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Past, Present, and Future of Quantified Peritoneal Dialysis

2001· review· en· W2051304553 on OpenAlexaboutno aff
Naveed Ul Haq, Karl D. Nolph

Bibliographic record

VenueSeminars in Dialysis · 2001
Typereview
Languageen
FieldMedicine
TopicDialysis and Renal Disease Management
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePeritoneal dialysisIntensive care medicineInternal medicine

Abstract

fetched live from OpenAlex

The role of peritoneal dialysis (PD) as a modality in renal replacement therapy has been well established. In this article we review various aspects in the evolution of PD, with special emphasis on adequacy. Until the late 1950s PD was still considered as a last resort in the treatment of terminal uremia. The introduction of a chronic indwelling catheter made chronic PD possible. The concept of continuous ambulatory peritoneal dialysis (CAPD), proposed in 1975, had a major impact on the way PD was performed later. The value of determining the adequacy, using urea clearance normalized to total body water (Kt/V) or creatinine clearance normalized to body surface area, was clearly highlighted by the Canada-USA (CANUSA) study. Introduction of standardized peritoneal equilibration tests has been very helpful in enhancing the efficiency of PD. In 1995 the National Kidney Foundation-Dialysis Outcomes Quality Initiatives (NKF-DOQI) established guidelines to improve patient survival and outcome on dialysis. These guidelines established minimum criteria for PD adequacy. Compliance and malnutrition remain important factors determining the efficacy of PD. The "healthy start" concept emphasizes an early start of dialysis in patients with end-stage renal disease (ESRD). The quest for an ideal PD modality has recently led to renewed interest in the idea of continuous flow peritoneal dialysis (CFPD). PD continues to grow and at the same time faces many challenges. Its role as a renal replacement therapy is likely to evolve further in the years to come.

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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.977
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.027
GPT teacher head0.324
Teacher spread0.297 · 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 designOther design
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

Citations4
Published2001
Admission routes1
Has abstractyes

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