Serum albumin and von Willebrand factor: possible markers for early detection of vascular damage in children undergoing peritoneal dialysis
Bibliographic record
Abstract
PURPOSE: Cardiovascular diseases are the main causes of morbidity and mortality in children with end-stage renal disease and the relationships among several relevant potential biomarkers were investigated in pediatric peritoneal dialysis patients. METHODS: Serum homocysteine, von Willebrand factor (vWF), apolipoproteins A and B, lipoprotein-a, high sensitive-CRP, hemoglobin, phosphorus and parathyroid hormone (PTH) levels, systolic (SBP) and diastolic (DBP) blood pressure, carotid intima-media thickness (cIMT) and left ventricular mass index (LVMI) were measured in 21 pediatric peritoneal dialysis patients and control subjects. RESULTS: All risk factors were higher in patients than controls. LVMI values were negatively correlated with hemoglobin and positively correlated with PTH and phosphorus levels (p=0.007, r= - 0.573; p=0.013, r= 0.532 and p=0.035, r= 0.461, respectively). cIMT was negatively associated with serum albumin and positively correlated with vWF levels and with SBP and DBP (p=0.006, r= - 0.578; p=0.039, r= 0.453; p=0.02, r= 0.503; p=0.024, r= 0.491, respectively). Robust regression analyses showed that hemoglobin was an independent predictor of LVMI and serum albumin was an independent predictor of cIMT. CONCLUSION: Only uremia-related factors were independent risk factors for predicting LVMI and cIMT. Hemoglobin level may be a critical factor in the development of left ventricular hypertrophy; therefore, effective treatment of anemia is crucial. Low serum albumin and high hsCRP and vWF levels, and their correlations with cIMT, indicate these patients could be at risk of developing malnutrition-inflammation-atherosclerosis syndrome and suggest that serum albumin and vWF levels may be useful markers for early detection of vascular damage.
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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 | 0.002 |
| 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 | 0.001 |
| 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".