Authors’ Response: Patients on Appropriate T<sub>4</sub>Replacement Are as Content as They Would Be on Any Thyroid Hormone
Bibliographic record
Abstract
Dr. Laurberg has suggested that one of the reasons that may explain, in part, the observations of a decreased sense of general well-being in some treated hypothyroid patients may be that there is “bias in diagnosing and therapy” (1). Dr. Laurberg has specifically commented on data suggesting that individuals who are treated with thyroid hormone are more likely to have both a high General Health Questionnaire score and other medical comorbidities, such as diabetes, cardiac disease, stroke, hypertension, epilepsy, and depression (2, 3). We agree with Dr. Laurberg that these data are consistent with the possibility that patients presenting with symptoms of depression, general sense of a lack of well-being, or other medical conditions (which may themselves be associated with decreased quality of life, such as diabetes) may be more likely to be screened for, diagnosed with, and treated for hypothyroidism. Such symptoms may be persistent, despite T4 therapy (particularly if hypothyroidism is not the cause of the impaired well-being), and the depressed quality of life noted in T4-treated patients may be wrongly attributed to T4 therapy itself. Such an explanation may explain, in part, the lack of effect of the addition of T3 to T4 therapy (in patients with a normal TSH) in improving general sense of well-being, as seen in our study (4). If further trials of T3 therapy fail to detect a benefit on well-being, the need to look at nonthyroidal approaches may be more pressing.
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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 | 0.004 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.050 | 0.026 |
| Insufficient payload (model declined to judge) | 0.027 | 0.013 |
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".