ABSTRACT
Background Fungal infections, especially mucormycosis, have remarkably surged during the coronavirus disease 2019 (COVID-19) era, especially during the second wave peak of the pandemic raising the concern of the clinicians for the admitted patients. Steroid therapy, diabetes, and other immunocompromised states are more commonly associated with COVID-19-associated mucormycosis (CAM). Aim and objective The aim of this study is to ascertain the prevalence of fungal infections amidst the second wave of the COVID-19 pandemic and discern the associated risk factors. Materials and methods During the second peak of COVID-19, samples were received in the microbiology laboratory from all clinically suspected mucormycosis patients. These samples underwent processing for potassium hydroxide (KOH) wet mount, fungal culture on Sabouraud's dextrose agar (SDA) medium, and COVID-19 reverse transcription-polymerase chain reaction (RT-PCR) testing. All relevant clinical and associated risk factors were tabulated and analyzed. Results Among the 107 suspected cases of mucormycosis, 39 (36.4%) were confirmed positive for COVID-19 via RT-PCR, while 68 (63.6%) tested negative. Males exhibited a predominant infection rate, with the rhinocerebral system being the most commonly affected site. Significantly higher mortality rates were observed in COVID-19-associated mucormycosis (CAM) patients (33.4%) compared to those without COVID-19 (5.9%), with a notable p-value of 0.0005. CAM patients also demonstrated a higher frequency of ICU admissions (77%) compared to non-COVID-19-associated mucormycosis patients (21.4%), a statistically significant finding (p-value of 0.007). Additionally, immunocompromised states, diabetes, and the administration of oxygen therapy were identified as significant risk factors in CAM (p < 0.05). Notably, mucormycosis accounted for the majority of fungal isolates (48.27%) among COVID-19 patients. Conclusion Mucormycosis infection is more commonly seen in COVID-19-infected patients as compared to non-COVID-19 patients, especially with comorbidities such as diabetes mellitus, steroid usage, and other immunocompromised states.
ABSTRACT
INTRODUCTION: Lower respiratory tract infections (LRTIs) are a common cause of morbidity and mortality worldwide. Accurate identification of the pathogens causing LRTIs is crucial for ensuring of diagnostic and antibiotic stewardship. The Biofire Pneumonia Panel (BFPP) is a molecular diagnostic test that allows rapid detection of various bacterial and viral pathogens. In this study, we compared the performance of BFPP with standard culture methods for the detection of pathogens. MATERIALS AND METHODS: Respiratory samples from 70 patient with suspected LRTIs were tested using both BFPP and standard culture methods. The distribution of isolated bacterial pathogens was analyzed, and the sensitivity and specificity of BFPP were calculated. Additionally, the performance of BFPP in detecting antimicrobial resistance genes was evaluated. The results were compared with those obtained from VITEK-2 antimicrobial susceptibility testing and culture-based methods. RESULTS: Among the suspected LRTI cases, BFPP identified a single pathogen in 32.8% of cases and multiple pathogens in 40% of cases. The standard culture method detected a single pathogen in 47.1% of cases. BFPP showed a sensitivity of 93.9% and a specificity of 45.9% for the total sample. The performance of BFPP in detecting antimicrobial resistance genes varied for different pathogens with overall sensitivity of 40.1% and specificity of 95.9%. CONCLUSION: The Biofire Pneumonia Panel (BFPP) demonstrated high sensitivity for several bacterial pathogens, indicating its potential as a rapid diagnostic tool. However, its performance varied for different microorganisms, and it had limitations in detecting certain pathogens and antimicrobial resistance genes for which still required more further studies to explore different resistance gene mechanism that can be incorporated in this panel in future. The BFPP can complement standard culture methods as a rapid tool in the diagnosis of LRTIs.
