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Record W1964164491 · doi:10.1159/000167500

Acetate Metabolism during Hemodialysis: Metabolic Considerations

2008· review· en· W1964164491 on OpenAlexaff
Patrick Vinay, Manuel Cardoso, Alberto Tejedor, Michel Prud rsquo homme, Michel Levelillee, Bernard Vinet, Maryse Courteau, A. Gougoux, M. Rengel, Louis R. Lapierre, Yves Piette

Bibliographic record

VenueAmerican Journal of Nephrology · 2008
Typereview
Languageen
FieldMedicine
TopicNeurological and metabolic disorders
Canadian institutionsUniversité de MontréalHôpital Notre-Dame
Fundersnot available
KeywordsBicarbonateHemodialysisMedicineMetabolismDialysisInternal medicineEndocrinologyMetabolic acidosisBiochemistryChemistry

Abstract

fetched live from OpenAlex

Acetate is used during regular hemodialysis to replace the bicarbonate lost during dialysis. The temporal changes of plasma bicarbonate and acetate concentrations and the critical role of acetate metabolism for the maintenance of plasma bicarbonate are described. We point out that the maximal rate of acetate oxidation in man is usually reached during dialysis, and we identify physiologic and pathologic factors that may modify this Vmax. A syndrome of 'intolerance to acetate' has been described. This syndrome is analyzed in the light of the metabolic consequences of a rapid flux of acetate oxidation in liver and muscle cells. More specifically, the effects of rapid acetate metabolism on tissue ATP, CoA, adenosine and other ATP degradation products are presented. The possible impact of dialysis-induced depletion of carnitine on optimal acetate metabolism is discussed. The potential clinical consequences produced by these changes are presented in relation to the symptoms sometimes observed during dialysis against acetate: vasodilation, hypotension and angina pectoris. The hypoxemia induced by acetate is also briefly reviewed. Different directions are proposed for future research.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.002

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 head0.314
Teacher spread0.281 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations43
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueAmerican Journal of NephrologySame topicNeurological and metabolic disordersFrench-language works237,207