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Record W2214805893 · doi:10.3899/jrheum.151094

Routine Hydroxychloroquine Blood Concentration Measurement in Systemic Lupus Erythematosus Reaches Adulthood

2015· letter· en· W2214805893 on OpenAlexvenueno aff
N. Costedoat‐Chalumeau, Véronique Le Guern, Jean‐Charles Piette

Bibliographic record

VenueThe Journal of Rheumatology · 2015
Typeletter
Languageen
FieldMedicine
TopicSystemic Lupus Erythematosus Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineHydroxychloroquineRheumatoid arthritisPharmacokineticsPharmacodynamicsInternal medicineWhole bloodActive metabolitePharmacologyCoronavirus disease 2019 (COVID-19)

Abstract

fetched live from OpenAlex

The benefits of hydroxychloroquine (HCQ) treatment in patients with systemic lupus erythematosus (SLE) are now clearly recognized and it has been highly recommended that all patients with SLE should be prescribed this drug1. One less well-known benefit of HCQ is related to its pharmacokinetic properties (i.e., its long half-life) and to the availability of a blood assay to measure its blood concentration. Indeed, HCQ and its metabolite levels can be quantified by high performance liquid chromatography, which is available in many centers because this type of equipment is required to monitor other drugs (antidepressants, tyrosine kinase inhibitors, antibiotics, etc.). Methods of dosage may vary slightly, but for reasons of sensitivity and reproducibility, blood HCQ concentrations ([HCQ]) should be measured in whole blood (minimum 1 ml blood sampled in EDTA or in lithium heparinate tubs). In the 1980s, Tett, et al first described this method and studied the importance of [HCQ] measurement in patients with rheumatoid arthritis (RA). They first showed that there was a great variability in [HCQ] among individuals, including in healthy volunteers and adherent patients2,3. They also found a significant, although weak, correlation between [HCQ] and clinical efficacy in RA [corresponding to the so-called pharmacokinetic/pharmacodynamic (PK-PD) effect]3,4. These data were later confirmed by Munster, et al 5. When this blood measurement became available in our center in 2000, we decided to evaluate the PK-PD relationship of HCQ in patients with SLE. Among 143 unselected patients with SLE who were all receiving 400 mg/day of HCQ, the mean [HCQ] on day 0 was 1017 ± 532 ng/ml with more than a 10-fold range of drug concentrations found after similar doses6. We observed that low [HCQ] were associated with increased disease activity, and that low baseline [HCQ] … Address correspondence to Dr. N. Costedoat-Chalumeau, Hôpital Cochin, 75014, Paris, France. E-mail: nathalie.costedoat{at}gmail.com

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
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 head0.041
GPT teacher head0.279
Teacher spread0.238 · 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 designObservational
Domainnot available
GenreCommentary

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

Citations24
Published2015
Admission routes1
Has abstractyes

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