Qualitative study on obstacle factors for inadequate utilization rate of autologous arteriovenous fistula in dialysis patients
Bibliographic record
Abstract
ObjectiveTo analyze the obstacle factors for inadequate utilization rate of autologous arteriovenous fistula(AVF) during the first dialysis of dialysis patients.MethodsUsing the focus group interview method,interviews were conducted with 16 medical and nursing staff from the nephrology department and dialysis room of Second Hospital of Shanxi Medical University,as well as 20 patients diagnosed with end-stage kidney disease who underwent hemodialysis treatment for less than 3 months.Colaizzi's 7⁃step analysis method was used for data analysis.ResultsThe obstacle factors for inadequate utilization rate of autologous AVF during the first dialysis of dialysis patients included three aspects:evidence, adopters, and practice environment.In terms of evidence:lack of relevant data support,difficult execution.Nurses lack authority.Lack of research results from other fields to assist patients in making active decisions. In terms of adopters:patients do not attach importance to the disease and have insufficient awareness.The patient refuses to establish an arteriovenous fistula in advance.The patient's emotions was confusion and fear.In terms of practical environment:a lack of standardized operating procedures for autologous arteriovenous fistula.A lack of a comprehensive vascular access specialist management team.And a lack of established multidisciplinary cooperation mechanisms.ConclusionsGuided by the Ottawa research application model,this study identified 9 major obstacle factors for inadequate utilization rate of autologous AVF during the first dialysis of dialysis patients from three aspects:evidence,potential adopters,and practical environment.It provided a basis for constructing intervention strategies and promoting the early establishment of autologous arteriovenous fistulas in the future.
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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 | 0.008 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".