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Daily (quotidian) nocturnal home hemodialysis: Nine years later

2004· article· en· W1911682223 on OpenAlexaffvenue
Andreas Pierratos

Bibliographic record

VenueHemodialysis International · 2004
Typearticle
Languageen
FieldMedicine
TopicDialysis and Renal Disease Management
Canadian institutionsHumber River Regional HospitalUniversity of Toronto
Fundersnot available
KeywordsMedicineHemodialysisHome hemodialysisDialysisHyperphosphatemiaIntensive care medicineAnemiaNocturnalReimbursementLeft ventricular hypertrophyInternal medicineBlood pressureKidney diseaseHealth care

Abstract

fetched live from OpenAlex

Daily nocturnal home hemodialysis was developed to satisfy the need for a highly effective, smooth, and cost-effective home dialysis therapy. It combines the benefits of the following dialysis methods: long, frequent, and home hemodialysis. It provides a high dialysis dose for small, as well as large, molecules including beta(2)-microglobulin; improves quality if life; and leads to control of hyperphosphatemia without the need for phosphate binders, as well as dissolution for extraosseous calcifications. Furthermore, it controls blood pressure often without medications, is associated with regression of left ventricular hypertrophy, improves cardiac function, improves anemia as well as nutrition, allows an unrestricted diet, and corrects sleep apnea. Finally, it decreases the overall cost of patient care and improves cost utility when compared to conventional hemodialysis. The main obstacle to its wider utilization is the structure of the current reimbursement system. Along with short daily hemodialysis, long intermittent dialysis, and the convective dialysis techniques, daily nocturnal hemodialysis promises to improve dialysis outcomes.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.011
GPT teacher head0.253
Teacher spread0.242 · 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

Citations26
Published2004
Admission routes2
Has abstractyes

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