Anatomical factors associated with left innominate vein stenosis in hemodialysis patients
Bibliographic record
Abstract
Central venous stenosis remains a challenge in hemodialysis patients. Venograms have shown that left innominate vein (LIV) stenosis often occurs in front of the trachea, where it crosses the aortic arch, suggesting that there may be an anatomical factor involved, such as iliac vein compression syndrome. The goal of this study was to determine whether LIV stenosis can be attributed to compression. From September 2008 to December 2011, 19 hemodialysis patients (ten women, nine men) with symptomatic venous hypertension of the upper-left extremity were enrolled in this study. Venography and multidetector computed tomography were used to determine the location of the venous stenosis and to assess LIV anatomy. LIV diameter and the space between the sternum and aortic arch were compared between the LIV stenosis (LIVS) group (n = 9) and the non-LIV-stenosis (NLIVS) group (n = 10). The mean age of the cohort was 63 ± 17.3 years. The mean LIV diameter was 1.69 ± 1.55 mm in the LIVS group and 8.71 ± 2.33 mm in the NLIVS group. The space between the aortic arch and sternum was smaller in the LIVS group (4.55 ± 2.67 mm) than in the NLIVS group (15.25 ± 6.12 mm, P < 0.001). A contributing factor to LIV stenosis may be due to anatomical compression of the aortic arch behind the sternum. Preoperative noncontrast computed tomography is recommended for hemodialysis patients to exclude extrinsic compression.
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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 | 0.001 |
| 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) | 0.001 | 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".