FREQUENCY OF INVASIVE FUNGAL RHINOSINUSITIS AMONG COVID-19 PATIENTS OF PESHAWAR

Background: Acute invasive fungal rhinosinusitis (AIFR) has emerged as a severe opportunistic infection in patients with COVID-19, particularly among those with underlying immunocompromising conditions. While isolated case reports dominate existing literature, studies estimating the overall frequency of AIFR among SARS-CoV-2-infected individuals remain limited. Understanding its prevalence is essential for guiding early clinical suspicion, timely diagnosis, and effective management, especially in high-risk populations and resource-constrained healthcare settings. Objective: To determine the frequency of acute invasive fungal rhinosinusitis in patients diagnosed with COVID-19. Methods: This descriptive cross-sectional study was conducted at the ENT Department of Khyber Teaching Hospital, Peshawar, from 16th March 2023 to 15th September 2023. A total of 298 patients aged 10–60 years with confirmed COVID-19 via RT-PCR were enrolled using non-probability consecutive sampling. Patients with prior sinonasal surgery, facial trauma, known malignancy of the sinuses, or chronic immunosuppressive disorders unrelated to COVID-19 were excluded. Fungal sinusitis was suspected clinically and confirmed by direct microscopic examination of sinonasal tissue samples immersed in 10% potassium hydroxide (KOH). Histopathological evaluation was also performed to validate tissue invasion. Results: The mean age of participants was 57.85 ± 7.99 years, mean BMI was 25.12 ± 1.01 kg/m², and the average duration of illness was 7.79 ± 2.65 days. Of the 298 patients, 202 (67.8%) were older than 55 years, and 152 (51.0%) were female. A BMI over 25 kg/m² was observed in 134 patients (45.0%), and 124 (41.6%) were smokers. Invasive fungal rhinosinusitis was confirmed in 65 cases, yielding a frequency of 21.8%. Conclusion: AIFR was found in a considerable proportion of COVID-19 patients, particularly among elderly individuals and those with metabolic risk factors. Early identification is crucial to reduce morbidity and improve outcomes.