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Central venous catheterization in infants and children – small caliber audio‐Doppler probe <i>versus</i> ultrasound scanner

2005· article· en· W2039564739 on OpenAlexfundno aff
Toshimi Arai, YAMASHITA MASAO

Bibliographic record

VenuePediatric Anesthesia · 2005
Typearticle
Languageen
FieldHealth Professions
TopicCentral Venous Catheters and Hemodialysis
Canadian institutionsnot available
FundersCanadian Anesthesiologists' Society
KeywordsMedicineUltrasoundCaliberScannerDoppler effectDoppler ultrasoundRadiologyInternal jugular vein

Abstract

fetched live from OpenAlex

BACKGROUND: Ultrasound guidance for cannulation of the internal jugular vein has been shown to increase the success rate and reduce the incidence of complications in infants and children. We compared the use of a small caliber audio-Doppler probe with an ultrasound scanner for cannulation of a central venous (CV) line via the right internal jugular vein in infants and children. METHODS: Fifty-two infants and 29 children scheduled for open-heart surgery were enrolled. Cannulation was guided using a small caliber audio-Doppler probe (the AU group, n = 42), or an ultrasound scanner image (the US group, n = 39). Ultimate success rate, success rate at the first attempt, success rate within 5 min, and complications were compared for the two groups. RESULTS: In children (>12 months), both methods were equally efficient. But in infants (<12 months), success rate at the first attempt using audio-Doppler was worse than the rate using an ultrasound scanner and there were more complications when audio-Doppler was used. CONCLUSIONS: We conclude that application of both the audio-Doppler and the ultrasound scanner is useful in children over 1 year of age for access to the internal jugular vein. However, in infants and neonates, the ultrasound scanner would be more useful than the audio-Doppler.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.018
GPT teacher head0.279
Teacher spread0.261 · 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 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

Citations21
Published2005
Admission routes1
Has abstractyes

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