Ultrasound Guided FNAC for Evaluation of Neck Lumps to Improve Inadequacy Rates; A Complete Audit Cycle
Bibliographic record
Abstract
We present a completed audit cycle evaluating inadequacy rates in neck lump and thyroid fine needle aspiration cytology with and without ultrasound scan guidance. The first cycle of the audit was from January to July 2010 comparing free hand fine needle aspiration cytology (FNAC) with ultrasound guided fine needle aspiration cytology (USS+FNAC). Changes to practice were made, firstly all thyroid FNAC would be performed with USS+FNAC and a reduced threshold for referral for USS+FNAC for non-thyroid neck masses. The second audit cycle was completed sixteen months later to assess for an improvement in practice. 1st phase; 155 patients, 70 freehand, 85 USS+FNAC. 50% of the thyroid FNAC freehand were inadequate compared to 18% of the thyroid USS+FNAC. 2nd phase; 196 patients, USS+FNAC 134, freehand 62. Thyroid FNAC 105 (USS+FNAC-104, freehand-1). Inadequate USS+FNAC = 21/104 (20%). The completed audit cycle shows an increased proportion of thyroid FNACs performed by ultrasound guidance, improving from 82% to 99%, with an overall reduction of inadequate thyroid FNACs from 24% to 21%. There was a noticeable variability in the inadequacy rates from radiologist to radiologist with the head and neck senior radiologist demonstrating the lowest inadequacy rate at 9.6% in the second cycle. Although ultrasound guidance for FNAC is important for the reasons of increased sensitivity, specificity and accuracy, we have demonstrated that the operator experience and skill are just as important.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.028 | 0.059 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".