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Record W2051064714 · doi:10.1097/mat.0b013e318169271e

Can Extracellular Fluid Volume Expansion in Hemodialysis Patients Be Safely Reduced Using the Hemocontrol Biofeedback Algorithm? A Randomized Trial

2008· article· en· W2051064714 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

VenueASAIO Journal · 2008
Typearticle
Languageen
FieldMedicine
TopicDialysis and Renal Disease Management
Canadian institutionsWestern UniversityHumber River Regional Hospital
Fundersnot available
KeywordsHemodialysisExtracellular fluidRandomized controlled trialMedicineBiofeedbackUltrafiltration (renal)Clinical endpointBlood volumeInternal medicineCardiologyPhysical therapyExtracellularChemistry

Abstract

fetched live from OpenAlex

Extracellular fluid volume (ECFV) expansion in hemodialysis patients is associated with increased mortality. Attempts to remove excess fluid often result in intradialytic hypotension (IDH). Blood volume monitoring has been used to aid selection of ultrafiltration rates and dialysate conductivity to minimize IDH. Automating ultrafiltration and dialysate conductivity using the Hemocontrol Biofeedback System (HBS) has reduced IDH in IDH-prone subjects. We undertook a randomized controlled trial to determine if the HBS could safely reduce ECFV in ECF-expanded subjects. Patients with ECFV >45% of total body water were randomized to receive hemodialysis by either HBS or best clinical practices for 6 months. The primary endpoint was change in ECFV; exploratory variables included frequency of IDH, interdialytic weight gain, and changes in serum Na. Treatment with HBS did not result in any change in ECFV, even after multivariable adjustment. The frequency of IDH was however significantly lower with HBS when compared with best clinical practices without differences in other variables.

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)0.002
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: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.135
Threshold uncertainty score0.688

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
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 head0.021
GPT teacher head0.254
Teacher spread0.233 · 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