Outcomes in Pediatric Thyroidectomy: Results From a Multinational, Multi‐institutional Database
Bibliographic record
Abstract
OBJECTIVE: Traditionally, data regarding thyroidectomy were extracted from billing databases, but information may be missed. In this study, a multi-institutional pediatric thyroidectomy database was used to evaluate recurrent laryngeal nerve (RLN) injury and hypoparathyroidism. STUDY DESIGN: Retrospective multi-institutional cohort study. SETTING: Tertiary care pediatric hospital systems throughout North America. METHODS: Data were individually collected for thyroidectomies, then entered into a centralized database and analyzed using univariate and multivariable regression models. RESULTS: In total, 1025 thyroidectomies from 10 institutions were included. Average age was 13.9 years, and 77.8% were female. Average hospital stay was 1.9 nights and 13.5% of patients spent at least 1 night in the pediatric intensive care unit. The most frequent pathology was papillary thyroid carcinoma (42%), followed by Graves' disease (20.1%) and follicular adenoma (18.2%). Overall, 1.1% of patients experienced RLN injury (0.8% permanent), and 7.2% experienced hypoparathyroidism (3.3% permanent). Lower institutional volume (odds ratio [OR], 3.57; 95% CI, 1.72-7.14) and concurrent hypoparathyroidism (OR, 3.51; 95% CI, 1.64-7.53) correlated with RLN injury on multivariable analysis. Graves' disease (OR, 2.27; 95% CI, 1.35-3.80), Hashimoto's thyroiditis (OR, 4.67; 95% CI, 2.39-9.09), central neck dissection (OR, 3.60; 95% CI, 2.36-5.49), and total vs partial thyroidectomy (OR, 7.14; 95% CI, 4.55-11.11) correlated with hypoparathyroidism. CONCLUSION: These data present thyroidectomy information and complications pertinent to surgeons, along with preoperative risk factor assessment. Multivariable analysis showed institutional volume and hypoparathyroidism associated with RLN injury, while hypoparathyroidism associated with surgical indication, central neck dissection, and extent of surgery. Low complication rates support the safety of thyroidectomy in pediatric tertiary care centers.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".