Review of fine needle aspiration cytology in the management of goitres in Ibadan, Nigeria.

Niger J Clin Pract

Department of Surgery, College of Medicine, University of Ibadan, University College Hospital, Ibadan, Oyo State, Nigeria.

Published: June 2010

Objective: The use of Fine Needle Aspiration Cytology (FNAC) in the investigation of goitres was introduced into our practice more than a decade ago. This is a review of its diagnostic accuracy for thyroid carcinoma seven years after the first evaluation and following the establishment of the 'FNAC Clinic'.

Method: This is a retrospective study of patients who had FNAC of goitres and the histopathology of their thyroidectomy specimens between 1995 and 2004. The accuracy of the cytology reports were evaluated against the histology reports. The turnaround time of the patients for surgery was also determined.

Results: There were 130 females and 21 males with an age range of 7-86 years. The diagnostic accuracy of the procedure for carcinoma was 89% with a sensitivity of 35%, specificity of 97%, positive predictive value of 64%, and a negative predictive value of 91%. The average turnaround time for surgery was 178.7 +/- 248.7 days with a range of five days to three and a half years.

Conclusion: The diagnostic accuracy of FNAC of goitre for carcinoma improved in the period under review. However, the long surgery turnaround time may reduce the usefulness of the procedure. The accuracy may be improved further by a protocol of ultrasound guidance, capillary collection with no-aspiration technique, on-site review of slides with a repeat of FNA as necessary.

Download full-text PDF

Source

Publication Analysis

Top Keywords

diagnostic accuracy
12
turnaround time
12
fine needle
8
needle aspiration
8
aspiration cytology
8
accuracy
5
review
4
review fine
4
cytology management
4
management goitres
4

Similar Publications

Objective: This study evaluated the diagnostic value of plasma Neutrophil extracellular traps (NETs) levels and the index of cardiac electrophysiological balance (iCEB) in identifying silent myocardial ischemia (SMI) in maintenance hemodialysis (MHD) patients.

Methods: This cross-sectional observational study involved patients receiving MHD treatment. Data were collected on coronary angiography performed in our hospital from February 2023 to February 2024.

View Article and Find Full Text PDF

Background: Cardiac autonomic neuropathy (CAN) is a significant complication in chronic kidney disease (CKD), leading to increased morbidity and mortality. Early detection is essential for managing CKD patients effectively, especially those on hemodialysis. This study evaluated the prevalence CAN in CKD and diagnostic accuracy of Bellavere's Score in predicting CAN in CKD patients, including those undergoing hemodialysis.

View Article and Find Full Text PDF

Tuberculous meningitis diagnosis and treatment: classic approaches and high-throughput pathways.

Front Immunol

January 2025

Rehabilitation Medicine Department, The Affiliated Changsha Hospital of Xiangya School of Medicine, Central South University (The First Hospital of Changsha, Changsha, China.

Tuberculous meningitis (TBM), a severe form of non-purulent meningitis caused by (Mtb), is the most critical extrapulmonary tuberculosis (TB) manifestation, with a 30-40% mortality rate despite available treatment. The absence of distinctive clinical symptoms and effective diagnostic tools complicates early detection. Recent advancements in nucleic acid detection, genomics, metabolomics, and proteomics have led to novel diagnostic approaches, improving sensitivity and specificity.

View Article and Find Full Text PDF

Introduction: The transition to electric vehicles (EVs) has highlighted the need for efficient diagnostic methods to assess the state of health (SoH) of lithium-ion batteries (LIBs) at the end of their life cycle. Electrochemical Impedance Spectroscopy (EIS) offers a non-invasive technique for determining battery degradation. However, automating this process in industrial settings remains a challenge.

View Article and Find Full Text PDF

Objective: To design a deep learning-based model for early screening of diabetic retinopathy, predict the condition, and provide interpretable justifications.

Methods: The experiment's model structure is designed based on the Vision Transformer architecture which was initiated in March 2023 and the first version was produced in July 2023 at Affiliated Hospital of Hangzhou Normal University. We use the publicly available EyePACS dataset as input to train the model.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!