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Record W4408246010 · doi:10.1111/hdi.13212

Analysis and Management of Perivenous Tissue Pain in the Outflow Tract of Arteriovenous Fistulas During Dialysis

2025· article· en· W4408246010 on OpenAlexvenueno aff
Chenwei Wang, Ruibin Zhang, Xiao Wang, Xiuxiu Liu, Xiaoping Wang, Qingzhen Gao

Bibliographic record

VenueHemodialysis International · 2025
Typearticle
Languageen
FieldHealth Professions
TopicCentral Venous Catheters and Hemodialysis
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineFistulaArteriovenous fistulaStenosisDialysisHemodialysisSurgeryPercutaneousRadiology

Abstract

fetched live from OpenAlex

BACKGROUND: Pain is a prevalent cause of medical consultation among dialysis patients, severely impacting both treatment outcomes and quality of life. This study focuses on a specific yet underexplored type of pain-delayed and progressive perivenous tissue pain in the outflow tract of arteriovenous fistulas (AV fistula) during dialysis. The aim is to summarize its clinical features, investigate its underlying mechanisms, and evaluate the effectiveness of various treatments, ultimately providing new insights into pain management. METHODS: This study included 36 patients who experienced delayed and progressive perivenous tissue pain in the outflow tract of AV fistulas during dialysis. Pain features were systematically summarized, and the AV fistula status was comprehensively evaluated through general observation, physical examination, and imaging. A series of trial interventions were employed to further explore the underlying mechanisms of pain. Based on these findings, appropriate treatment strategies were identified and implemented, with therapeutic outcomes monitored over a 12-month follow-up. FINDINGS: The specific pain may be closely associated with venous hypertension. Ultrasonography identified high-flow fistulas in 18 patients, while angiography revealed varying degrees of outflow vein stenosis in 23 patients. Five patients with slightly elevated fistula blood flow and no significant stenosis underwent bandage compression therapy. Thirty-one patients with markedly increased blood flow and/or outflow vein stenosis received ultrasound-guided flow restriction surgery, percutaneous transluminal angioplasty, or combined therapies. All patients achieved pain relief, with no recurrence during the follow-up period. CONCLUSIONS: This study systematically investigates perivenous tissue pain in the outflow tract of AV fistula during dialysis. Venous hypertension is likely the primary underlying cause of this condition. Treatment options, including bandage compression, flow restriction surgery, percutaneous transluminal angioplasty, and combined therapies, effectively alleviate the tissue pain.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.017
GPT teacher head0.331
Teacher spread0.314 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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