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Record W2323862112 · doi:10.5414/cnp68151

The economics of home nocturnal hemodialysis: how should we cost the benefits?

2007· review· en· W2323862112 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

VenueClinical Nephrology · 2007
Typereview
Languageen
FieldMedicine
TopicDialysis and Renal Disease Management
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMedicineObservational studyRandomized controlled trialHemodialysisIntensive care medicineModalitiesHome hemodialysisDialysisCost effectivenessQuality of life (healthcare)RandomizationCost–benefit analysisRisk analysis (engineering)SurgeryInternal medicineNursing

Abstract

fetched live from OpenAlex

Home nocturnal hemodialysis (HNHD) has been established as a safe and effective way to provide dialysis for patients who require renal replacement therapy. Non-randomized studies have shown that patients switched to HNHD have improvements in blood pressure, left ventricular mass and quality of life. At present, there are no RCTs or long-term observational studies demonstrating a clear reduction in cardiovascular events or mortality. Several HNHD centers have published articles documenting the costs of this modality as compared to conventional HD. Some of these studies have found HNHD to provide significant cost savings, while others have found the two modalities to be relatively equivalent in terms of costs. In this paper, we review the results of these costing studies and illustrate some of the limitations associated with these studies including the lack of randomization, inconsistent reporting of HNHD start-up costs, potential patient selection biases and limited follow-up. On balance, it appears premature to conclude that HNHD is cost-saving in comparison to conventional hemodialysis. However, two ongoing randomized trials, which are collecting resource use information, will help to answer this question. Once these data are available, a formal economic evaluation should be done to determine the impact of HNHD on both clinical outcomes and costs. This information will assist decision-makers in determining whether to make HNHD more widely available.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.977
Threshold uncertainty score0.811

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.197
GPT teacher head0.420
Teacher spread0.223 · 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