MétaCan
Menu
Back to cohort

Blood Flow and Recirculation Rates in Tunneled Hemodialysis Catheters

2004· article· en· W2020830224 on OpenAlexaff
Lynne Senécal, Elaine Saint-Sauveur, Martine Leblanc

Bibliographic record

VenueASAIO Journal · 2004
Typearticle
Languageen
FieldHealth Professions
TopicCentral Venous Catheters and Hemodialysis
Canadian institutionsHôpital Maisonneuve-Rosemont
Fundersnot available
KeywordsDialysisMedicineHemodialysisBlood flowCatheterHemodialysis CatheterSurgeryUltrafiltration (renal)CardiologyChemistryChromatography

Abstract

fetched live from OpenAlex

Long-term catheters are widely used in some dialysis units. Because of higher dialysis dose targets, high flow catheters have been made available. We measured blood flow (Qb in ml/min) and recirculation rate (R%) in two types of tunneled dialysis catheters using ultrasound-dilution technology (Transonic). Thirty-seven catheters were evaluated (27 Opti-Flow, 10 High-Flow), as inserted in jugular or subclavian veins. Real Qb and R were measured at increasing pump blood flows (250, 300, 350, 400, and 450 ml/min) in absence of ultrafiltration. For all, real Qb was similar to pump Qb (261 vs. 250, 304 vs. 300, 349 vs. 350, 389 vs. 400, and 431 vs. 450 ml/min, respectively). Catheters with reversed lines were all recirculating (R between 18% and 24%). Sixteen nonreversed catheters had no R at all Qb, whereas four nonreversed catheters had minimal R (between 7% and 11%); R did not increase significantly with the rise in pump Qb. The two types of tunneled catheters deliver high Qb without high R if ports are not reversed. The relative decrease in treatment efficiency should be accounted for in dialysis prescription if such tunneled catheters are used as long-term access, especially if lines have to be reversed.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.030
GPT teacher head0.333
Teacher spread0.303 · 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 designBench or experimental
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

Citations27
Published2004
Admission routes1
Has abstractyes

Explore more

Same venueASAIO JournalSame topicCentral Venous Catheters and HemodialysisFrench-language works237,207