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Record W2555826161 · doi:10.1111/hdi.12511

Bioimpedance monitoring of cellular hydration during hemodialysis therapy

2016· article· en· W2555826161 on OpenAlexvenueno aff
Leslie D. Montgomery, Richard Montgomery, Wayne A. Gerth, Susie Q. Lew, Michael D. Klein, Julian M. Stewart, Marvin S. Medow, Manuel T. Velasquez

Bibliographic record

VenueHemodialysis International · 2016
Typearticle
Languageen
FieldMedicine
TopicBody Composition Measurement Techniques
Canadian institutionsnot available
FundersNational Institute of Diabetes and Digestive and Kidney Diseases
KeywordsHemodialysisExtracellular fluidMedicineIntravascular volume statusDialysisIntracellular FluidIntracellularInterstitial fluidBlood volumeExtracellularFluid compartmentsUrologyCardiologyInternal medicineIntensive care medicineChemistryHemodynamicsBiochemistry

Abstract

fetched live from OpenAlex

Introduction The aim of this paper is to describe and demonstrate how a new bioimpedance analytical procedure can be used to monitor cellular hydration of End Stage Renal Disease (ESRD) patients during hemodialysis (HD). Methods A tetra-polar bioimpedance spectroscope (BIS), (UFI Inc., Morro Bay, CA), was used to measure the tissue resistance and reactance of the calf of 17 ESRD patients at 40 discrete frequencies once a minute during dialysis treatment. These measurements were then used to derive intracellular, interstitial, and intravascular compartment volume changes during dialysis. Findings The mean (± SD) extracellular resistance increased during dialysis from 92.4 ± 3.5 to 117.7 ± 5.8 Ohms. While the mean intracellular resistance decreased from 413.5 ± 11.7 to 348.5 ± 8.2 Ohms. It was calculated from these data that the mean intravascular volume fell 9.5%; interstitial volume fell 33.4%; and intracellular volume gained 20.3%. Discussion These results suggest that an extensive fluid shift into the cells may take place during HD. The present research may contribute to a better understanding of how factors that influence fluid redistribution may affect an ESRD patient during dialysis. In light of this finding, it is concluded that the rate of vascular refill is jointly determined with the rate of "cellular refill" and the transfer of fluid from the intertitial compartment into the intravascular space.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.080
Threshold uncertainty score0.463

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
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 head0.028
GPT teacher head0.284
Teacher spread0.255 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations19
Published2016
Admission routes1
Has abstractyes

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