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Comparison of Topiramate Concentrations in Plasma and Serum by Fluorescence Polarization Immunoassay

2000· article· en· W2330400695 on OpenAlex
David J. Berry, Philip N. Patsalos

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

VenueTherapeutic Drug Monitoring · 2000
Typearticle
Languageen
FieldMedicine
TopicEpilepsy research and treatment
Canadian institutionsSt. Thomas Hospital
Fundersnot available
KeywordsFluorescence polarization immunoassayTopiramateChromatographyTherapeutic drug monitoringChemistryCentrifugationImmunoassayBlood samplingPharmacologyMedicineDrugInternal medicineEpilepsyImmunology

Abstract

fetched live from OpenAlex

Topiramate has been recently licensed as an antiepileptic drug. A fluorescence polarization immunoassay (FPIA), the Innofluor, has been developed to determine topiramate in heparinized plasma. Since therapeutic drug monitoring laboratories may not have control over collection of the samples submitted to them, it is important for analytical methods to be robust and able to cope with any specimen. The effect of different anticoagulants on the topiramate FPIA assay was investigated by collecting blood from 50 patients with epilepsy being maintained on a range of topiramate doses as part of their therapy. After venesection the blood was divided among four tubes: plain, heparinized, EDTA, and fluoride/oxalate. Erythrocytes were separated by centrifugation and supernatant fluid frozen to await duplicate assay by FPIA. Results were compared by means of Altman and Bland difference plots which indicated that there was no significant difference between values obtained with heparinized plasma and the other fluids. It was concluded that the Innofluor assay is robust and gives similar results when blood samples are collected into any of the specified anticoagulants.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.205
Threshold uncertainty score0.294

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 head0.340
Teacher spread0.314 · 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