Patterns and Predictors of Metastatic Spread to the Neck in Pediatric Thyroid Carcinoma
Bibliographic record
Abstract
OBJECTIVE: Evaluate patterns and predictors of spread to the neck in pediatric metastatic differentiated thyroid carcinoma (DTC). METHODS: Patients <18 years old undergoing thyroidectomy by a single surgeon from January 2015 to December 2019 were included. Neck sublevels were removed separately according to AJCC boundaries. Clinical outcomes included nerve injury, hypocalcemia, hematoma, and residual tumor. RESULTS: Forty-eight children underwent thyroid surgery. Thirty (63%) were for malignancy, 27 (90%) of which were DTC. Nineteen (70%) patients with DTC underwent 24 neck dissections; 19 central plus lateral and 5 central alone. The female to male ratio increased from 1:1 to 3:1 with age. Two children with lateral neck involvement had sub-centimeter primaries. Patients requiring neck dissection were more likely to have 1) diffuse sclerosing or tall cell variant, 2) T3 or T4 disease, 3) genetic mutation, 4) lymphatic invasion, 5) extracapsular extension, 6) positive resection margin. Levels IIA (79%), III (89%), IV (84%), VI (100%) were most commonly involved. Levels IB (16%), IIB (16%), VB (16%) were also involved, often without involvement of adjacent levels. Permanent injuries included one unilateral recurrent laryngeal nerve, one mild marginal mandibular nerve and one mild accessory nerve. Hypocalcemia was highest following neck dissection for malignant disease. One patient was re-operated for a mediastinal node. Most patients with N1 disease received radioactive iodine. Most patients have no evidence or indeterminate disease on long-term follow-up. CONCLUSION: Children with lateral nodal spread from DTC should be considered for neck dissection including Levels IB, IIA, IIB, III, IV, VB, bilateral VI. LEVEL OF EVIDENCE: 4 Laryngoscope, 131:E1002-E1009, 2021.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".