Adiponectin and All-Cause Mortality in Patients with Chronic Kidney Disease: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Background/Objectives: Elevated levels of adiponectin in chronic kidney disease (CKD) have been paradoxically associated with increased mortality. This meta-analysis aimed to evaluate the association between circulating adiponectin levels and all-cause mortality in patients with CKD, in total and various subgroups. Methods: We systematically searched PubMed, Embase, and Cochrane Library from their inception to December 2024 for studies examining baseline adiponectin levels and observed mortality outcomes in patients with CKD. Studies were included if they evaluated CKD stages 2–5 patients, measured baseline circulating adiponectin levels, and reported hazard ratios (HRs) for all-cause mortality. We excluded non-original research, studies of acute conditions, normal kidney function, kidney transplantation, and those using log-transformed or standardized HRs. HRs with a 95% confidence interval (CI) for all-cause mortality risk per 1 µg/mL increase in adiponectin were extracted and analyzed using the Comprehensive Meta-Analysis Version 4. Study quality was assessed using the Newcastle–Ottawa Scale. Results: Twelve studies with 2523 subjects were included. The pooled unadjusted HR was 1.003 (95% CI: 0.981–1.025) using a random-effects model (I2 = 79%). Subgroup analyses demonstrated increased mortality risk with elevated adiponectin levels in non-Asia (HR 1.021 [95% CI: 1.006–1.037], p = 0.006), studies with female proportion <47% (HR 1.021 [95% CI: 1.009–1.033], p < 0.001), and studies with body mass index ≥25 kg/m2 (HR 1.023 [95% CI: 1.008–1.038], p = 0.003). In contrast, higher adiponectin levels were associated with decreased mortality risk in the peritoneal dialysis group (HR 0.956 [95% CI: 0.934–0.979], p < 0.001) and female proportion ≥47% group (HR 0.929 [95% CI: 0.874–0.988], p = 0.019). Discussion/Conclusions: This meta-analysis revealed that elevated adiponectin levels have varying associations with the risk of all-cause mortality across CKD patient subgroups. These findings suggest that the prognostic value of adiponectin levels in CKD may be modulated by demographic and clinical factors. Limitations include poor generalizability with underrepresentation of early-stage CKD. This research received no external funding and was not registered.
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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 | 0.010 | 0.022 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.038 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| 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".