Does a Combination Regimen of Thyroxine (T<sub>4</sub>) and 3,5,3′-Triiodothyronine Improve Depressive Symptoms Better Than T<sub>4</sub>Alone in Patients with Hypothyroidism? Results of a Double-Blind, Randomized, Controlled Trial
Bibliographic record
Abstract
Some hypothyroid patients receiving levothyroxine replacement therapy complain of depressive symptoms despite normal TSH measurements. It is not known whether adding T(3) can reverse such symptoms. We randomized 40 individuals with depressive symptoms who were taking a stable dose of levothyroxine for treatment of hypothyroidism (excluding those who underwent thyroidectomy or radioactive iodine ablation of the thyroid) to receive T(4) plus placebo or the combination of T(4) plus T(3) in a double-blind manner for 15 wk. Participants receiving combination therapy had their prestudy dose of T(4) dropped by 50%, and T(3) was started at a dose of 12.5 micro g, twice daily. T(4) and T(3) doses were adjusted to keep goal TSH concentrations within the normal range. Compared with the group taking T(4) alone, the group taking both T(4) plus T(3) did not report any improvement in self-rated mood and well-being scores that included all subscales of the Symptom Check-List-90, the Comprehensive Epidemiological Screen for Depression, and the Multiple Outcome Study (P > 0.05 for all indexes). In conclusion, the current data do not support the routine use of combined T(3) and T(4) therapy in hypothyroid patients with depressive symptoms.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".