Thyroid Biopsy Specialists: A Quality Initiative to Reduce Wait Times and Improve Adequacy Rates
Bibliographic record
Abstract
PURPOSE: To develop and implement a program where selected sonographers would be trained to perform thyroid biopsies independently under the supervision of a radiologist, with the goal of improving efficiency and quality. MATERIALS AND METHODS: Institutional research ethics board approval was obtained for this retrospective study, with waiver of informed consent. After approval from the relevant regulatory bodies, four sonographers successfully completed a training program and began to perform all thyroid biopsies (with informed consent) in a room adjacent to the main radiologist-run biopsy room, where the radiologist was available for backup as needed. In the preimplementation period (January 2010 to April 2011), 1321 nodules were biopsied, 29 of which included on-site cytopathology assessment. In the postimplementation period (August 2011 to July 2012), 1347 nodules were biopsied, 103 of which underwent on-site cytopathology assessment. Wait times and adequacy rates were calculated for both periods. RESULTS: Patient wait times decreased from a mean of 80-90 days before implementation of the thyroid biopsy specialist program to 20-30 days afterward. The percentage of adequate samples improved from 74.6% (985 of 1321 nodules) to 78.6% (1059 of 1347 nodules), with a P value of .015 (74.1% [957 of 1292 nodules] to 77.5% [964 of 1244 nodules] when excluding nodules with on-site cytopathology assessment, P = .0497). The percentage of malignant samples showed no significant change in the two time periods, 5.1% (68 of 1321 nodules) before implementation of the program versus 5.4% (73 of 1347 nodules) after implementation, P = .823 (5.1% [66 of 1292 nodules] vs 5.3% [66 of 1244 nodules] in the respective time periods when excluding nodules with on-site cytopathology assessment, P = .888). No major procedural complications occurred. CONCLUSION: Sonographers can be successfully trained to perform ultrasonography-guided thyroid biopsies safely under the supervision of a radiologist, which can improve wait times and adequacy rates.
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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 | 0.009 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".