The Ongoing Debate Regarding Completion Thyroidectomy Versus Primary Thyroid Surgery for Low and Intermediate Differentiated Thyroid Carcinoma: A Meta-Analysis
Bibliographic record
Abstract
Lobectomy is increasingly performed for low-risk differentiated thyroid cancer (DTC) and papillary thyroid microcarcinoma (PTMC). However, there is a continuous controversy about completion thyroidectomy (CT) following lobectomy. The current meta-analysis aimed to assess the outcomes of the initial surgical procedure versus CT performed for low/intermediate-risk thyroid carcinoma. Six hundred and sixty-one articles were retrieved, and only 15 full texts fulfilled the inclusion and exclusion criteria. There were 15 studies, including 17,143 patients; twelve were retrospective, two prospective studies, and a controlled trial. Seven articles were from Asia, four from the USA, two from Europe, while two were published in Canada. The studies showed no difference between lobectomy and primary thyroid surgery regarding post-surgery complications. CT was not different from the initial surgical procedure in terms of complications for DTC. The study was limited by the retrospective studies included, the outcomes assessed were not uniform, and significant heterogeneity was observed. Further, well-controlled, more specific trials are needed.
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 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 | 0.034 | 0.054 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.041 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".