MétaCan
Menu
Back to cohort
Record W2921341733 · doi:10.1159/000496480

A Novel Fluorescent Clinical Method to Rapidly Quantify Plasma Volume

2019· article· en· W2921341733 on OpenAlexaff
Bruce A. Molitoris, Anthony G. George, Patrick Murray, Daniel Meier, Erinn S. Reilly, Erin Barreto, Ruben M. Sandoval, Dana V. Rizk, Andrew Shaw, W. Frank Peacock

Bibliographic record

VenueCardiorenal Medicine · 2019
Typearticle
Languageen
FieldMedicine
TopicHemodynamic Monitoring and Therapy
Canadian institutionsUniversity of Alberta
FundersNational Center for Advancing Translational SciencesNational Institute of Diabetes and Digestive and Kidney Diseases
KeywordsHematocritFluoresceinChromatographyMedicineDextranFluorescenceSalineIndocyanine greenDilutionAlbuminRhodamine 123RhodamineUrologyVolume of distributionPharmacokineticsNuclear medicineBiomedical engineeringChemistryPathologyInternal medicineBiochemistry

Abstract

fetched live from OpenAlex

OBJECTIVES: To determine the performance of a rapid fluorescent indicator technique for measuring plasma volume (PV). METHODS: This was an open-label, observational evaluation of a two-component intravenous visible fluorescent dye technique to rapidly measure PV in 16 healthy subjects and 16 subjects with chronic kidney disease (8 stage 3 and 8 stage 4 CKD), at 2 clinical research sites. The method consisted of a single intravenous injection of 12 mg of a large 150-kDa carboxy-methyl dextran conjugated to a fluorescent rhodamine-derived dye as the PV marker (PVM), and 35 mg of a small 5-kDa carboxy-methyl dextran conjugated to fluorescein, the renal clearance marker. Dye concentrations were quantified 15 min after the injections for initial PV measurements using the indicator-dilution principle. Additional samples were taken over 8 h to evaluate the stability of the PVM as a determinant of PV. Blood volumes (BV) were calculated based on PV and the subject's hematocrit. Pharmacokinetic parameters were calculated from the plasma concentration data taken over several days using noncompartmental methods (Phoenix WinNonlin®). Linear correlation and Bland-Altman plots were used to compare visible fluorescent injectate-measured PV compared to Nadler's formula for estimating PV. Finally, 8 healthy subjects received 350 mL infusion of a 5% albumin solution in normal saline over 30 min and a repeat PV determination was then carried out. RESULTS: PV and BV varied according to weight and body surface area, with PV ranging from 2,115 to 6,234 mL and 28.6 to 41.9 mL/kg when weight adjusted. Both parameters were stable for > 6 h with repeated plasma measurements of the PVM. There was no difference between healthy subjects and CKD subjects. Overall, there was general agreement with Nadler's estimation formula for the mean PV in subjects. A 24-h repeat dose measurement in 8 healthy subjects showed PV variability of 98 ± 121 mL (mean = 3.8%). Additionally, following an intravenous bolus of 350 mL of a 5% albumin solution in normal saline in 8 healthy subjects, the mean (SD) measured increase in PV was 356 (±50.0) mL post-infusion. There were no serious adverse events reported during the study. CONCLUSIONS: This minimally invasive fluorescent dye approach safely allowed for rapid, accurate, and reproducible determination of PV, BV, and dynamic monitoring of changes following fluid administration.

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)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.003
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.047
GPT teacher head0.394
Teacher spread0.347 · 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 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

Citations6
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueCardiorenal MedicineSame topicHemodynamic Monitoring and TherapyFrench-language works237,207