@article{Ashish Joshee_Rajni Joshee_2022, title={Lymph node FNA cytology reporting using new proposed IAC sydney system for reporting lymph node cytology- A single institution retrospective study}, volume={5}, url={https://ijhcr.com/index.php/ijhcr/article/view/4304}, abstractNote={<p>Introduction: Lymph node enlargement is a common clinical finding in a wide spectrum of diseases and its evaluation is essential for proper patient care. Fine needle aspiration cytology has been used as an initial diagnostic method in such conditions especially for infective conditions and also to differentiate between benign and malignant lesions. A standardized category based cytology reporting system was proposed by IAC in 2019 which gives 5 categories of cytological diagnosis and also provides management category for each class. Aim and Objectives: The present study aims to analyze and classify lymph node samples as per new proposed Sydney system and also to assess the risk of malignancy of each category. Material and Methods: This single institution retrospective study included lymph node FNAC cases over 5 year duration. Clinical details of all included cases were recorded. Cytology aspirate slides were reevaluated as per new reporting system. Histopathology correlation was done in cases where possible. Statistical analysis was done. Results: 1409 lymph node aspirates were evaluated with cases having slight male predominance and average age of 31.24 years. Benign category diagnosis was most common. Overall the most common diagnosis was reactive hyperplasia of lymph node. Metastatic squamous cell carcinoma was most common malignant diagnosis. Risk of malignancy calculated after histopathological correlation was highest in malignant category where it was 96.7%. Diagnostic accuracy of the new system in current study was 94.16%. Conclusion: Using standard categorical cytology reporting system will allow improved reports and clinical communication for better patient care.</p>}, number={3}, journal={International Journal of Health and Clinical Research}, author={Ashish Joshee and Rajni Joshee}, year={2022}, month={Jan.}, pages={95–99} }