The effect of different levothyroxine administration regimens on thyroid hormone levels: a systematic review, pairwise, and network meta-analysis
Bibliographic record
Abstract
Introduction This systematic review aimed to compare the effect of alternative levothyroxine administration regimens on thyroid hormone levels and patient-reported outcomes (PROs) among adults with hypothyroidism.Methods We searched PubMed, Embase, CENTRAL, CINAHL, LILACS, SciELO, Scopus, Web of Science, OpenGrey, ProQuest, ClinicalTrials.gov, and ICTRP from inception to May/2023 for randomized controlled trials (RCTs). We assessed the risk of bias with Cochrane Risk of Bias 2.0 tool. We analyzed TSH levels by pairwise and network meta‐analyses (NMA). The FT4 levels and PROs were qualitatively assessed.Results We included 14 RCTs (906 participants) comparing different regimens, as bedtime vs. before breakfast. A total of 12 RCTs were at high risk of bias. Seven RCTs were included in the TSH meta-analysis, where the mean difference (MD) and 95% confidence interval (CI) were as follows: bedtime vs before breakfast (4 RCTs) 0.69 (−1.67–3.04), I2 = 92%, very low certainty evidence; weekly dose vs before breakfast (2 RCTs) 1.68 (0.94–2.41), I2 = 0%, low certainty evidence; and at breakfast vs before breakfast (1 RCT) 0.65 (−1.11–2.41), very low certainty evidence. The NMA showed no evidence of differences in TSH level with different regimens.Conclusion The evidence is insufficient to determine the most effective levothyroxine administration regimen for hypothyroidism.Systematic review registration PROSPERO – CRD42021279375
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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 | 0.037 | 0.095 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.024 | 0.047 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".