Correlation between hyperthyroidism and risk of stroke: a meta-analysis based on prospective cohort studies
Bibliographic record
Abstract
Objective To investigate the correlation between (HT) and stroke. Methods The search terms included hyperthyroidism and cerebral infarction in both Chinese and English, and thyroid dysfunction thyroid disorder thyroid disease thyrotoxicosis cerebrovascular disease and cerebrovascular accident in English. PubMed, Embase, Google Scholar, CNKI, CBM and Wanfang were searched, and the related magazines were also hand-searched. These studies were selected and related data were extracted by two authors according to the inclusion and exclusion criteria, and a third author would make a decision when the former two authors couldn't reach an agreement. The Newcastle-Ottawa Scale (NOS) was used to evaluate the quality of included studies, and the Stata 12.0 software was used for meta-analysis. Results Eleven prospective cohort studies were included. The NOS scores indicated that all the studies were high-quality studies. The meta-analysis showed that the risk of stroke in the HT group is 1.30 times as high as that in the euthyroidism (ET) group (P<0.05). Subgroup analyses showed that among Asian populations, the risk of stroke in the HT group is 1.39 times as high as that in the ET group (P<0.05); the risk of stoke in the clinical HT group is 1.32 times as high as that in the ET group (P<0.05 ); and the risk of stroke in the HT group without atrial fibrillation is 1.33 times as high as that in the ET group (P<0.05). In addition, the subgroup analysis of studies which had adjusted most of confounding factors showed that the risk of stroke in the HT group was 1.35 times as high as that in the ET group (P<0.05). Begg and Egger tests both showed that there were no published biases, and the RR value was 1.26 after conducting a trim and fill analysis. Sensitivity analysis indicated that the results were stable. Conclusion HT might be a risk factor of stroke, but due to the limitations of this meta-analysis, further relevant research is warranted for validation. Key words: Hyperthyroidism; Stroke; Atrial fibrillation; Meta-analysis
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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 | 0.011 | 0.022 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.038 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".