Vascular access for hemodialysis: Experience of a team of nephrologists
Bibliographic record
Abstract
A survey conducted by Bonucchi et al. underlined the different types of doctors placing arteriovenous fistula (AVF) for hemodialysis in the United States and Europe (in particular Italy). In fact, nephrologists definitely prevail in Italy, where almost 48.8% of nephrologists place an AVF themselves or with the help of a vascular surgeon (26.4%). In Europe, only 35% do so, whereas 89% of AVF are performed by surgeons in the United States. In 98% of the cases occurring at our center, the AVF was placed and reviewed by the nephrologists. This paper reports surgery cases related to the period between January 1983 and September 2006. Over this time, 1386 operations for placing and reviewing vascular access were conducted. Among these, 47 (3.3%) were related to a cuffed central venous catheter (CVC); 1138 (80.2%) related to a distal AVF; 201 (10.6%) related to a proximal AVF; and 51 (3.6%) related to an arteriovenous graft (AVG). In addition, 33 (2.3%) operations performed before January 1983 relating to AV Scribner shunts were included. Arteriovenous fistulas or AVGs were provided to our patients (only 2.6% of them have a CVC), and AVF rescue operations were performed in the shortest possible time with advantages for the patient and his vascular access.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".