Retrospective Analysis of the Development of Human Thyroglobulin during Pregnancy in Patients with Treated Non-Recurrent Differentiated Thyroid Cancer
Bibliographic record
Abstract
Aim: Therapy success in patients with differentiated thyroid cancer (DTC) after thyroidectomy and radioiodine therapy (RIT) is proven by permanent decrease in human thyroglobulin (hTg) to <1 ng/mL. In this retrospective analysis hTg development before, during and after pregnancy were analyzed. Material and methods: A descriptive analysis of hTg courses in 47 women with 57 pregnancies under levothyroxine substitution was performed after treatment of DTC without evidence of residual or recurrent disease. We compared hTg levels before, during and after pregnancies. A median of four measurements were performed during pregnancy. Results: In five out of the 47 patients at least one hTg increase to ≥1.0 ng/mL occurred during pregnancy (P1: 1.1; P2: 1.75; P3: 1.0; P4: 1.1; P5: 1.07 ng/mL). In another three cases an increase to ≥0.5 ng/mL occurred. After delivery, all patients returned to undetectable hTg levels. Human Tg maxima during pregnancy were significantly elevated according to Friedman´s Chi2 and p Holm−Bonferroni. Conclusion: In women with ablative thyroid therapy after DTC, a temporary elevation in hTg levels during pregnancy may occur. The reason therefore remains unclear and requires further investigation.
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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".