European Journal of Cardiovascular Medicine

The COVID-19 pandemic has been accompanied by a surge in secondary infections, particularly invasive fungal infections, in severely affected regions such as India. While bacterial superinfections were initially the most commonly reported, the emergence of opportunistic fungal infections—most notably mucormycosis—during the pandemic prompted significant clinical concern. Mucormycosis, caused by fungi of the order Mucorales, is an angio-invasive infection that can rapidly progress, especially in immunocompromised individuals, and has been associated with high morbidity and mortality rates if not promptly diagnosed and treated.1

India witnessed an unprecedented rise in COVID-19-associated mucormycosis (CAM) cases during the second wave, primarily among individuals with uncontrolled diabetes mellitus and those receiving corticosteroids for COVID-19 management (2,3). The Indian Ministry of Health and Family Welfare declared mucormycosis a notifiable disease on May 10, 2021, following over 41,000 reported CAM cases, largely attributed to improper steroid usage, hyperglycaemia, and oxygen therapy during hospitalization (4).

Conventional mycological techniques, including direct microscopy, culture, and slide culture followed by Lactophenol Cotton Blue (LPCB) staining, have historically been used to identify fungal pathogens. These methods, however, are time-consuming, often requiring up to a week for definitive identification, and are highly dependent on expert interpretation [5]. Furthermore, species-level identification is particularly challenging using conventional techniques alone, especially among morphologically similar fungi within the Mucorales order [6].

Recent advances in diagnostic mycology have introduced Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry (MALDI-TOF MS) as a rapid and reliable tool for the identification of microbial pathogens, including filamentous fungi [7,8]. MALDI-TOF identifies organisms by analyzing unique protein spectra and comparing them to reference databases, enabling species-level identification with high accuracy and significantly reduced turnaround time [9].

Given the urgent need for rapid diagnosis and the limitations of conventional methods, this study aims to evaluate the performance of MALDI-TOF MS in comparison to traditional culture and microscopy techniques for the identification of fungal isolates in clinically suspected CAM cases. This approach is intended to improve diagnostic accuracy, guide timely antifungal therapy, and enhance our understanding of the evolving epidemiology of mucormycosis during the COVID-19 pandemic.

This descriptive observational study was conducted in May 2021 to April 2023 at tertiary care hospitals in Telangana and Andhra Pradesh, India. The study population included 100 clinically suspected cases of COVID-19-associated mucormycosis (CAM), selected based on clinical symptoms suggestive of mucormycosis and a documented history of SARS-CoV-2 infection confirmed by RT-PCR. Ethical clearance was obtained from the Institutional Ethics Committee, and written informed consent was obtained from all participants.

Biopsy or debrided tissue samples were collected from suspected CAM cases under aseptic conditions. Each specimen was subjected to a series of diagnostic procedures. Initially, direct microscopy was performed using a 10% potassium hydroxide (KOH) wet mount and Calcofluor white staining to detect fungal elements, including hyphal morphology and branching patterns. Samples were subsequently cultured on Sabouraud Dextrose Agar (SDA) and Dichloran Rose Bengal Chloramphenicol Agar (DRBC) and incubated at 25–30°C for up to seven days. Fungal colonies were assessed macroscopically for texture, pigmentation, and sporulation, and microscopically using Lactophenol Cotton Blue (LPCB) mounts prepared from culture growth. [5].

Conventional fungal identification relied on colony morphology, slide culture, and microscopic features observed in LPCB preparations. Identification was generally limited to the genus level due to the morphological similarities among species of Mucorales. Although conventional methods are widely practiced, they are time-consuming and dependent on experienced personnel, and may not always achieve species-level resolution [10].

For rapid and precise identification, Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry (MALDI-TOF MS) was employed. Well-sporulated fungal isolates were harvested using sterile cotton swabs. Protein extraction was performed using a standard ethanol–formic acid protocol as previously described in microbial identification workflows [11,12]. The prepared samples were analyzed using the VITEK MS system (bioMérieux), which integrates the SARAMIS™ (Spectral Archiving and Microbial Identification System) database. Identification confidence was considered valid at a threshold of ≥60% for species-level assignment, in accordance with manufacturer guidelines and published standards [13].

Clinical and epidemiological data were collected through a combination of patient interviews and review of medical records. The data included patient demographics (age, sex), COVID-19 disease severity (mild, moderate, severe), comorbidities such as diabetes mellitus and hypertension, and treatment history. Particular attention was given to risk factors including corticosteroid therapy (dose and duration), oxygen therapy, antibiotic and antiviral use, mineral supplementation (e.g., zinc), steam inhalation practices, and mask usage behaviour, including type of mask and frequency of reuse.

All collected data were entered into Microsoft Excel and analyzed using Epi Info version 7. Continuous variables were expressed as means with standard deviations, while categorical variables were presented as percentages. The identification results obtained from MALDI-TOF MS were compared with conventional methods for concordance at both genus and species levels. Due to the descriptive nature of the study, statistical comparisons were limited to frequency distributions and proportions.

Demographic and Clinical Characteristics

A total of 100 patients with clinically suspected COVID-19-associated mucormycosis (CAM) were enrolled. The mean age of the study population was 47.6 ± 1.93 years, with a male predominance (77%). The median time interval between COVID-19 diagnosis and onset of CAM symptoms was 12.8 ± 1.58 days, ranging from 3 to 44 days.

The majority of cases (96%) presented with rhino-orbital mucormycosis (ROCM), while pulmonary mucormycosis (PMM) was noted in 4% of cases. The most common presenting symptoms were orbital pain, periorbital swelling, ptosis, and visual disturbances, observed in 89% of patients. Headache was reported in 38%, followed by facial numbness and swelling in 29%, nasal discharge or obstruction in 28%, and loosening of teeth in 15%. Classical signs like necrotic patches were seen in only 5%, while fever was present in 16% of patients.

Table 1: Findings on KOH mount

Table 2: Fungal isolates identified by Conventional method

Table 3: Species level identification by MALDI TOF and its spectrum

Table 4: Comparison between Conventional and MOLDI TOF

Risk Factors

Among all patients, 97% had diabetes mellitus; 47% were known diabetics, while 50% were diagnosed with de novo diabetes during or after COVID-19. Hypertension (25%), obesity (7%), chronic kidney disease (2%), and hypothyroidism (2%) were other recorded comorbidities. Steroid therapy was reported in 74% of cases, with an average dose of 37.8 mg/day and mean duration of 10.6 days. However, only 30% of patients had documented dosing information.

Hospitalization during COVID-19 illness was reported in 72% of patients, with 53% having received oxygen therapy. Antibacterial usage was reported in 74% of cases, antiviral drugs in 42%, and mineral supplementation (primarily zinc) in 42%. Steam inhalation was practiced by 54%. Only 54% of patients reported mask usage post-COVID-19 diagnosis, of whom 41% used cloth masks, 13% surgical masks, and 3% N95 masks. Notably, 24% admitted to reusing masks beyond 24 hours without proper cleaning.

Microscopy and Culture Findings

Direct microscopic examination using KOH and Calcofluor white staining revealed broad, pauci-septate hyphae in 82% of cases, characteristic of Mucorales. Narrow septate hyphae (suggestive of Aspergillus spp.) were observed in 2%, while mixed morphologies, including combinations of septate hyphae and yeast forms, were seen in 15% of specimens. (Fig 2, Table 1)

Culture positivity was observed in 73 out of 100 samples (73%). Of these, the most commonly isolated genus by conventional methods was Rhizopus (44%), followed by Aspergillus spp. (7%), Rhizomucor (3%), Mucor spp. (2%), and Fusarium spp. (1%). Mixed fungal growth involving combinations of Mucorales and Aspergillus was noted in 8% of culture-positive samples. Candida spp. was isolated in 2%, and 30% of samples did not yield growth. (Table 2 & Fig 3)

MALDI-TOF MS Identification

Among the 73 culture-positive isolates, 40 were further processed and successfully identified using MALDI-TOF MS. There was 100% concordance at the genus level between MALDI-TOF and conventional methods. The most frequently identified species was Rhizopus microsporus (40%), followed by R. arrhizus (32%), Aspergillus flavus (11%), A. terreus (3%), A. niger (3%), and A. ochraceous (3%). Rare isolates included Rhizopus homothallicus (3%), Candida albicans (3%), and Mucor irregularis (2%). (Table 3 & Fig 4)

Comparison between Conventional identification & MALDI-TOF MS Identification

Conventional identification was largely limited to genus-level classification, whereas MALDI-TOF enabled species-level resolution. All Rhizopus spp. identified conventionally were resolved into R. arrhizus, R. microsporus, or R. homothallicus by MALDI-TOF. Similarly, among Aspergillus spp., conventional identifications as A. flavus were further differentiated into A. flavus, A. terreus, and A. ochraceous. These findings demonstrate MALDI-TOF's superior utility for detailed fungal profiling.

One isolate that was identified as Aspergillus flavus by conventional morphology was reclassified as A. ochraceous via MALDI-TOF, highlighting the superior discriminatory power of this technique. Spectral confidence scores for all identifications exceeded 99.9%, confirming the robustness of the method. (Table 4)

The present study evaluated the clinical profiles, risk factors, and fungal species isolated from cases of COVID-19-associated mucormycosis (CAM), and compared the diagnostic performance of conventional mycological methods with MALDI-TOF MS. Our findings reinforce the alarming rise of CAM during the second wave of COVID-19 in India and highlight the role of MALDI-TOF as a rapid, accurate alternative for fungal species identification.

Demographically, the study population had a mean age of 47.6 years and showed male predominance (77%), consistent with reports by Pal et al. (78% males, mean age 52 years) and Hoenigl et al. (77% males, mean age 55 years) [13,14]. The majority of mucormycosis cases in our study were rhino-orbital (96%), with only 4% showing pulmonary involvement, which mirrors the typical clinical distribution observed in other Indian cohorts [15,16].

Diabetes mellitus was identified as the most prominent risk factor, present in 97% of our study population. Of note, 50% of these cases were newly diagnosed during or shortly after COVID-19 infection. Similar findings were reported by Sen et al. (78%) and Ramaswami et al. (70%), establishing hyperglycaemia—either pre-existing or steroid-induced—as a critical driver of CAM [15,17]. The injudicious use of corticosteroids, observed in 74% of our patients, is another major factor. Many of these patients received higher-than-recommended doses even for mild COVID-19 illness, echoing findings by Pal et al. and Mishra et al. [13,16]. This inappropriate steroid uses likely exacerbated glycaemic control and immune suppression, creating an environment conducive to fungal proliferation.

Oxygen therapy, hospitalization, antibiotic and mineral supplement use, and poor mask hygiene were also observed in a large proportion of our study population. Oxygen therapy (53%) and hospitalization (72%) have been cited as independent risk factors in previous studies, possibly due to contaminated equipment or hospital environments [15,19]. Reuse of cloth masks beyond 24 hours was reported by 24% of participants in our cohort, an emerging concern in community-level CAM prevention.

On direct microscopy, most samples (82%) exhibited broad, pauci-septate hyphae typical of Mucorales, while 15% showed mixed fungal forms. Mixed fungal infections, particularly co-infections with Aspergillus, are increasingly reported, and in our study, Aspergillus spp. were identified in 7% of cases by conventional culture, with an additional 8% showing mixed growth of Mucorales and Aspergillus [19].

Culture-based identification, although fundamental in clinical mycology, yielded results in only 70% of cases and was limited to genus-level classification. Rhizopus spp. (44%) were the most commonly isolated fungi, in agreement with the literature [13,15,16]. However, species-level identification by conventional methods is inherently restricted due to the morphological similarities among Mucorales genera.

MALDI-TOF MS proved superior in this context by identifying 40 out of 73 culture-positive isolates at the species level. The most frequent species were Rhizopus microsporus (40%) and R. arrhizus (32%), which are consistent with those reported by Hoenigl et al. and Chander et al. [14,20]. A notable finding was the re-identification of a conventional Aspergillus flavus isolate as A. ochraceous, a rare and potentially toxigenic pathogen. Aspergillus ochraceous has been reported in a few case studies involving invasive infections, such as osteomyelitis and disseminated aspergillosis, particularly in immunocompromised hosts [21,22]. Its identification using MALDI-TOF underscores the importance of accurate species resolution in clinical decision-making.

The 100% genus-level concordance between MALDI-TOF and conventional methods in our study affirms its reliability. Moreover, MALDI-TOF significantly reduced identification turnaround time and eliminated the dependence on mycological expertise. Its diagnostic performance in fungal identification has been previously validated in both yeast and mold species [23].

Despite these strengths, our study has limitations. Only 40 of the 73 culture-positive samples were processed by MALDI-TOF due to logistic constraints. Also, data on inflammatory markers like serum ferritin and CRP were insufficient to determine their predictive value.

The study demonstrates that MALDI-TOF MS offers a rapid, reliable, and accurate alternative to conventional methods for species-level fungal identification in CAM. With India bearing the brunt of the global mucormycosis burden, integrating such technologies in routine diagnostics is imperative for effective epidemiological surveillance and antifungal stewardship

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