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Record W1976236563 · doi:10.1117/1.2357611

Hemodialysis monitoring in whole blood using transmission and diffuse reflection spectroscopy: a pilot study

2006· article· en· W1976236563 on OpenAlexafffund
Neil Lagali, Kevin D. Burns, Deborah Zimmerman, Réjean Munger

Bibliographic record

VenueJournal of Biomedical Optics · 2006
Typearticle
Languageen
FieldMedicine
TopicDialysis and Renal Disease Management
Canadian institutionsUniversity of Ottawa
FundersCanadian Institutes of Health ResearchUniversity of Ottawa
KeywordsHemodialysisDiffuse reflectance infrared fourier transformSpectroscopyMedicineReflection (computer programming)Diffuse reflectionPrincipal component analysisMaterials scienceBiomedical engineeringNuclear magnetic resonanceOpticsInternal medicineChemistryComputer science

Abstract

fetched live from OpenAlex

Visible and near infrared transmission and diffuse reflection spectroscopy were used to monitor changes in whole blood resulting from hemodialysis treatment for end-stage renal disease. Blood samples from 8 patients on chronic hemodialysis therapy were measured in the 500- to 1700-nm wavelength range immediately before and after a single treatment. Principal component scores characteristic of each spectrum were derived, and mean pre- and posttreatment scores of the first principal component indicated a significant treatment-dependent change in both optical transmission (P = 0.004) and diffuse reflection (P < 0.001). Significant treatment-induced change persisted (P < 0.05) when the first four principal components were used to account for >97% of the treatment-dependent spectral variation. Some blood spectral changes expressed in terms of difference spectra (posttreatment - pretreatment) were consistent with standard clinical indicators of weight reduction, urea reduction, and potassium change, with probable origins at a molecular level. The results indicate the feasibility of using optical transmission and diffuse reflection spectroscopy to characterize clinically relevant blood changes for the future development of more comprehensive indicators of hemodialysis efficacy and long-term clinical outcomes. Moreover, the optical techniques employed are adaptable for potential online monitoring of blood changes during the hemodialysis treatment.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.850
Threshold uncertainty score0.321

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 head0.026
GPT teacher head0.309
Teacher spread0.283 · 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

Citations7
Published2006
Admission routes2
Has abstractyes

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