An Analysis for Aggravation of Thyroid Function After Discontinuing Potassium Iodine in Graves’ Patients Treated With Methimazole and Potassium Iodine
Bibliographic record
Abstract
Background: The efficacy of methimazole (MMI) combined with potassium iodine (KI) therapy as an initial treatment of Graves’ disease (GD) is reported in an area of excessive iodine intake. However, transient aggravation of thyroid function after cessation of KI is often observed. Therefore, we evaluated the factors related with transient aggravation after cessation of KI in GD patients treated with MMI and KI therapy. Methods: This was a retrospective chart review. Seventy-three GD patients were enrolled in this study. Subjects were divided into two groups. Subjects with transient aggravation were group A, and those without transient aggravation were group B. Between two groups, possible factors were evaluated. Standardized assays were used to measure TSH, free T4 (FT4), free T3 (FT3) and thyrotropin-binding inhibitor immunoglobulin (TRAb). Ultrasonography was used to estimate thyroid volume. Results: Fisher’s exact test or Mann-Whitney U test revealed that “firstly adjusted drugs”, “the duration of FT4 normalization from initiation of medication to correction of FT4 to normal range” and “adoption of simultaneous reduction of both MMI and KI” are significant factors. In addition, the latter two factors stayed significant even by multiple logistic regression analysis. Conclusion: Our study suggested that the methods of drugs’ adjustment and “the duration from initiation of medication to normalization of thyroid hormone” may be significant factors of transient aggravation after cessation of KI. It may be better not to reduce both drugs simultaneously, especially in patients who show the relatively shorter duration of normalization of thyroid function. J Endocrinol Metab. 2013;3(6):132-137 doi: http://dx.doi.org/10.4021/jem204w
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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 | 0.001 |
| 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".