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ACCESS RECIRCULATION AND THE USE OF VENOVENOUS DIALYSIS CATHETERS

2000· article· en· W2018991237 on OpenAlexaff
Mercedeh Kiaii, C Kianfar, Robert M. Lindsay

Bibliographic record

VenueASAIO Journal · 2000
Typearticle
Languageen
FieldHealth Professions
TopicCentral Venous Catheters and Hemodialysis
Canadian institutionsWestern University
Fundersnot available
KeywordsCatheterMedicineDialysisDialysis catheterVenous accessAnesthesiaThrombosisPosition (finance)Surgery

Abstract

fetched live from OpenAlex

Access recirculation (AR) is important as it can diminish the adequacy of dialysis. It is believed that AR is common in veno-venous catheters. However, the frequency of AR with the use of such catheters has not been established. We studied 24 patients with catheters (19 Perm-caths, and 5 temporary catheters). AR was measured by the ultrasound dilution (Transonic) technique. Qb was increased to maximum rate (venous pressure < 250 mmHg, arterial pressure >-250 mmHg). Qb ranged from 300 – 450 ml/min (average 420 ml/min). With catheters in normal position, 2 people had nonsignificant AR (4%), 3 had significant AR (>5%), and the rest had 0 recirculation. AR ranged from 7% – 51% (average 18%) with catheters in reverse position. In conclusion, AR is rarely present when veno-venous catheters are used in the normal position. If AR is present, it usually implies that there is catheter malfunction such as thrombosis. Reversing the lines results in some recirculation, varying with the individual, and the Qb. Therefore, to ensure optimal dialysis adequacy, care must be taken in using veno-venous catheters in reversed position, and maximal possible Qb should be used with the lines in the normal position.

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)0.014
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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
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 head0.112
GPT teacher head0.371
Teacher spread0.259 · 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

Citations0
Published2000
Admission routes1
Has abstractyes

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