Sky-High Thyroglobulin Level Following Thyroid Lobectomy Without Evidence of Metastatic Disease
Bibliographic record
Abstract
Background/Objective: Thyroglobulin (Tg) serves as a crucial indicator for monitoring recurrence in patients with differentiated thyroid cancer following total thyroidectomy and radioactive iodine therapy. The utility of following Tg after thyroid lobectomy (TL) is debatable. There appears to be insufficient evidence to establish a specific Tg cutoff that can reliably detect persistent or recurrent disease after TL. The objective of this report is to describe a patient with an unexpectedly elevated Tg level following thyroid lobectomy for low-risk papillary thyroid carcinoma. Case Report: A 41-year-old female patient underwent a left thyroid lobectomy for low-risk classic papillary thyroid carcinoma. Her postoperative assessment reveals an unexpectedly elevated Tg at 4055 ng/mL (normal range: 3.5-77 ng/mL) with a negative Tg antibody <22 IU/mL (kIU/L). This is confirmed through repeated tests using multiple techniques to rule out laboratory errors and interference. Metastatic workup, including thyroid sonographic assessment and biopsy, chest computed tomography, and an 18F-fluorodeoxyglucose positron emission tomography scan, yielded negative results. Following thyroidectomy, the Tg level decreases dramatically to 0.7 ng/mL (0.7 μg/L). Discussion: Significantly elevated Tg levels after TL warrant careful consideration, but it is crucial to exclude potential laboratory errors and assay interference; additionally, it is essential to rule out underlying metastatic disease. Conclusion: Measuring Tg and Tg antibody levels post-TL can provide a baseline for future reference. However, this case illustrates that high levels of Tg can be seen in the absence of thyroid cancer and therefore cannot reliably predict the risk of recurrence.
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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 | 0.000 | 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".