Introduction
The COVID-19 pandemic has adversely affected the world. As on 08th July 2022, globally, 558,703,551 confirmed cases and 6,369,057 deaths due to COVID-19 were reported [
1]. The COVID-19 illness is further compounded by co-occurrence of fungal infections among patients with COVID-19, weeks or months after their recovery. Such occurrences of COVID-19 Associated Mucormycosis (CAM) were reported from several countries [
2]. The unprecedented increase in cases of CAM in India during the second wave of the pandemic in May 2021 became a cause of concern and strained the already overwhelmed healthcare system [
3]. By the end June 2021, 40,824 cases of mucormycosis had been reported from India with 3229 patients succumbing to death [
4].
Mucormycosis is an opportunistic fungal infection caused by
Mucorales. It is an invasive disease with protracted clinical course, challenging treatment options and a very high mortality rate, which has increased from 41% in pre-COVID-19 era to 49% during the pandemic [
3,
5,
6]. Several equivocal hypotheses have been put forth regarding the risk factors associated with development of CAM. Systematic reviews from India and elsewhere have identified factors such as low oxygen milieu, diabetes mellitus (DM), inappropriate doses and duration of glucocorticoid use, host innate immunity related issues and prolonged duration of hospital stay with or without mechanical ventilation to be responsible for development of mucormycosis among COVID-19 patients [
7]. A retrospective study from India before the second wave of the pandemic, during September-December 2020, revealed COVID-19 related hypoxemia and improper glucocorticoid use to be associated with CAM [
8]. However, the surge of CAM cases during the second wave of the pandemic in India from May 2021 onward underlined the need for further in-depth investigation. Against this background, we conducted a multi-site case control investigation with the objectives of examining the monthly trend of proportion of CAM cases among in-patients since 1st January 2021 and identifying factors associated with the development of CAM post-second wave.
Material and methods
Study settings and participants
Study sites were the hospitals selected from the National Clinical Registry for COVID-19 as well as institutions associated with the Indian Council of Medical Research (ICMR) mycology research network [
9]. Eleven sites were chosen across the country and grouped under four zones based on their geographic locations, namely: North, East, West and South plus Central. The sites were shortlisted based on a selection matrix, which included willingness to conduct the study, infrastructure for COVID-19 testing, capacity for diagnosis of fungal diseases and investigators’ research expertise. Each research team consisted of microbiologists and clinicians such as ophthalmologists, general physicians, otolaryngologists, and radiologists.
Trend analysis
Medical record-based analysis of monthly trend of confirmed cases of CAM was carried out in the participating hospitals during 1st January 2021 to 30th September 2021. The total number of patients admitted in the same hospitals were considered as denominator.
Cases and controls
A case was considered as CAM when a COVID-19 patient (active or recovered, any age and gender) was suspected of mucormycosis clinically and confirmed microbiologically for the same [
10]. All specimens (either biopsy from paranasal sinus or nasal discharge or broncho-alveolar lavage or sputum) were considered microbiologically positive if aseptate or sparsely septate broad ribbon-like hyphae, with 90° branching angles were observed under direct microscopy in wet mount with potassium hydroxide (KOH) or lactophenol cotton blue or Periodic Acid Schiff (PAS) or Grocott-Gomori’s Methenamine-Silver (GMS) stain and/or culture on Sabouraud Dextrose Agar (SDA) showed cottony rapid growth with or without black heads, followed by identification of fungus by microscopy. Two controls were enrolled from a population of all COVID-19 patients discharged from the same hospital, 3–4 weeks prior to the date of diagnosis of an enrolled case of mucormycosis.
Suspected cases of mucormycosis, not microbiologically confirmed, irrespective of the treatment received and critically ill patients, unable to participate in the interview, were excluded from the study. The cases and controls were enrolled during 15th June 2021 to 30th September 2021. An individual once enrolled as control, was not considered in the population of controls for subsequent cases.
Sample size and sampling
Based on previous reports, the least common risk factor for CAM was intensive care unit (ICU) stay. Taking the proportion of CAM and COVID-19 in-patients requiring ICU stay as 68% and 30%, respectively [
11,
12] and a conservative Odds Ratio (OR) of 3, the sample size was estimated using Open Epi v3.0 (Rollins School of Public Health, Emory University) for unmatched case control design [
13]. With an allocation ratio of 1:2, the sample size was calculated as 73 cases and 145 controls at the power of 95% and alpha error of 5%. In each zone (North, East, West and South plus Central), 218 patients (73 cases of CAM and 145 controls of COVID-19 without mucormycosis) were attempted to be enrolled with overall sample size of 872. Due to the dynamic situation of the pandemic and differential burden of disease during the study period, there was unequal enrolment from different geographic locations. The zone wise enrolment of cases and controls is depicted in the spot map presented as Additional file
1: Fig S1.
Data were collected using a structured questionnaire with the following domains: (i) socio-demographic profile, (ii) present hospitalization, (iii) past hospitalization (in last 3 months), and (iv) home-based care for COVID-19. Data were extracted from the medical records of eligible cases and controls (as described above) by designated project staff posted at each of the study sites. They were trained by using virtual platform on how to use the paper-based clinical investigation reporting form (CRF) prior to data collection. The cases were enrolled while they were admitted for treatment at the hospital while the participants selected as controls were contacted telephonically. Their contact details and other pertinent clinical information were retrieved from hospital records. Confidentiality of the consenting participants was maintained, and patient identifiers were not entered in the CRF. They were requested to share their laboratory reports and treatment records on WhatsApp or via electronic mail (if not available from the hospital records).
Detection of variants through next generation sequencing
A subset of naso and oro-pharyngeal swab samples were transported to the ICMR-National Institute of Virology (ICMR-NIV), Pune in dry ice for next generation sequencing (NGS). Total RNA was extracted from 400 µl of each specimen using the Magmax™ Viral RNA/Pathogen RNA Extraction kit (Applied Biosystems, ThermoScientific, USA). Specimens with E gene Ct < 30 were processed for SARS-CoV-2 whole genome sequencing using the amplicon-based COVID Seq method (Illumina, USA) as per the instructions of the manufacturer. Total RNA was also tested for N and E subgenomic RNA (sgRNA). Viral gRNA and sgRNA were calculated using standard curve as described earlier [
14]. NGS was performed using the Covidseq kits as described earlier [
15].
Data management and analyses
Information collected on paper CRFs were entered in web portal designed by ICMR with unique login IDs for each participating site. Collation, validation, cleaning, and verification were carried out at the ICMR Headquarters. Chi-square test was used for trend analysis. Descriptive analyses of socio-demographic, clinical and laboratory profiles of all cases and controls were undertaken. Statistical analyses were performed using student ‘t’ or Mann Whitney U test as appropriate for continuous variables while categorical variables were compared using Chi-square or Fisher’s exact test. Probability at 5% level was considered as statistically significant. Multivariable logistic regression was used to identify factors associated with the development of CAM. Variables with significance at p value < 0.05 in bivariate analysis were included in logistic regression model. Doses of steroids such as dexamethasone, methylprednisolone and hydrocortisone were converted to equivalent doses of prednisolone and multiplied with the duration to obtain the administered cumulative dose. All statistical analyses were performed using R CRAN (version 4.0.2) software.
Ethical considerations
Approvals were obtained from the ICMR-Central Ethics Committee on Human Research and the Institutional Ethics Committee of each of the participating sites. Written informed consent was obtained from CAM cases while controls were contacted telephonically, and verbal consent was taken and recorded in the consent form by the interviewer. Parental consent was obtained for children aged less than 18 years. Verbal and written assent of child were obtained for children between 7 to 12 years and those above 12, respectively.
Discussion
The present multi-site, nationwide study clearly depicted that the trend of CAM cases in hospitals in India peaked during the month of May 2021, about a month following the peak in admission of COVID-19 cases in April of the same year. This could probably be explained by complex immune response due to SARS-CoV-2 infection leading to a stage of immunosuppression after the initial cytokine storm, particularly during the second week of infection [
16,
17]. Immunosuppression due to COVID-19 associated treatment with steroid could have further compounded this phenomenon. Noticeably, a similar occurrence of satellite epidemic of herpes zoster was recorded in the early 1990s following HIV epidemic induced immunosuppression among young injection heroin users in the north-eastern state of Manipur bordering Myanmar [
18].
The socio-demographic profile of CAM cases in our study were similar to that in other Indian studies from Chandigarh, Delhi and Pune, and an online Mycotic Infections in COVID-19 (MUNCO) registry [
8,
19‐
22]. Saprophytic fungi such as
Mucorales are found in ecological spaces such as soil, dust and decomposing vegetation [
23]. The results of the current study corroborated with this fact as more than one-fourth of the CAM cases (27.9%) reported dusty working environments such as either farming or gardening or both, whereas frequency of such occupational exposure among controls was only 14.7%.
Genomic sequencing of cases and controls showed a comparable presence of SARS-CoV-2 variants and did not reveal any specific association of mutation in either group. Variants of concern (Alpha, Delta and Delta derivates) or variants under investigation did not show any preferential distribution among CAM cases. However, the small sample size used in genomic sequencing precludes us from drawing any further inference from the same.
Uncontrolled DM is a known risk factor for mucormycosis. A systematic review of CAM cases globally, revealed diabetes to be a more frequently reported association from India than elsewhere (66.1% vs. 54.8%) [
24]. DM as a risk factor has been reported consistently from studies conducted across India during COVID-19 pandemic [
5,
19,
21,
22,
25]. There is emerging evidence of hyperglycemia induced increase in surface glucose-regulated protein (GRP78) expression on the endothelium, which in turn not only facilitates SARS CoV-2 entry by forming a complex with spike protein and angiotensin converting enzyme 2 (ACE2) receptors, but also mediates interaction with
Mucorales spores through spore protein homologue CotH3 and promotes endothelial invasion [
26,
27]. It is therefore important to monitor blood glucose levels during COVID-19 management and attain good glycemic control, with special attention on severe cases of COVID-19 who are on systemic corticosteroids.
Evidence is equivocal with respect to the role of supplemental oxygen during COVID-19 illness and subsequent development of CAM. While the current study and other studies on CAM showed higher requirement of oxygen among CAM cases during COVID illness [
8,
28], studies conducted in other Indian cities such as Delhi and Pune did not witness such association [
19,
21]. Interestingly, use of NRBM was found to be a protective factor against development of CAM in the current investigation. Use of high flow oxygen devices was reported to be lower in CAM group in study conducted in Delhi, India [
19]. Moreover, unhygienic ways to deliver oxygen or prolonged use of same mask for more than two patients has been hypothesized for occurrence of mucormycosis [
3].
Irrational corticosteroid use has been associated with development of many opportunistic infections including mucormycosis. Steroids induce immunosuppression by inhibiting macrophages and neutrophils and raise blood sugar levels, thereby increasing the risk of CAM. Inappropriate use of steroids during the second wave of COVID-19 pandemic could have resulted in prolonged hyperglycemia among pre-diabetic and diabetic patients, which in turn probably resulted in invasive mucormycosis. Corticosteroid use, one of the proven predisposing factors for mucormycosis, has not been recognized as an independent risk factor in the current study [
29]. However, we observed that the odds of developing CAM were nearly three times higher with the use of methylprednisolone as compared to dexamethasone. Though efficacy of both dexamethasone and methylprednisolone is comparable, preclinical studies have demonstrated a higher lung to plasma ratio for methylprednisolone compared with dexamethasone [
30]. We may hypothesize that this led to more severe immunosuppression, rendering the lung tissue incapable of getting rid of the fungal spores.
Strengths and limitations of the study
The current investigation was a large, multi-site study conducted across four regions of the country. Validated methods were used to ascertain cases and controls. However, the current study had a few limitations as well. The information related to laboratory parameters and treatment was retrieved from paper-based medical records, which were not uniformly available across all institutes, hence not included in the multivariate model. Due to the nature of data collection (i.e., telephonically for controls), detailed information on dusty environments, use of alternative medicines or over-the-counter purchase and usage of steroids could not be explored in the current investigation. Moreover, recall bias cannot be ruled out regarding information obtained from controls. Lastly, we did not explore the impact of climate of a place and hospital environment related factors (e.g., humidifiers in the ICUs) which could serve as a potential source for mucormycosis outbreaks [
31,
32]. However, this objective was beyond the scope of our investigation.
To conclude, CAM was found to be strongly associated with host factors such as diabetes mellitus and environmental factors such as working in dusty environment. Factors related to clinical management such as duration of hospital stay during COVID -19 illness and use of steroids increased the odds of CAM. On the other hand, oxygen supplementation through NRBM had a protective effect. Appropriate management of hyperglycemia, judicious use of steroids and use of NRBM during oxygen supplementation among COVID-19 patients thus emerged as potential intervention areas to prevent subsequent occurrence of mucormycosis.
Acknowledgements
Authors are grateful for the excellent support provided by Dr. Abhinendra Kumar, Mrs. Savita Patil, Ms. Manisha Dudhmal, Mr. Yash Joshi, Mr. Ajay Kumar, Mrs. Kaumudi Kalele, Ms. Pranita Gawande, Ms. Jyoti Yemul for processing of the samples for NGS at ICMR-NIV, Pune.
CONSORTIUM NAME: ICMR- Mucormycosis group
Anita M. Shete3, Triparna Majumdar3, Priya Abraham3, Anudita Bhargava4, Rupa Mehata4, Ripu Daman Arora4, Richa Tigga4, Gopa Banerjee5, Vijay Sonkar5, HS Malhotra5, Neeraj Kumar5, Rajashri Patil7, Chandrashekhar G Raut7, Kumkum Bhattacharyya8, Preetam Arthur9, L Somu9, Padma Srikanth9, Naresh K Panda10, Dipti Sharma10, Wasil Hasan11, Aftab Ahmed11, Meeta Bathla13, Sunita Solanki13, Hiren Doshi13, Yash Kanani12, Nishi Patel13, Zincal Shah13, Alok Kumar Tembhurne14, Chhaya Rajguru (Waghmare)16, Lalitkumar R Sankhe16, Shrinivas S Chavan16, Reetika Malik Yadav14, Vikas Deswal15, Kuldeep Kumar15
3ICMR-National Institute of Virology, Pune, India. 4All India Institute of Medical Sciences, Raipur, India, 5King George's Medical University, Lucknow, India. 7Dr. D. Y. Patil Medical College, Hospital and Research Centre, Pune, India. 8Institute of Post Graduate Medical Education and Research, Kolkata, India. 9Sri Ramachandra Medical College and Research Institute, Chennai, India. 10Post Graduate Institute of Medical Education and Research, Chandigarh, India. 11Jawaharlal Nehru Medical College Aligarh Muslim University, Aligarh, India. 12Smt. NHL Municipal Medical College, Ahmedabad, India. 13AMC MET Medical College, Ahmedabad, India. 14ICMR-NIIH, Mumbai, India. 15Medanta-The Medicity, Gurugram, India. 16Grant Government Medical College and Sir J.J Group of Hospitals, Mumbai, India.
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