Monitoring of Thyroid Malfunction and Therapies in Pregnancy and the Postpartum Period: A Systematic Updated Critical Review of the Literature
Bibliographic record
Abstract
PURPOSE: From the very beginning of pregnancy, the maternal thyroid has to adapt to increased thyroid hormone secretion of up to 50%. This is paralleled by changes in thyroid-stimulating hormone secretion and by the thyroid-topic action of human chorionic gonadotropin. Thus, hypothyroidism and hyperthyroidism may occur. Many women exhibit preexisting thyroid diseases. This review tries to add the most recently published approaches to diagnosing thyroid malfunction in pregnancy to existing guidelines. METHODS: Different literature-based approaches to diagnosing thyroid malfunction during pregnancy and the postpartum period were applied. To diagnose thyroid malfunction in pregnancy, trimester-specific reference ranges for thyroid-stimulating hormone and T4 are used. RESULTS: Definitions of thyroid malfunction are given. Treatment schedules for various thyroid diseases were reviewed and, on the basis of recent findings, were revised where necessary. For a daily clinical workup, this outline not only suggests diagnostic and therapeutic steps but also refers to frequent pitfalls and misinterpretations of laboratory data. CONCLUSIONS: Although the body of knowledge is increasing rapidly, the authors believe that this review is able to present new ideas concerning diagnostic and therapeutic tools for thyroid malfunction in pregnancy and the postpartum period. Nevertheless, there seems to remain room for individual approaches based on the personal experience of physicians who deal with these issues regularly.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".