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A study of 8 hour long night dialysis with the Aksys PHD dialysis system

2005· article· en· W2057867399 on OpenAlexvenueno aff
C.M. Kjellstrand, C R Blagg, Todd S. Ing, Belinda Young

Bibliographic record

VenueHemodialysis International · 2005
Typearticle
Languageen
FieldMedicine
TopicDialysis and Renal Disease Management
Canadian institutionsnot available
Fundersnot available
KeywordsLiterDialysisMedicineHemodialysisUreaCreatinineKt/VExtracorporealUrologySurgeryAnimal scienceInternal medicineChemistryBiochemistry

Abstract

fetched live from OpenAlex

The Aksys PHD system is designed for short quotidian dialysis employing a 52‐liter batch of ultrapure dialysate and up to 30 in situ hot water reuses of the entire extracorporeal circuit including a 40‐liter physical cleaning before each dialysis. Methods: We studied the effect of the 52‐liter tank during 108 long 5–8 hour dialysis 3.5–6 times/week in 5 patients and one 50‐liter patient simulator for 4 weeks. Phosphate (PO4), beta‐2 microglobulin (b‐2), urea (BUN), and creatinine (creat) were measured pre‐, during, and post‐dialysis 86 times and in total dialysate 74 times during long dialysis. Tank saturation, Kt/V, and monthly chemistries were also measured. Results: Patient weight 76 ± 2 kg, QB 234 ± 23 ml/min, QD 498 ± 13 ml/min. Dialysate was recirculated 4.8 times during 8 hours. Analyte Short Long dialysis p Pre‐BUN 70 ± 18 49 ± 15 <0.0001 Pre‐creat 12 ± 3 10 ± 2 <0.0002 Pre‐PO4 5.2 ± 1.5 4.1 ± 1.1 <0.003 Pre‐b‐2 34.0 ± 5.3 27.8 ± 4.5 <0.0001 All patients on 8 hrs × 5 dialyses/week stopped phosphate binders within 3 weeks. eKt/V(urea) rose to 0.5 in one hour and then slowly to 0.8 at 8 hours. Weekly stdKt/V: Dialyses/week/Hrs: 2 5 8 5 2.2 2.7 3.0 6 2.7 3.4 3.6 7 3.1 3.8 4.4 At 8 hrs the tank was 99 ± 8% saturated with BUN, 86 ± 12% with creat, 77 ± 18% with PO4, and only 12 ± 5% with b‐2. Total removal per dialysis increased 2 gm BUN, 0.4 gm creat, 0.4 gm PO4, and 40 mg b‐2. The decline per reuse in conductivity clearance was only 0.7 ± 1.2% during short and 1.4 ± 1.4% during long dialysis (p = 0.11). There was no change in monthly chemistries or hematologies. Discussion: The data show that the Aksys PHD is very effective for long 8‐hour dialysis. The data for PO4 and b‐2 are the same as reported for conventional dialysis machines using 5 times as much dialysate, and the weekly stdKt/V if the PHD is used every night is twice the standard defined by K/DOQI. The exceptional cleanliness and biocompatibility by way of the one‐per‐month reuse should be a great advantage to patients. The full automatization saves the patient one hour every night and 30 minutes every morning. The PHD also economizes on filters and dialysate and is good for the environment.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.016
GPT teacher head0.256
Teacher spread0.241 · 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

Citations0
Published2005
Admission routes1
Has abstractyes

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