Circulating Irisin Level and Thyroid Dysfunction: A Systematic Review and Meta‐Analysis
Bibliographic record
Abstract
Both thyroid hormones and irisin have profound influences on the metabolism of the human body. Based on their similarities, several studies have been conducted to explore changes in irisin levels in patients with hypothyroidism and hyperthyroidism. This study was conducted in accordance with the PRISMA statement and the MOOSE reporting guideline. Based on a preregistered protocol (PROSPERO-CRD42019138430), a comprehensive search of eight databases was performed from inception to April 2020. Studies with original data collected from patients with thyroid dysfunction were included. Subgroup analysis was performed based on the different types of clinical manifestations and patient characteristics. The quality of each study and the presence of publication bias were assessed by the Newcastle-Ottawa score (NOS) and funnel plot with Egger's test, respectively. A total of 11 studies with 1210 participants were included. Ten studies were identified as high-quality studies. Pooled analysis indicated decreased irisin levels in patients with hypothyroidism (MD -10.37, 95% CI -17.81 to -2.93). Subgroup analysis revealed an even lower level of irisin in patients with clinical-type hypothyroidism (MD -17.03, 95% CI -30.58 to -3.49) and hypothyroidism caused by autoimmune disease (MD -19.38, 95% CI -36.50 to -2.26). No differences were found after achieving euthyroid status from levothyroxine treatment in patients with hypothyroidism compared with controls. No differences were found between patients with hyperthyroidism and controls. Correlation analyses revealed a possible negative correlation between irisin and TSH and positive correlations between irisin and both fT3 and fT4. Irisin was correlated with TSH receptor antibodies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".