Comparison of serum albumin, C‐reactive protein and carotid atherosclerosis as predictors of 10‐year mortality in hemodialysis patients
Bibliographic record
Abstract
Serum albumin, C-reactive protein (CRP), and the intima-medial thickness of the common carotid artery (CA-IMT) are associated with clinical outcomes in hemodialysis (HD) patients. However, it remains unclear which parameters are more reliable as predictors of long-term mortality. We measured serum albumin, CRP, and CA-IMT in 206 HD patients younger than 80 years old, and followed them for the next 10 years. One hundred sixty-eight patients (age: 57 +/- 11 years, time on HD: 11 +/- 7 years) were enrolled in the analyses. We divided all patients into three tertiles according to their albumin levels, and conducted multivariate analyses to examine the impact on 10-year mortality. Seventy-three (43.5%) patients had expired during the follow-up. Serum albumin was significantly lower in the expired patients than in the surviving patients (3.8 +/- 0.3 vs. 4.0 +/- 0.3, P<0.01), while CRP (4.7 +/- 5.0 vs. 2.8 +/- 3.5 g/L, P=0.01) and CA-IMT (0.70 +/- 0.15 vs. 0.59 +/- 0.11 mm, P<0.01) were significantly higher in the expired group. The multivariate analysis revealed that there was a significantly higher risk for total mortality in HD patients with serum albumin <3.8 g/dL (odds ratio 5.04 [95% CI: 1.30-19.60], P=0.02) when compared with those with albumin >4.1 g/dL. In contrast, CRP and CA-IMT did not associate with total death. It follows from these findings that serum albumin is more superior as a mortality predictor compared with CRP and CA-IMT in HD patients.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".