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Record W4283709982 · doi:10.4097/kja.22231

Hydrolocation Assisted Subclavian Venous Catheterization

2022· article· en· W4283709982 on OpenAlexaff
Joshua Frohlich, Sushil Sancheti

Bibliographic record

VenueKorean journal of anesthesiology · 2022
Typearticle
Languageen
FieldHealth Professions
TopicCentral Venous Catheters and Hemodialysis
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsMedicinePneumothoraxSubclavian veinSubclavian arteryRadiologyVeinSurgeryCatheter

Abstract

fetched live from OpenAlex

BACKGROUND: Of the three common central access sites, subclavian vein catheterization has the lowest risk of infection but the highest risk of pneumothorax. The main disadvantage of the short-axis ultrasound guided approach is difficult needle-tip visualization. We describe use of the hydrolocation technique to improve needle-tip localization. CASE: Two females, an 81-year-old and a 72-year-old, presented for coronary artery bypass grafting requiring central vein cannulation. To confirm that the needle tip was visualized and not the shaft, needle advancement was paused and 1 ml of saline injected. The appearance of a small anechoic pocket superficial to the subclavian vein helped to visualize the needle tip. Negative aspiration was then re-applied and slight advancement resulted in aspiration of blood and successful subclavian vein puncture. CONCLUSIONS: The use of hydrolocation for subclavian vein access was easily implemented, required little modification in setup and technique, and provided improved localization of the needle tip.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.035
GPT teacher head0.325
Teacher spread0.290 · 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 designCase report
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

Citations2
Published2022
Admission routes1
Has abstractyes

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