A Retrospective Epidemiological Analysis of Fungal Infections of Skin and Soft Tissue in a Health Care Setup in Delhi, India

Introduction: Fungal infections of the skin and soft tissue can be an important cause of morbidity and mortality in both immunocompromised and immunocompetent patients and usually pose a major diagnostic challenge. Aim: The present study was done to study the type of fungal isolates from pus and soft tissue specimens and to clinically correlate these fungal isolates. Materials and Methods: A retrospective analysis of fungal isolates from pus and soft tissue specimens was done over a period of one year and their clinical history was studied from medical records department. The identification of yeast isolates was done by automated (MALDI-TOF-Vitek MS and Vitek-2) and conventional methods and mycelial fungi were identified by lactophenol cotton blue mount of growth and/or slide culture. Results: Out of 288 pus/tissue specimens received for fungal culture during the study period, 37 showed growth of fungi. Out of 37 fungi, 24 were yeast isolates and 13 were mycelial fungi. Candida albicans (24.3%) constituted the majority of the fungal infections followed by Candida glabrata (21.6%), Aspergillus sp. (18.9%) and Dematiaceous fungi (13.5%). All the Dematiaceous fungi were isolated from post-transplant patients. Out of 37 patients, 12 were immunocompromised and 22 had history of surgery. Antifungal resistance was not seen in C. albicans while Candida haemulonii/auris showed 100% resistance to amphotericin B and fluconazole. All the patients in our study had history of prior antibiotic intake for one or other reasons. In contradiction to leucopenia, many of the patients in our study had leucocytosis at the time of isolation of fungi. Conclusion: A variety of fungi may cause pus and soft tissue infections in both immunocompromised and immunocompetent individuals. The results signify the importance of clinicomycological awareness, correlation, fungal speciation and trend of antifungal susceptibility pattern for the optimum treatment of the patients.