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SOLUTE MASS TRANSFER AREA COEFFICIENTS IN A PERITONEAL DIALYSIS POPULATION

2000· article· en· W2079167669 on OpenAlexaff
Laurie J. Garred, Wojciech Turek, A Slingeneyer

Bibliographic record

VenueASAIO Journal · 2000
Typearticle
Languageen
FieldMedicine
TopicDialysis and Renal Disease Management
Canadian institutionsLakehead University
Fundersnot available
KeywordsPeritoneal dialysisMass transferCreatinineUrologyChemistryPeritoneal equilibration testUreaPopulationContinuous ambulatory peritoneal dialysisChromatographyInternal medicineMedicineBiochemistry

Abstract

fetched live from OpenAlex

The mass transfer properties of the peritoneal membrane are best characterized by solute mass transfer area coefficients (KBD). In this study we examined KBD values for urea, creatinine and glucose in 109 peritoneal dialysis patients. The following procedure was employed for the 145 test exchanges. Samples were drawn from the peritoneum for solute concentration measurement immediately following infusion of 2L of dialysate and at 15, 30, 60, 120, 180 and 240 min dwell time. The volume drained at the end of the 240 min exchange was measured and a blood sample taken for plasma solute concentration measurement. KBD values were extracted from these data employing Garred's simple model for peritoneal mass transfer. Mean KBD results ± standard deviation were:TableFour patients had 4 KBD evaluations spaced over time periods ranging from 18.4 to 42.4 months. The repeated KBD values for all patients were consistent and did not demonstrate any long term change in peritoneal mass transfer capacity. Plotting urea KBD versus glucose KBD demonstrated a proportional relationship between the two: The proportionality coefficient of 1.78 is close to the 1.73 constant predicted from diffusion theory (KBD inversely proportional to square root of molecular weight). The linear relationships found when creatinine KBD was plotted versus KBD for urea and glucose (R = 0.73, 0.88) had an unexpected negative intercept. These results indicate the variability of KBD among peritoneal dialysis patients and may be useful for kinetic modeling.

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)0.003
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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.013
GPT teacher head0.251
Teacher spread0.238 · 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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