Risk Factors for the Development of Cephalic Arch Stenosis
Bibliographic record
Abstract
PURPOSE: The creation of a vascular access is necessary in hemodialysis patients, including those with marginal vessels. Upper arm fistulae are attractive due to the ease of creation and of achieving high access flow rates. Cephalic arch stenosis (CAS) can lead to failure of upper arm fistulae and is increasingly identified. We hypothesized that CAS is promoted by high blood flow rates, brachiocephalic fistulae, and an angle of cephalic vein insertion approaching 90 degrees. METHODS: All patients requiring a fistulogram between January 2004 and May 2006 had surveillance fluoroscopy of the central veins. Demographic, clinical and laboratory parameters were collected and the angle of the cephalic vein insertion measured by 3 blinded independent observers. RESULTS: Fifty-eight patients had fistulograms and CAS was detected in 18 subjects. Significant differences between the CAS and non-CAS groups were brachiocephalic fistula site (p = 0.046), access flow (mL/min) (p = 0.012), and absence of diabetes (p = 0.03). Univariate predictors of CAS include access flow (per 100 mL/min) (p = 0.042), platelet count (p = 0.031) and calcium-phosphate product (p = 0.026). The relationship of brachiocephalic site and CAS was confounded by access flow [(per 100 mL/min)*brachiocephalic fistula site (p = 0.016)] and fistula age [brachiocephalic fistula site*fistula age (p = 0.017)]. In multivariate analysis, renovascular disease, calcium-phosphate product, platelet count and access flow (per 100 mL/min)*brachiocephalic fistula predicted CAS (p < 0.001, Negelkerke's R-Square = 0.55). The angle of insertion of the cephalic vein was not predictive for CAS. CONCLUSIONS: CAS may be a long-term consequence of high blood flow rates. The interaction of access flow and brachiocephalic fistula supports the hypothesis that high flow through a brachiocephalic fistula promotes CAS. The multiple factors influencing cephalic arch remodeling require further research.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".