Native Arteriovenous Fistulas: Correlation of Intra‐Access Blood Flow with Characteristics of Stenoses Found During Diagnostic Angiography
Bibliographic record
Abstract
Surveillance of the intra-access blood flow (Qa) has improved identification of thrombosis risk (Qa < or = 500 ml/minute), and these patients are referred for angiogram and angioplasty. The purpose of this study was to correlate the Qa with patient and stenotic lesion characteristics both before and after angioplasty in a retrospective cohort of 210 patients who were preselected on the basis of reduced Qa (369 +/- 121 ml/minute). Angiograms revealed a total of 643 stenoses, and all patients had at least one significant stenosis (>50% luminal narrowing). There was no significant association between the preangioplasty Qa and the number, location, or length of stenoses, but there was a significant negative correlation between the degree of stenosis and the preangioplasty Qa. Five hundred eighty stenoses in 190 patients were treated with angioplasty; the postangioplasty Qa was 633 +/- 208 ml/minute. Of the residual stenoses, all had less than 50% narrowing. There was no correlation between the postangioplasty Qa and the length or degree of stenoses, but there was a significant negative correlation between the postangioplasty Qa and the number of stenoses. We conclude that the primary determinant of reduced preangioplasty Qa is the degree of stenosis, when stenoses are over 50%, whereas the primary determinant of reduced postangioplasty Qa is the number of stenosis. For patients with two or more residual stenoses and failure to achieve Qa > 500 p;ml/minute postangioplasty, the alternative procedure is a prompt surgical revision in order to maintain the goal of access patency.
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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 | 0.005 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".