Circulating Adiponectin Levels Are Paradoxically Associated With Mortality Rate: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
CONTEXT: Some studies have surprisingly indicated that serum adiponectin is positively related to mortality rate, thus casting doubts on its role as a therapeutic target for cardiovascular disease. OBJECTIVE: To summarize evidence about direction, strength and modulators of this controversial association. DATA SOURCES: MEDLINE, Web of Science, CINHAL, Cochrane Library and Scopus from inception through June 2018. STUDY SELECTION: English-language prospective studies reporting the association between adiponectin and all-cause or cardiovascular mortality. DATA EXTRACTION: Two investigators independently extracted data and assessed study quality using standard criteria following the Preferred Reporting Items for Systematic Reviews and Meta-analyses and The Newcastle-Ottawa Scale, respectively. Pooled hazard ratios (HRs) (95% confidence intervals-CIs) were derived using a fixed or random effects models when appropriated and were expressed for one standard deviation (SD) increment of adiponectin. DATA SYNTHESIS: We identified fifty-five (n=61,676 subjects) and twenty-eight (n=43,979 subjects) studies for all-cause and cardiovascular mortality, respectively. Pooled HRs, were 1.24 (1.17-1.31) and 1.28 (1.19-1.37) for all-cause and cardiovascular mortality, respectively. Similar results were obtained also for High Molecular Weight adiponectin. When meta-analyses were restricted to studies reporting data on natriuretic peptides a 43% and 28% reduction on a log scale of these associations were observed after natriuretic peptides adjustment. CONCLUSIONS: Our results strongly points to a paradoxical association between high adiponectin levels and increased mortality rate, which is partly modulated by natriuretic peptides.
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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 | 0.016 | 0.039 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.030 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| 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".