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Record W4413931688 · doi:10.5114/ait/208286

Ultrasound-assisted peripheral venous cannulation in patients undergoing elective surgery under general anaesthesia: prospective randomized trial

2025· article· en· W4413931688 on OpenAlexaff
Miroslav Kalina, Barbora Štádlerová, David Astapenko, Marcela Bílská, Vladimír Černý, Roman Škulec

Bibliographic record

VenueAnaesthesiology Intensive Therapy · 2025
Typearticle
Languageen
FieldHealth Professions
TopicCentral Venous Catheters and Hemodialysis
Canadian institutionsDalhousie University
Fundersnot available
KeywordsMedicineAnesthesiaRandomized controlled trialPalpationSurgeryUltrasoundGeneral anaesthesiaProspective cohort studyGroup BCatheterClinical trialRadiologyInternal medicine

Abstract

fetched live from OpenAlex

Introduction Peripheral venous catheter (PVC) insertion is a common intervention, conventionally performed using visualization and palpation techniques. It has been reported that the first attempt success rate can be as low as 51%. Ultrasound guidance improves the overall success rate and the success rate of the first attempt. Therefore, we performed a randomized, prospective, clinical trial to compare two different techniques of PVC insertion in the setting of an operating theatre with a focus on the first attempt success rate. Material and methods This clinical trial allocated patients scheduled for elective surgery in general anaesthesia to undergo PVC cannulation with ultrasound guidance (Group A) or to undergo PVC cannulation without the use of ultrasound (Group B). Results A total of 613 adult patients were enrolled. The success of the first cannulation attempt was significantly higher in Group A compared to Group B (Group A: 90.6%, Group B: 84.5%, P = 0.039). The overall success rate in both groups was 100%. The time needed to perform PVC cannulation was significantly lower in Group B than Group A (Group A: 406 ± 200 s, Group B: 301 ± 215 s, P < 0.001). Conclusions We found that ultrasound-guided PVC cannulation was associated with a higher first-attempt success rate than the conventional technique.

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)0.004
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.027
GPT teacher head0.327
Teacher spread0.300 · 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 designRandomized trial
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

Citations1
Published2025
Admission routes1
Has abstractyes

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