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Patient preferences for in‐center intense hemodialysis

2005· article· en· W2011932650 on OpenAlexvenueno aff
Nirupama Ramkumar, Srinivasan Beddhu, Paul W. Eggers, Lisa M. Pappas, Alfred K. Cheung

Bibliographic record

VenueHemodialysis International · 2005
Typearticle
Languageen
FieldMedicine
TopicDialysis and Renal Disease Management
Canadian institutionsnot available
FundersNational Institute of Diabetes and Digestive and Kidney Diseases
KeywordsHemodialysisMedicineCenter (category theory)Home hemodialysisMedical emergencyEmergency medicineIntensive care medicineInternal medicine

Abstract

fetched live from OpenAlex

There is a lack of data on patient preferences for intense hemodialysis (IHD). In this study, we conducted a cross-sectional survey to identify patient preferences and patient-centered barriers for IHD. A questionnaire on preferences and anticipated barriers, anticipated benefits, and quality of life for three in-center IHD schedules (daytime 2 hr six times/week [DHD], nocturnal 8 hr three times/week [ND3], and nocturnal 8 hr six times/week [ND6]) was administered to 100 chronic hemodialysis patients. A majority of patients (68%) were willing to undergo DHD for symptomatic benefits or increase in survival. An increase in energy level (94%) and improvement in sleep (57%) were the most common potential benefits that would justify DHD, but only 19% would undergo DHD for an increase in survival of < or =3 years. Only 20% and 7% would consider ND3 and ND6, respectively. The most common reported barriers were inadequate time for self (50%) and family (53%), followed by transportation difficulties (53%). Most patients would undergo DHD for symptomatic or survival benefits, but not ND3 or ND6. Disruption of personal time, however, is an important consideration. Success of DHD program would depend on arrangements for transportation to dialysis unit.

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 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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.727
Threshold uncertainty score0.937

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.020
GPT teacher head0.277
Teacher spread0.258 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
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

Citations78
Published2005
Admission routes1
Has abstractyes

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