The Role of a Pre-Fine Needle Aspiration Clinic in Improving the Quality of Thyroid Nodule Investigation in Saskatchewan
Bibliographic record
Abstract
Background: The Canadian province of Saskatchewan introduced a pre-fine needle aspiration (FNA) clinic to review adherence of referrals for thyroid biopsy based on the guidelines of the American College of Radiology’s (ACR) Thyroid Imaging, Reporting and Data System (TI-RADS) scoring system. The intention is to minimize low-yield biopsy rates by improving the quality of thyroid nodule investigation in Saskatchewan through this clinic. TI-RADS is a malignancy risk scoring system for thyroid nodules based on five sonographic characteristics: composition, echogenicity, shape, margin, and echogenic foci (calcium). Recommendations for intervention or clinical follow-up are further determined by the size of the nodule. Methods: Through a retrospective chart review of all thyroid biopsy referrals to the Royal University Hospital (RUH) in Saskatchewan between 22 March 2016 and 17 May 2018, the impact of the multidisciplinary pre-FNA clinic on appropriate thyroid biopsies in Saskatchewan was evaluated. Results: This study evaluated 252 referrals, 203 of which underwent FNA and 23 which received surgical biopsy. TI-RADS scores appended to thyroid biopsy referrals increased upon pre-FNA clinic initiation, yet score quality did not improve. Rates of malignant biopsies were lower than ACR-reporting suggesting inappropriate biopsy of low risk nodules perhaps by overcalling the TI-RADS score. The majority of FNA cytology matched final surgical pathology, with 78% of indeterminate FNAs being malignant, and all non-diagnostic FNAs being benign. Conclusions: The implementation of the pre-FNA clinic reduced the number of thyroid biopsies in Saskatchewan by 11% overall.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.000 | 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".