Pediatric thyroid nodules: ultrasonographic characteristics and inter-observer variability in prediction of malignancy
Bibliographic record
Abstract
BACKGROUND: Pediatric thyroid nodules, while uncommon, have high malignancy risk. The objectives of the study were (1) to identify sonographic features predictive of malignancy; (2) to create a prediction model; and (3) to assess inter-observer agreement among radiologists. METHODS: All available cases of thyroid nodules, surgically removed between 2000 and 2009. Three radiologists reviewed the sonographic images; 2 pathologists reviewed the tissue specimens. Adult prediction models were applied. Interobserver variability was assessed. RESULTS: Twenty-seven subjects, mean age 13.1±3.4 years, were included. Nineteen nodules were differentiated thyroid carcinomas. On multivariate analysis, size was the only significant predictor of malignancy. On recursive partitioning analysis, size >35 mm with microcalcification and ill-defined margins yielded the best prediction model. Radiologist inter-observer agreement regarding malignancy was moderate (κ=0.50). CONCLUSIONS: Larger size, microcalcifications and ill-defined margins on ultrasound demonstrate the best predictive model for malignancy in the pediatric population. Experienced pediatric radiologists demonstrate moderate inter-observer agreement in prediction of malignancy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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".