Strategies for planning the optimal dialysis access for an individual patient
Bibliographic record
Abstract
PURPOSE OF REVIEW: Achieving functioning vascular access in hemodialysis patients remains challenging. Current guidelines recommend creating arteriovenous fistulas (AVFs) as the initial form of vascular access and are primarily based on outdated, observational data. Determining the optimal access for each individual patient is, therefore, of great interest. RECENT FINDINGS: Multiple recent studies suggest that certain subgroups of patients may benefit from alternative forms of vascular access. In particular, the elderly and patients with limited life-expectancy may be less likely to benefit from an AVF first approach. These patients may be more likely to die before benefiting from an AVF and are more likely to experience primary failure of an AVF. If these factors are considered, arteriovenous grafts, and in some cases central venous catheters, become a valid alternative form of vascular access. Patients may also have strong opinions about each type of vascular access, leading to a preference for alternative forms of access. SUMMARY: A patient-centered approach to the choice of dialysis access that incorporates a balance between recent evidence from the literature and patient preferences may be preferred to the current fistula first focus in vascular access choice.
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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".