Impact of coronary artery calcification in hemodialysis patients: Risk factors and associations with prognosis
Bibliographic record
Abstract
The risk factors of coronary artery calcification (CAC) and the impact of CAC on cardiovascular events, cardiovascular deaths, and all-cause deaths in hemodialysis (HD) patients have not been fully elucidated. We examined the CAC score (CACS) in 74 HD patients using electron-beam computed tomography. Fifty-six patients underwent a second electron-beam computed tomography after a 15-month interval to evaluate CAC progression. We evaluated (1) the risk factors for CAC and its progression and (2) the impact of CAC on the prognosis. In the cross-sectional study, HD vintage and high-sensitive C-reactive protein (hsCRP) were the independent risk factors for CAC. In the prospective cohort study, delta CACS (progression of CAC) was significantly correlated with hsCRP, fibrinogen, and serum calcium level in the univariate analysis. Stepwise multiple regression analysis revealed that only hsCRP was the independent risk factor for CAC progression in HD patients. Kaplan-Meier survival analysis revealed that cardiovascular events (P<0.0001), cardiovascular deaths (P=0.039), and all-cause deaths (P=0.026) were significantly associated with CACS. In conclusion, CAC had significantly progressed in HD patients during the 15-month observation period. Microinflammation was the only independent risk factor for CAC progression in HD patients. The advanced CAC was a significant prognostic factor in HD patients, i.e., which was strongly associated with future cardiovascular events, cardiovascular deaths, and all-cause deaths.
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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 | 0.000 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".