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Cyclosporine pharmacokinetics and blood pressure responses after conversion to once‐daily dosing in maintenance liver transplant patients

2007· article· en· W2082260239 on OpenAlexaff
John M. Kovarik, Federico Villamil, Alejandra Otero, Gary Levy, Stephen V. Lynch, Umberto Cillo, Lutz Fischer, Björn Nashan, S. Pollard, Luciano De Carlis

Bibliographic record

VenueClinical Transplantation · 2007
Typearticle
Languageen
FieldMedicine
TopicRenal Transplantation Outcomes and Treatments
Canadian institutionsDalhousie UniversityToronto General Hospital
FundersEli Lilly and Company
KeywordsMedicineDosingPharmacokineticsLiver transplantationBlood pressurePharmacologyAnesthesiaIntensive care medicineTransplantationInternal medicine

Abstract

fetched live from OpenAlex

In this six-month randomized multicenter trial, we characterized cyclosporine pharmacokinetics and blood pressure profiles in maintenance liver transplant patients converting from twice-daily to once-daily cyclosporine dosing. A total of 60 patients were randomized as follows: group A (n = 14) maintained twice-daily dosing; group B (n = 24) converted to once-daily dosing at the same total daily dose as pre-conversion; and group C (n = 22) was treated the same as group B but with a 25% reduction in dose and C2 at two to three wk post-conversion. After conversion to once-daily dosing in groups B and C, trough blood levels (C0) did not change; whereas, C2 nearly doubled. The total daily area under the concentration-time curve AUC(0-24) increased by 29%. After the dose reduction in group C, the AUC(0-24) was similar to the pre-conversion value. Hence, a 25-30% dose reduction can be considered after conversion to once-daily dosing. In the study observation period in weeks 4-15, the median (25-75 percentile) C2 was 568 (469-750) ng/mL for group A; 1055 (840-1224) ng/mL for group B; and 764 (575-959) ng/mL for group C. Conversion to once-daily dosing was associated with a decrease in nighttime mean arterial blood pressure.

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)0.000
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 score0.006
Threshold uncertainty score0.733

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 head0.029
GPT teacher head0.350
Teacher spread0.320 · 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

Citations7
Published2007
Admission routes1
Has abstractyes

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