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Record W1592834784 · doi:10.1111/hdi.12025

Arteriovenous fistula for the 80 years and older patients on hemodialysis: Is it worth it?

2013· article· en· W1592834784 on OpenAlexaffvenue
Annie‐Claire Nadeau‐Fredette, Rémi Goupil, Bernard Montreuil, Annie Carignan, Martine Leblanc

Bibliographic record

VenueHemodialysis International · 2013
Typearticle
Languageen
FieldHealth Professions
TopicCentral Venous Catheters and Hemodialysis
Canadian institutionsUniversité de MontréalHôpital Maisonneuve-Rosemont
Fundersnot available
KeywordsMedicineHemodialysisArteriovenous fistulaReferralPopulationVascular accessCentral venous catheterSurgeryInternal medicineCatheter

Abstract

fetched live from OpenAlex

Over the last years, the proportion of patients older than 80 years with end-stage renal disease has been constantly growing. Arteriovenous fistula (AVF) is known as the best vascular access for hemodialysis, but evidence for its added value is lacking for elderly. We retrospectively identified new vascular access (AVF and central venous catheter) created or installed between June 2005 and June 2008 in patients 80 years and older and in patients between 50 and 60 years. For every new AVF, we calculated primary failure, primary and secondary patency durations. Fifty-five and 57 patients had a new vascular access in the >80 years old and 50 to 60 years old groups. Among these, 25 and 41 were new AVF in the older and younger groups. Primary failure was more frequent in elderly than in the younger (40% vs. 17%, P=0.04). Primary patency was not significantly different in both groups (P=0.06). Secondary patency was shorter in elderly (P=0.005). Among the older group, the presence of an AVF was not associated with a difference in mortality (46% vs. 60%, P=0.28), whereas there was a lower mortality in the younger group with AVF (12% vs. 43% P=0.008). These results indicate lower patency duration in very elderly patients compared to middle-aged patients. Without leading to the exclusion of patients over 80 years old for AVF creation, it might reinforce the need of a careful selection and evaluation in this population prior to referral.

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)0.002
metaresearch head score (Gemma)0.003
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 score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.002
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 head0.032
GPT teacher head0.329
Teacher spread0.297 · 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

Citations22
Published2013
Admission routes2
Has abstractyes

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