Hypoproteinemia as a prognostic risk factor for arteriovenous fistula failure
Bibliographic record
Abstract
INTRODUCTION: Any vascular access is of limited duration with many factors which influence survival in patients on chronic hemodialysis (HD). Hypoproteinemia as a marker of chronic illness is common among chronic HD patients. Our aim was to analyze the survival of the primary arteriovenous fistula (AVFs) and the risk factors which influence their patency and to test the hypothesis that patients with normal values of serum proteins have lower risk of AVF failure compared to patients with hypoproteinemia. METHODS: Seven hundred thirty-four consecutive patients were included who underwent creation of an AVF. The patients were prospectively followed-up for 2 years. Only patients with AVF function after a month from its creation were analyzed. The patients were divided into two subgroups, with normal and low serum protein levels (<65 g/L). FINDINGS: At follow-up 497 (67.7%) AVFs were still functional while 237 (32.3%) AVFs failed due to thrombosis or stenosis. Serum proteins and AVFs created on the forearm were positive predictors while diabetes was a negative predictor of longer AVF survival (P < 0.001; P = 0.003; P = 0.043). When comparing patients with normal and low serum protein levels (<65 g/L), mean survival time was significantly longer in patients with normal serum levels (P < 0.001). DISCUSSION: In this study, hypoproteinemia was an independent prognostic marker for AVF failure at 2 years. Hypoproteinemia, based on our results, is an independent, more sensitive and prognostic marker of possible vascular access failure than the presence of other common factors which influence shorter AVF survival.
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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 | 0.000 |
| 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) | 0.002 | 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".