Relationship Between Vascular Access Flow and Hemodynamically Significant Stenoses in Arteriovenous Grafts
Bibliographic record
Abstract
BACKGROUND: Vascular access dysfunction is a major source of hemodialysis patient morbidity. The NKF K/DOQI Guidelines promote access flow monitoring as the most preferred access surveillance method and have established access flow thresholds for fistulography: an absolute threshold of 600 ml/min and a dynamic threshold of flow less than 1000 ml/min that has decreased by more than 25% over 4 months. The Guidelines apply universally to accesses of different types, sizes, locations, and initial flow rates. METHODS: This article studies the application of access flow guidelines with human experimental data, animal experimental data, and a mathematical model of the arteriovenous graft system. RESULTS AND CONCLUSIONS: Analysis of experimental data and the mathematical model shows that a 20 to 30% and greater decrease in graft flow generally suggests the appearance of hemodynamically significant stenosis as defined by flow criteria. The model suggests that not all 50 to 60% stenoses may be hemodynamically significant or the most flow limiting. The mathematical model also suggests that positive predictive value of access surveillance may be increased for high-flow upper arm grafts by increasing the dynamic K/DOQI threshold from 1000 ml/min to 1200 ml/min.
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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 | 0.011 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".