The Diagnostic Value of Fine-Needle Aspiration Cytology in Cervical Lymphadenopathy in Correlation to Postoperative Histopathological Results in a Tertiary Care Center in Saudi Arabia

沙特阿拉伯一家三级医疗中心细针穿刺细胞学检查在颈部淋巴结肿大诊断中的价值及其与术后组织病理学结果的相关性研究

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Abstract

Background Lymphadenopathy is a frequently encountered presentation in the clinical practice. Cervical lymphadenopathy implies that the cervical nodal tissue measures more than 1 cm in diameter. It requires prompt and accurate diagnosis to begin an appropriate treatment plan. Fine-needle aspiration cytology (FNAC) is considered an initial diagnostic method due to its simplicity, minimal invasiveness, quick availability of results, and low risk of complications. This study aimed to evaluate the diagnostic value of FNAC by comparing the cytological and histological diagnoses of patients with cervical lymph node enlargement at Aseer Central Hospital, Southern Region, Saudi Arabia. Methodology This observational, retrospective, record review study was conducted at the Otorhinolaryngology Head and Neck Surgery Department in Aseer Central Hospital, Abha, Saudi Arabia. Using a data collection sheet, the data of 102 patients were collected from electronic records and reviewed retrospectively. The study included patients who underwent cervical lymph node excision biopsy between 2020 and 2023 due to enlargement of the cervical lymph node. The cytological diagnoses were compared with the histopathological diagnoses of the same enlarged cervical lymph nodes. Results The most common FNAC findings were lymphomas and reactive lymph nodes (26.2% and 19.7%, respectively). The positive predictive value of FNAC was 100% and the negative predictive value was 86.7%. Overall, the diagnostic accuracy was 95.3%. Conclusions FNAC is a safe diagnostic method with minimal invasiveness and complications. This study showed that FNAC and tru-cut biopsy have good diagnostic value in examining patients with cervical lymphadenopathy regardless of their limitations and drawbacks. They have good sensitivity, specificity, positive and negative predictive values, and accuracy.

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