Pattern of Thyroid Lesions in Western Region of Saudi Arabia: A Retrospective Analysis and Literature Review
Bibliographic record
Abstract
BACKGROUND: Ultrasonography (US) is being recognized as a traditional way of the diagnosis of various thyroid disorders, and this will help in detecting the thyroid tumors in early stage. Thyroid nodules are common and usually benign; steps to diagnose malignancy should include a careful clinical evaluation, laboratory tests, a thyroid US exam and a fine-needle aspiration (FNA) biopsy. METHODS: A total of 173 registered cases were used for analysis in this study. Diagnosis was made following US-guided FNA cytology (FNAC) and histopathological diagnosis; clinicopathological and demographic data of all such patients were obtained and analyzed for the present study. For statistical analysis, Statistical Package of Social Sciences v.22 (SPSS) was used. RESULTS: In the current study, 87.3% of patients were female, and 12.7% were male. The mean age of the patients was 43.35 years, 86.4% were Saudi nationals and there was no significant difference between age groups. Overall, the distribution of lesions in all age groups was 41.6% in the right lobe, 9.3% lesions were adenomatous, 71.1% were colloid, and 10.4% were lymphocytic. The final diagnosis of thyroid lesions was confirmed after histopathological examinations. Out of 173 cases, 12.6% (20 cases) of male patients and 87.4% (139 cases) of female patients had benign lesions, respectively. Only one male case was malignant, and seven cases were malignant in female group. Eighty percent of males and 77.7% females have colloid nodules, and 15% of males and 9.3% of females have adenomatous nodules. Four cases were non-diagnostic, one case was atypia in females, and one case was suspicious of malignancy in a male. CONCLUSIONS: Most thyroid lesions in this study population were benign, while papillary carcinoma was the most common malignancy encountered. There was a marked female predominance in all types of thyroid diseases. The most common age group affected is 30 - 39 years. In Saudi Arabia, growing prevalence of thyroid cancer may be due to the increased screening using sensitive imaging in clinical practice, and ultrasonography is the most accurate and cost-effective method for detecting thyroid lesions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".