Thyroid Colloid Nodules Diagnosed by Fine-Needle Aspiration: Efficacy of Suppression
Bibliographic record
Abstract
BACKGROUND: This study reviewed the accuracy of fine-needle aspiration biopsy (FNAB) and the efficacy of thyroid suppression for colloid nodules in our population to determine the utility of these two modalities on the decision to operate. METHODS AND MATERIALS: A retrospective chart review of patients with colloid nodules diagnosed by FNAB from January 1993 to July 1995 was conducted. A 52-patient cohort underwent surgical management, and their needle aspirate cytologies and final pathologies were reviewed. RESULTS: A 7.7% false-negative rate in the detection of thyroid malignancy by FNAB was obtained. This is in keeping with data reported in the literature. Virtually no efficacy of hormonal suppression in our population was found. CONCLUSION: When the literature is reviewed and compared with the results of this study, the use of FNAB as a decision tool to operate is valid. The decision to operate based on the outcome of hormonal suppression, however, is not valid based on our results.
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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 | 0.002 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".