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Record W4283388489 · doi:10.1002/dta.3338

Analysis of dried blood spots is a feasible alternative for detecting ephedrine in doping control

2022· article· en· W4283388489 on OpenAlexfundno aff
Sara Amalie Solheim, Andreas Thomas, Thomas K. Ringsted, Mario Thevis, Andreas Breenfeldt Andersen, Henrik Sørensen, Nikolai Baastrup Nordsborg, Jakob Mørkeberg

Bibliographic record

VenueDrug Testing and Analysis · 2022
Typearticle
Languageen
FieldMedicine
TopicHormonal and reproductive studies
Canadian institutionsnot available
FundersInternational Olympic CommitteeWorld Anti-Doping AgencyDivision of Mathematical SciencesAnti Doping Danmark
KeywordsEphedrineDried bloodSpotsChromatographyMedicineChemistryPharmacologyPathology

Abstract

fetched live from OpenAlex

Dried blood spot (DBS) testing allows fast, easy and minimally invasive collection of microvolumes of blood. In an anti-doping context, DBS testing has particular relevance for substances prohibited in-competition only such as ephedrine, which is currently detected by urine analysis, because DBS can add information about the blood drug concentrations during the in-competition period. Several collection methods and devices exist for DBS collection from different anatomical sites. Thus, agreements between concentrations of target analytes in DBS samples from different sampling sites, along with between DBS and those in conventional venous plasma samples, need to be evaluated. Herein, we collected matched upper-arm DBS, fingerprick DBS and venous plasma samples from eight healthy male subjects in an 8-h period following oral administrations of 20 mg ('low dose') and 60 mg ('high dose') of ephedrine. We show that the use of alternative sampling sites and matrices is a feasible possibility for ephedrine analysis in doping control. We observed very good agreement between collection sites and that specificity and sensitivity can be upheld despite use of an alternative collection site. However, potential concentration differences between DBS and venous plasma should be considered, and distinct threshold might be necessary if implementing both blood matrices in ephedrine analysis.

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)0.001
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 score0.237
Threshold uncertainty score0.444

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.004
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 head0.031
GPT teacher head0.294
Teacher spread0.263 · 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 designObservational
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

Citations8
Published2022
Admission routes1
Has abstractyes

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