Clinical diagnostic utility of ultrasound-guided fine needle aspiration biopsy in parotid masses
Bibliographic record
Abstract
BACKGROUND: Fine needle aspiration (FNA) is a common diagnostic tool used in the initial evaluation of parotid masses. In the literature, variable diagnostic accuracy of FNA is reported. Therefore, when considering clinical management of these patients, the utility of FNA is unclear. The aim of this study was to determine the capability of ultrasound-guided FNA to differentiate between benign and malignant neoplasms. Further, the way in which FNA results affect clinical decision-making was assessed. METHODS: Retrospective data were collected for all patients who underwent parotidectomy at a large Canadian tertiary care center between 2011 and 2016. Patient demographics, preoperative imaging reports, preoperative FNA results, and final pathological diagnosis were analyzed. RESULTS: Of the 199 patients who underwent parotidectomy, 184 had preoperative ultrasound-guided FNA. There were a total of 13 non-diagnostic FNAs. In diagnosing malignancy, FNA had a sensitivity and specificity of 71.4% and 98.7%, respectively. The positive predictive value (PPV) was 83.3%. The negative predictive value was 97.5%. Of the non-diagnostic FNAs, 2 out of 13 (15.4%) were deemed malignant neoplasms on final pathology. CONCLUSION: FNA is a useful adjunct in the work-up of parotid masses, but it should be used with caution. Due to limited sensitivity, it should not be relied upon as the sole determinant of a surgeon's management plan.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".