Comparison between total thyroidectomy and hemithyroidectomy in TIR3B thyroid nodules management
Bibliographic record
Abstract
PURPOSE: Thyroid nodules classified as TIR3B according to SIAPEC 2014 are considered a clinical challenge due to the risk to be malignant. This retrospective study aimed to compare the performances of total thyroidectomy (TT) and hemithyroidectomy (HT) in the surgical management of a consecutive cohort of patients affected by TIR3B thyroid nodule in terms of side effects and the rate of malignancy detected. METHODS: From 2011 to 2019, 136 (111 women, 25 men; average age of 53.5 years) patients having a thyroid nodule with a cytological diagnosis of TIR3B who underwent TT or HT were retrospectively included. RESULTS: Out of 136 patients, 106 (78%) received TT, while the remaining 30 (22%) HT. The final diagnosis was malignant in 65 patients (48%), with follicular variant of papillary carcinoma as the most frequent. The diagnosis of malignancy was significantly more common in the TT group with 56 patients (53%) compared to the HT group with 9 cases (30%) (p = 0.001). Patients who underwent TT were significantly older, had larger nodules and the time between diagnosis and surgery was significantly longer compared to HT (p = 0.001; p0.003; p = 0.002). No main post-surgical complications were registered, except for one case of transient hypocalcemia in a patient who underwent TT. CONCLUSIONS: Our data showed a malignancy rate of TIR3B lesions higher than expected (48%). Both TT and HT seem to be effective approaches for the treatment of TIR3B nodules with a very low rate of post-surgical comorbidities. In the choice of surgical approach, it is crucial to consider the presence of risk factors (clinical and ultrasound characteristics), nodule size, patients' opinion, and surgeon's skills and experience.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.001 | 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".