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Record W2612432636 · doi:10.1111/sdi.12603

Ultrasound‐Guided Cannulation of the Hemodialysis Arteriovenous Access

2017· review· en· W2612432636 on OpenAlexaff
Frank L. Ward, Rose Faratro, Rory McQuillan

Bibliographic record

VenueSeminars in Dialysis · 2017
Typereview
Languageen
FieldHealth Professions
TopicCentral Venous Catheters and Hemodialysis
Canadian institutionsUniversity Health Network
Fundersnot available
KeywordsMedicineHemodialysisHemodialysis accessVascular accessUltrasoundRadiologyIntensive care medicineSurgery

Abstract

fetched live from OpenAlex

Successful cannulation of the arteriovenous access for patients with end-stage kidney failure to allow catheter-free hemodialysis is associated with superior patient outcomes. With an increasing rate of arteriovenous access creation, coupled with increasing dialysis patient age, the "difficult-to-cannulate" access is becoming more commonplace. Ultrasound-guided cannulation aims to improve first-time successful cannulations and minimize cannulation-associated complications such as infiltration and hematoma formation, minimizing delays in access use and reducing catheter dependency. Ultrasound-guided cannulation has the potential to not only improve patient experience but also reduce morbidity associated with complications, dialysis catheter dependency, and subsequent healthcare costs. A smooth and complication-free dialysis initiation is also important for the longevity of technique survival and self-cannulation in home hemodialysis patients. Appropriate training of the ultrasound operator is required to ensure competent image acquisition with simultaneous needling. There are various approaches and considerations in choosing how to apply the ultrasound probe and needle the access, which are often governed by personal choice, training, and institutional patterns of practice more than a robust evidence base. Future research should focus on providing more clarity on the optimal method of utilizing ultrasound guidance in arteriovenous access cannulation, the precise indications for its use and, lastly, the benefits it confers compared to traditional blind cannulation.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.965
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0030.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.148
GPT teacher head0.461
Teacher spread0.313 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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

Citations34
Published2017
Admission routes1
Has abstractyes

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