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Record W4415476384 · doi:10.1681/asn.2025pa1hw032

Role of Filtration Fraction to Predict Early Circuit Loss During CRRT with Regional Citrate Anticoagulation: A Retrospective Cohort Study

2025· article· en· W4415476384 on OpenAlexaff
F Chennou, Dani Abas, Jean Côté

Bibliographic record

VenueJournal of the American Society of Nephrology · 2025
Typearticle
Languageen
FieldMedicine
TopicAtrial Fibrillation Management and Outcomes
Canadian institutionsCentre Hospitalier de l’Université de MontréalUniversité de MontréalUniversity of Toronto
Fundersnot available
KeywordsRetrospective cohort studyFiltration (mathematics)Filtration fractionRenal functionCohort studyFraction (chemistry)

Abstract

fetched live from OpenAlex

Background: Continuous renal replacement therapy (CRRT) is an effective treatment modality for kidney failure in acutely ill patients. Despite circuit anticoagulation with heparin, and more recently regional citrate anticoagulation (RCA), circuit loss due to premature filter coagulation remains a costly clinical challenge. The filtration fraction (FF) equation is the ratio of ultrafiltration to plasma flow rates delivered to the filter; a high FF corresponds to higher post-filter hematocrit. Based on current guidelines and expert consensus, a FF below 0.20 to 0.25 is recommended to minimize the occurrence of filter clotting. However, the role of FF in predicting early circuit loss with RCA is uncertain. Methods: We performed a retrospective analysis of CVVHDF episodes at a large academic center between January 2021 and December 2023. The aims of this study were to correlate the FF with circuit lifespan and assess the ability of FF to predict >48, >36 and <24 hours circuit loss by using logistic regression and calculating the area under the curve (AUC). Results: A total of 1087 circuits from 252 patients (mean age 61 years, 68% men) were included. RCA was used in 347 circuits, whereas 713 received local circuit heparin, systemic heparin or no anticoagulation. Out of all circuits, 443 (41%) were lost due to filter clotting (<72 hours) and 126 (12%) were changed at 72 hours per protocol. The mean FF at initiation was 0.23 (SD 0.07) which was similar between the two groups. High FF correlated with lower circuit lifespan for the heparin/no anticoagulation group (Pearson coefficient: -0.307; p<0.001), but not for RCA (Pearson coefficient: 0.023; p=0.73). FF predicted >48, >36 and <24 hours circuit loss in the heparin/no anticoagulation group (beta of -1.08, -1.20 and -1.23, respectively; p<0.001), but not for RCA (beta of 0.28, 0.09, -0.28, respectively; p>0.05). The AUC to predict early circuit loss <24 hours was 0.67 [0.62-0.72](p<0.001) for heparin/no anticoagulation and 0.52 [0.44-0.62](p=0.51) for RCA. Conclusion: Our study showed an association between FF and circuit lifespan for filters receiving heparin or no anticoagulation, however this was not observed when using RCA. FF is a modest predictor of circuit coagulation with heparin/no anticoagulation.

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)0.004
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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.021
GPT teacher head0.298
Teacher spread0.278 · 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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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