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Record W2041545717 · doi:10.1159/000170327

Equations for the Calculation of the Protein Catabolic Rate from Predialysis and Postdialysis Urea Concentrations and Residual Renal Clearance in Stable Hemodialysis Patients

2008· article· en· W2041545717 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBlood Purification · 2008
Typearticle
Languageen
FieldMedicine
TopicDialysis and Renal Disease Management
Canadian institutionsLakehead University
Fundersnot available
KeywordsHemodialysisDialysisVolume of distributionResidualUreaMathematicsChemistryDistribution VolumeVolume (thermodynamics)ThermodynamicsInternal medicineMedicinePharmacokineticsPhysicsBiochemistry

Abstract

fetched live from OpenAlex

Several simple equations exist for the calculation of Kt/V from predialysis (C<sub>pre</sub>) and postdialysis (C<sub>post</sub>) measurements of urea concentration. Analogous equations are needed for precise determination of patient protein catabolic rate (nPCR) from C<sub>pre</sub> and C<sub>post</sub>. In this study we develop three simple nPCR equations from urea mass balance theory. The equations, which include a term for residual function, may be applied to any session of the week for patients dialyzed three times weekly who are in steady state with respect to dialysis dose and protein catabolism. The precision of each equation was tested with C<sub>pre</sub>, C<sub>post</sub> data obtained from steady state simulations of 540 patients without residual renal clearance (K<sub>R</sub>) and 972 simulated patients with significant residual Kr. The simplest equation has the form: nPCR = a[kt/V+ Kr/V](C<sub>pre</sub>+ C<sub>post</sub>)+0.17 where V is urea distribution volume, and a and d are constants varying with session of the week. When compared to nPCR values calculated from formal urea kinetic modelling, the error determined with this formula never exceeded 5 % for the midweek or final session. A more complicated equation of the form: nPCR =a{[1-bC<sub>post</sub>/C<sub>pre</sub>][1-C<sub>post</sub>/C<sub>pre</sub>+ΔBW/V]C<sub>pre</sub>/(1-0.0003t)+d K<sub>R</sub>/V(C<sub>pre</sub>+ C<sub>post</sub>)}+0.17 provided nPCR estimates with a maximum error < 1.3% for any dialysis session of the week and for Kr up to 4 ml/min for a 70-kg patient. The only data required for the latter equation are C<sub>pre</sub>, C<sub>pos</sub>t, length of dialysis session, volume ultrafiltered (ΔBW), and an approximate value of the patient’s urea distribution volume. The proposed equations permit nPCR to be calculated simply and accurately for stable patients dialyzed three times a week.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.204
Threshold uncertainty score0.274

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.016
GPT teacher head0.228
Teacher spread0.212 · 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