Association between Copeptin and Metabolic Syndrome: A Systematic Review
Bibliographic record
Abstract
Background: Copeptin, a reliable marker for vasopressin release, has been associated with cardiometabolic diseases including metabolic syndrome (MetS). This systematic review aims to evaluate the association between copeptin and MetS. Methods: We searched in Pubmed, Scopus, EMBASE, and Web of Science databases until March 2021 and included observational studies (cohort studies, cross-sectional, and case-control) reporting the risk or prevalence of having MetS in patients with elevated copeptin levels compared to patients without elevated copeptin levels. The risk of bias was evaluated with the Newcastle-Ottawa Scale. Meta-analysis was not performed because of the heterogeneity of the copeptin cut-off values. Results: A total of 7 studies (5 cross-sectional, 1 case-control, and 1 cohort) were included comprising 11,699 participants. Most of them were performed in the adult general population. Two cross-sectional and one case-control studies found a positive significant association between higher levels of copeptin and MetS. While three cross-sectional and one cohort studies found no association. The case-control study had several methodological limitations, most cross-sectional studies were methodologically adequate and the cohort study had no methodological issues. Conclusions: The association between copeptin and MetS is inconsistent. However, the arginine-vasopressin system impairment contributes to metabolic disorders, expressing plasma copeptin changes. Thus, more longitudinal studies are required to corroborate the association of copeptin and MetS.
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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 | 0.004 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".