Patient perspective and satisfaction with different types of vascular access in hemodialysis: a systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: To assess satisfaction and perspectives of adult hemodialysis (HD) patients on different vascular access (VA) types (AVF, AVG, CVC) by synthesizing quantitative studies using validated questionnaires, focusing on overall satisfaction, physical symptoms, social functioning, and complications. METHODS: We systematically searched Medline, Web of Science, and Scopus for studies assessing adult HD patients' perspectives on VA using structured questionnaires. Risk of bias was assessed using the Newcastle-Ottawa Scale. Meta-analysis was performed using a random-effects model across three pairwise comparisons: AVF vs. CVC, AVF vs. AVG, and CVC vs. AVG. RESULTS: Of 1,253 records, 11 studies (n = 2910) met inclusion criteria. AVF patients had higher overall satisfaction compared to those with CVCs (MD: 7.06%, 95% CI: 2.98-11.14). Compared to AVG, AVF patients had higher overall satisfaction, though not statistically significant (MD: 5.12%, 95% CI: - 0.42 to 10.66; p = 0.069). Dissatisfaction with physical symptoms was significantly higher in AVF patients than in those with CVCs (MD: 8.76%, 95% CI: 4.19 to 13.34). Compared to CVC, AVF patients reported significantly lower dissatisfaction in both social functioning (MD: - 9.48%, 95% CI: - 15.98 to - 2.98) and dialysis-related complications (MD: - 10.08%, 95% CI: -12.66 to -7.50). CONCLUSIONS: AVFs are associated with higher overall patient satisfaction compared to other VA types. While AVF patients experience more physical discomfort, this is outweighed by significantly greater satisfaction in areas such as social functioning and dialysis-related complications. These findings emphasize the importance of considering patient-reported outcomes when evaluating VA options in HD care. CLINICAL TRIAL NUMBER: Not applicable.
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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 | 0.013 | 0.032 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.026 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".