Environmental Iodine Content, Female Sex and Age Are Associated with New-Onset Amiodarone-Induced Hypothyroidism: A Systematic Review and Meta-Analysis of Adverse Reactions of Amiodarone on the Thyroid
Bibliographic record
Abstract
OBJECTIVES: To investigate the incidence of new-onset amiodarone-induced hypothyroidism (AIH) and the associated risk factors. METHODS: We performed a systematic search in MEDLINE, Embase, the Cochrane Library and the Chinese database from 1995 to 2015. Studies that investigated amiodarone-related adverse reactions on the thyroid were included. A random-effect model was used for the meta-analysis to investigate the incidence rate of AIH and associated risk factors. RESULTS: We identified 465 studies, of which data from 9 studies were included, comprising 1,972 patients. The incidence of AIH was 14.0% (95% confidence interval, CI, 8.7-21.7%) as a whole; it was higher in areas with a high than a low iodine content in the environment (20.3 vs. 8.7%, p < 0.001); subgroup analysis showed that AIH occurred in 19.2% (95% CI 10.2-33.1%) of women and 13.3% (95% CI 7.9-21.7%) of men (p < 0.001). Meta-regression analysis indicated a positive correlation with the mean age and percentage of women. CONCLUSIONS: The occurrence of AIH is a relatively frequent complication of amiodarone, and older women are more likely to develop AIH, especially in areas with a high iodine content in the environment, and restriction of total exposure to iodine might decrease the incidence of AIH.
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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 | 0.006 | 0.015 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.027 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".