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Record W2596872016 · doi:10.2215/cjn.08460816

The Use of a Multidimensional Measure of Dialysis Adequacy—Moving beyond Small Solute Kinetics

2017· review· en· W2596872016 on OpenAlexaff
Jeffrey Perl, Laura M. Dember, Joanne M. Bargman, Teri Browne, David M. Charytan, Jennifer E. Flythe, LaTonya J. Hickson, Adriana M. Hung, Michel Jadoul, Timmy Chang Lee, Klemens B. Meyer, Hamid Moradi, Tariq Shafi, Isaac Teitelbaum, Leslie P. Wong, Christopher T. Chan

Bibliographic record

VenueClinical Journal of the American Society of Nephrology · 2017
Typereview
Languageen
FieldMedicine
TopicDialysis and Renal Disease Management
Canadian institutionsToronto General HospitalUniversity Health Network
FundersNational Institute of Diabetes and Digestive and Kidney DiseasesU.S. Department of Veterans Affairs
KeywordsDialysisMedicineDialysis adequacyHemodialysisIntensive care medicineNephrologyMeasure (data warehouse)Kt/VInternal medicineData miningComputer science

Abstract

fetched live from OpenAlex

Urea removal has become a key measure of the intensity of dialysis treatment for kidney failure. Small solute removal, exemplified by Kt/V urea, has been broadly applied as a means to quantify the dose of thrice weekly hemodialysis. Yet, the reliance on small solute clearances alone as a measure of dialysis adequacy fails fully to quantify the intended clinical effects of dialysis therapy. This review aims to ( 1 ) understand the strengths and limitations of small solute kinetics as a surrogate marker of dialysis dose, and ( 2 ) present the prospect of a more comprehensive construct for dialysis dose, one that considers more broadly the goals of ESRD care to maximize both quality of life and survival. On behalf of the American Society of Nephrology Dialysis Advisory Group, we propose the need to ascertain the validity and utility of a multidimensional measure that moves beyond small solute kinetics alone to quantify optimal dialysis derived from both patient-reported and comprehensive clinical and dialysis-related measures.

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)0.004
metaresearch head score (Gemma)0.006
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 score0.004
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.003
Science and technology studies0.0000.002
Scholarly communication0.0030.003
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0010.001

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 head0.237
GPT teacher head0.418
Teacher spread0.182 · 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

Citations90
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueClinical Journal of the American Society of NephrologySame topicDialysis and Renal Disease ManagementFrench-language works237,207