Cephalic arch stenosis in patients with fistula access for hemodialysis: Relationship to diabetes and thrombosis
Bibliographic record
Abstract
Numerous studies have identified the fistula as the best access for hemodialysis with fewest complications. The radiocephalic fistula (RCF) is the first access of choice, but often results in poor maturation. Therefore, an increased number of brachiocephalic fistulas (BCF) have been placed. Cephalic arch stenosis (CAS) can occur in patients with fistula access. The current study was done to determine the incidence and associated comorbidities in patients with BCF or RCF who have CAS. A retrospective review of 450 hemodialysis patients in 3 outpatient hemodialysis units between July 1, 2000 and July 1, 2005 (60 months) was preformed. We reviewed demographics, medications, and indications for venograms. Interventional Radiologists reviewed the venograms for evidence of CAS. Radiology reports were screened to determine incidence of thrombosis, treatment with either angioplasty or stent placement and if a complication such as venous rupture occurred. One hundred and twenty-seven patients had fistula access with at least 1 venogram. Of these, 30 were RCF and 97 were BCF. Cephalic arch stenosis occurred in 77% of patients with BCF and in 20% of patients with RCF. Those with diabetes had a lower rate of occurrence than those without (p<0.01). Cephalic arch stenosis led to a high rate of thrombosis (p<0.01). The probability of having multiple radiology procedures was higher with CAS than without (p<0.01). Cephalic arch stenosis is an important problem in hemodialysis patients who have fistula access, and contributes to thrombosis. Diabetes was found to have a negative association with CAS for undefined reasons. Attempts to understand this relationship are important.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".