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Record W2407737909

Radiologic placement of central venous catheters: rates of success and immediate complications in 3412 cases.

2001· article· en· W2407737909 on OpenAlexaff
Michael D. Tseng, D.J. Sadler, Jason Wong, Kevin R. Teague, Drew C. Schemmer, John C. Saliken, Benny So, Robin R. Gray

Bibliographic record

VenuePubMed · 2001
Typearticle
Languageen
FieldHealth Professions
TopicCentral Venous Catheters and Hemodialysis
Canadian institutionsFoothills Medical Centre
Fundersnot available
KeywordsMedicinePneumothoraxSurgeryComplicationCentral venous catheterInternal jugular veinCatheterInterventional radiologyHemodialysis CatheterSubclavian vein
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVE: To determine the success and immediate complication rates associated with 3412 central venous catheter placements performed in an interventional radiology suite. METHODS: Success and immediate complication rates were prospectively recorded for 3412 consecutive patients who had central venous catheters radiologically placed at a tertiary care centre between July 1993 and October 2000. The indication for placement and the insertion site were also recorded. RESULTS: The most common indication for both short- and long-term venous access was hemodialysis, and the right internal jugular vein was the most common site for catheter insertion. Placement was successful for 98.8% of tunnelled lines and 99.3% of temporary catheters. The rate for immediate complications (including pneumothorax, air emboli, bleeding and arterial puncture) for tunnelled catheter placements was 3.8% and for temporary catheter placements was 1.6%; no major complications were documented. CONCLUSION: Our results lend further evidence to the claim that the success and immediate complication rates of radiologically placed central venous catheters compare favourably with blind placement and surgical placement of central venous catheters.

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)0.001
metaresearch head score (Gemma)0.012
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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.000
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 head0.078
GPT teacher head0.342
Teacher spread0.264 · 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

Citations33
Published2001
Admission routes1
Has abstractyes

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