Combined Levothyroxine and Propylthiouracil Treatment in Children with Monocarboxylate Transporter 8 Deficiency: A Multicenter Case Series of 12 Patients
Bibliographic record
Abstract
Objective: To evaluate the combined administration of propylthiouracil (PTU) and levothyroxine (LT4) in managing monocarboxylate transporter 8 (MCT8) deficiency and identify optimal therapeutic dosages. Methods: This multicenter case series involved 12 male patients with MCT8 deficiency whose parents/guardians consented to PTU and LT4 treatment. Data were collected from January 2008 to June 24, 2024. The study focused on treatment safety and outcomes, analyzing baseline and last encounter biochemical, metabolic, and anthropometric parameters. Statistical analyses included Wilcoxon signed ranks tests and generalized estimated equations to assess effects on thyroid and metabolic markers, and receiver operating characteristics curves to predict optimal dose. Results: Patients showed a significant reduction in serum total triiodothyronine (TT3) concentration and TT3/TT4 ratio, with increased serum TT4 and free T4 (fT4) concentrations. The use of PTU effectively reduced TT3 concentration by 25% at an average dose of 6.8 mg/kg/day, while LT4 increased fT4 concentration by 40% from baseline at an average dose of 4.3 µg/kg/day. Thyrotropin concentration was undetectable on treatment. No statistical differences were observed in metabolic and physical parameters between baseline and last encounter overall for the group, but six of eight patients for whom these data were available had an increase in weight ( z -score). There were no adverse effects on liver function or granulocyte numbers noted throughout the period of observation. Conclusion: Combined treatment with PTU and LT4 normalized serum T3, fT4, and TT4 in patients with MCT8 deficiency. Individualized dose adjustments were crucial for achieving therapeutic goals, indicating the need for personalized treatment plans.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".