Diagnosis and Management of Juvenile Hyperthyroidism in Germany: A Retrospective Multicenter Study
Bibliographic record
Abstract
This retrospective multicenter study was designed to survey the management of childhood and adolescent hyperthyroidism in six pediatric endocrinological units in Germany. Fifty-six patients aged between 1.1 and 17.0 yr (median 10.5 yr) were enrolled. Data were collected retrospectively from the patients' records by a trained pediatric endocrinologist using standardized questionnaires. After the diagnosis of hyperthyroidism was established on the basis of clinical and biological findings, treatment with antithyroid drugs (carbimazole, methimazole, thiamazole, propylthiouracil) was started in all patients. In 55/56 of the patients treated with antithyroid drugs, euthyroidism was achieved (98%). However, 26 patients (47%) were still hyperthyroid after discontinuation of the medication. Eight children with continued hyperthyroidism ultimately underwent subtotal thyroidectomy 13-136 (median 28) months after the initial diagnosis. Management principles of the participating centers were heterogeneous. As a consequence, prospective multicenter studies are urgently needed to establish clear standards for the diagnosis and therapy of childhood hyperthyroidism.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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".