Srivastav¹, Richa Aggrawal³, Rajesh Malhotra⁴, Purva Mathur¹

Affiliations

¹ Department of Laboratory Medicine, AIIMS, New Delhi, India.
² Department of Microbiology, AIIMS, New Delhi, India.
³ Department of Anesthesia and Critical Care, AIIMS, New Delhi, India.
⁴ Department of Orthopedics, JPNATC, AIIMS, New Delhi, India.

Abstract

Introduction: During the second wave of coronavirus disease 2019 (COVID-19), superinfection caused by fungus and multidrug-resistant bacteria worsened the severity of illness in COVID-19 patients. Limited studies from India reported the antimicrobial resistance pattern of secondary infections. In this study, we aim to study the epidemiology of pathogens causing superinfections and genotyping of Gram-negative isolates in COVID-19 patients.

Methods: This retrospective study was conducted at a dedicated COVID-19 center, India. The identification of bacteria/fungi was done by Vitek2^® and matrix-assisted laser desorption/ionization-time of flight mass spectrometry system. Identification of beta-lactamase genes was done using thermal cycler. The diagnosis of mucormycosis was based on 10% potassium hydroxide direct microscopy. Statistical analyses were performed using STATA version 15.1 (StataCorp., College Station, TX, USA). For continuous variables, mean and standard deviation were computed. For comparing proportions of secondary infections across admission location and outcomes, the Chi-squared test of independence was used. To compare the mean and median between intensive care units and outcomes, an independent t-test and a Mann-Whitney test were used.

Results: Of all the clinical samples, 45.4% of samples were cultured positive for secondary infections. Acinetobacter baumannii (35%) was the most common Gram-negative pathogen, while among Gram positive, it was Enterococcus faecium (40%). Among fungus, Candida spp. (61%) predominates followed by molds. Colistin and tigecycline proved effective against these pathogens. bla_NDM was the most prevalent gene followed by the bla_OX among the carbapenemase genes.

Conclusions: The mortality rate among COVID-19 patients with secondary infection was significantly higher compared to the overall mortality rate in COVID-19 patients.

Keywords: Antimicrobial resistance; Mucor; NDM; coronavirus disease 2019.