Comparison Among the Daily Levothyroxine Doses According to the Etiology of Hypothyroidism
Bibliographic record
Abstract
Background: The initial doses of levothyroxine (LT4) replacement therapy in patients with hypothyroidism in clinical practice are usually empirical, perhaps because of the lack of data suggesting how much hormone is needed in each patient’s situation. The aim of our study is to evaluate the daily dose of oral LT4 needed to achieve the TSH goals in patients with hypothyroidism caused by different etiologies. Methods: Patients were divided and analyzed according to the etiology of the hypothyroidism. We retrospectively evaluated data from 557 patients (501 women) with hypothyroidism who had normal serum TSH and free T4 (FT4) levels in at least two consecutive appointments in which they were using the same levothyroxine doses. Results: The mean dose of levothyroxine in the total sample was 91.3 ± 37.18 µg/day (1.39 ± 0.63 µg/kg/day). Stratifying by group: central hypothyroidism 53.94 ± 28.07 µg/day (0.82 ± 0.48 µg/kg/day); primary hypothyroidism (no intervention) 81.37 ± 29.84 µg/day (1.25 ± 0.53 µg/kg-day); post radioactive iodine (I 131 ) 97.42 ± 28.32 µ g/day (1.33 ± 0.55 µg/kg/day); post-thyroidectomy for benign causes 102.8 ± 36.96 µg/day (1.54 ± 0.59 µg/kg/day); post-thyroidectomy for thyroid cancer 138.5 ± 35.25 µg/day (2.17 ± 0.58 µg/kg/day). Conclusion: The dose of LT4 required to stabilize the patient varies according to different hypothyroidism etiologies. J Endocrinol Metab. 2013;3(1-2):1-6 doi: https://doi.org/10.4021/jem165w
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 | 0.000 | 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".