The Role of Inflammation in Contributing to Vascular Risk in Subclinical Hyperthyroidism: Randomized Controlled Trial
Bibliographic record
Abstract
Background: Subclinical hyperthyroidism (SH, defined by low or undetectable serum thyroid stimulating hormone and normal thyroid hormones) is associated with increased cardiovascular risk (CVR) such as atrial fibrillation. Few studies also showed an increased risk of vascular disease and mortality in SH. Inflammation has been shown to play a significant role in the pathogenesis of cardiovascular disease. Increased levels of C-reactive protein (CRP), lipoprotein associated phospholipase A2 (Lp-PLA2, an inflammatory marker which plays a critical role in atherosclerosis), neutrophil to lymphocyte ratio (NLR) and monocyte to lymphocyte ratio (MLR) have been reported in conditions with increased cardiovascular risk. We aimed to ascertain whether abnormal CRP, Lp-PLA2, NLR and MLR contribute to an increased CVR in SH. Methods: CRP, Lp-PLA2, NLR and MLR in peripheral blood were measured in 30 SH subjects at baseline and after 6 months of treatment with either carbimazole or placebo in a randomized placebo-controlled design. Results: There was no significant difference in CRP, Lp-PLA2, NLR and MLR between carbimazole and placebo treated groups at 6 months. There was also no statistical difference in the above parameters if we compared the change or difference between two visits (visit 2 and visit 0 levels) in both groups. Conclusion: There is no evidence of chronic inflammation in our small cohort of SH subjects. Our finding needs to be confirmed in future studies with larger number of SH subjects. J Endocrinol Metab. 2021;11(1):28-32 doi: https://doi.org/10.14740/jem723
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".