Elevated osteoprotegerin is associated with all-cause mortality in CKD stage 4 and 5 patients in addition to vascular calcification
Bibliographic record
Abstract
BACKGROUND: Cardiovascular disease is the leading cause of death in the chronic kidney disease (CKD) population. The mechanisms of vascular damage are not fully understood. The objective of this study was to prospectively investigate the importance of novel mediators of vascular damage, in conjunction with vascular calcification (VC), on survival. METHODS: A total of 134 subjects [60 haemodialysis (HD), 28 peritoneal dialysis (PD) and 46 CKD stage 4] were studied. All survivors completed 40 months of follow-up. VC was measured using multi-slice spiral CT of the superficial femoral artery. Circulating osteoprotegerin (OPG), Fetuin-A and high sensitivity C-reactive protein (hs-CRP) were measured in addition to standard clinical biochemical analysis. RESULTS: After a 40-month follow-up, 31 patients had died (27 men and 4 women). Of 31 subjects, 31 had evidence of significant VC. The majority of deaths were in the HD group (48%), 36% were PD subjects and 16% were CKD subjects. The outcome of interest was survival at the end of follow-up. Multivariate logistical regression analysis revealed male gender [OR 8.06 (1.34-48.450) P = 0.02], OPG >25 pmol/L [OR 5.31(1.35-20.88) P = 0.02] and hypoalbuminaemia [OR 0.26 (0.12-0.56) P < 0.01], were associated with increased odds of death. CONCLUSION: We have previously reported that VC and low albumin predict death in CKD stages 4 and 5 over a 2-year follow-up period. These data show that OPG, independent of CRP, is also associated with a negative outcome. The mechanisms remain to be elucidated; however, it is likely that they are associated with vascular damage through mechanisms in addition to VC.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".