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Modality options for renal replacement therapy: The integrated care concept revisited

2006· review· en· W1966026626 on OpenAlexaffvenue
Gihad Nesrallah, David C. Mendelssohn

Bibliographic record

VenueHemodialysis International · 2006
Typereview
Languageen
FieldMedicine
TopicDialysis and Renal Disease Management
Canadian institutionsHumber River Regional Hospital
Fundersnot available
KeywordsMedicineModalitiesModality (human–computer interaction)Intensive care medicinePeritoneal dialysisRenal replacement therapyHemodialysisDialysisTreatment modalityEnd stage renal diseasePopulationTransplantationDiseaseAutonomySurgeryInternal medicineComputer science

Abstract

fetched live from OpenAlex

As the End-stage renal disease population continues to grow, innovative strategies that optimize patient outcomes while capitalizing on the relative strengths of the existing modalities must be sought. Renal transplantation remains the preferred form of renal replacement therapy, but given the limited supply of donor organs, dialytic therapies will continue to constitute a large part of the modality mix. Matching patients to the most suitable modalities requires that a number of factors be considered. These include the patient's autonomy, medical and social factors, system-related issues, patient outcomes, and finances. While peritoneal dialysis and hemodialysis (HD) have traditionally been viewed as competing modalities, we propose that they, along with home and frequent HD regimens, may be used in a complementary manner, which is based on current evidence, and may provide optimal outcomes while containing treatment costs. In this review, we attempt to synthesize the current literature describing the various issues that affect modality selection, and offer an approach to achieving a balance between these many competing factors.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.935
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.045
GPT teacher head0.355
Teacher spread0.310 · 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.

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

Citations37
Published2006
Admission routes2
Has abstractyes

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