MétaCan
Menu
Back to cohort
Record W2791455933 · doi:10.3390/diagnostics8010013

Comparison of a New Multiplex Immunoassay for Measurement of Ferritin, Soluble Transferrin Receptor, Retinol-Binding Protein, C-Reactive Protein and α1-Acid-glycoprotein Concentrations against a Widely-Used s-ELISA Method

2018· article· en· W2791455933 on OpenAlexafffund
Crystal D Karakochuk, Amanda Henderson, Kaitlyn L. I. Samson, Abeer M. Aljaadi, Angela M. Devlin, Elodie Becquey, James P. Wirth, Fabian Rohner

Bibliographic record

VenueDiagnostics · 2018
Typearticle
Languageen
FieldMedicine
TopicIron Metabolism and Disorders
Canadian institutionsBC Children's HospitalUniversity of British Columbia
FundersUniversity of British Columbia
KeywordsMultiplexFerritinSoluble transferrin receptorImmunoassayTransferrinTransthyretinBiomarkerRetinol binding proteinRetinol binding protein 4NephelometryTransferrin receptorMedicineChemistryImmunologyBiologyInternal medicineBiochemistryAntibodyIron deficiencyRetinolBioinformaticsAnemiaIron status

Abstract

fetched live from OpenAlex

Recently, a multiplex ELISA (Quansys Biosciences) was developed that measures ferritin, soluble transferrin receptor (sTfR), retinol-binding protein (RBP), C-reactive protein (CRP), α1-acid glycoprotein (AGP), thyroglobulin, and histidine-rich protein 2. Our primary aim was to conduct a method-comparison study to compare five biomarkers (ferritin, sTfR, RBP, CRP, and AGP) measured with the Quansys assay and a widely-used s-ELISA (VitMin Lab, Willstaett, Germany) with use of serum samples from 180 women and children from Burkina Faso, Cambodia, and Malaysia. Bias and concordance were used to describe the agreement in values measured by the two methods. We observed poor overall agreement between the methods, both with regard to biomarker concentrations and deficiency prevalence estimates. Several measurements were outside of the limit of detection with use of the Quansys ELISA (total n = 42 for ferritin, n = 2 for sTfR, n = 0 for AGP, n = 5 for CRP, n = 22 for RBP), limiting our ability to interpret assay findings. Although the Quansys ELISA has great potential to simplify laboratory analysis of key nutritional and inflammation biomarkers, there are some weaknesses in the procedures. Overall, we found poor comparability of results between methods. Besides addressing procedural issues, additional validation of the Quansys against a gold standard method is warranted for future research.

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)0.001
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.008
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.069
GPT teacher head0.350
Teacher spread0.282 · 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.

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
Published2018
Admission routes2
Has abstractyes

Explore more

Same venueDiagnosticsSame topicIron Metabolism and DisordersFrench-language works237,207