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Pharmacokinetics of tranexamic acid in patients undergoing cardiac surgery with use of cardiopulmonary bypass*

2012· article· en· W1582615997 on OpenAlexafffund
Vivek Sharma, John Fan, Angela Jerath, K. Sandy Pang, Barbara Bojko, Janusz Pawliszyn, J Karski, T. Yau, Stuart A. McCluskey, Marcin Wąsowicz

Bibliographic record

VenueAnaesthesia · 2012
Typearticle
Languageen
FieldMedicine
TopicBlood transfusion and management
Canadian institutionsUniversity of WaterlooUniversity of TorontoToronto General Hospital
FundersUniversity Health Network
KeywordsTranexamic acidMedicineCardiopulmonary bypassCardiac surgeryAnesthesiaPharmacokineticsBolus (digestion)SurgeryPharmacologyBlood loss

Abstract

fetched live from OpenAlex

We conducted a study to assess pharmacokinetics of high-dose tranexamic acid for 24 h after administration of the drug in patients undergoing cardiac surgery with cardiopulmonary bypass. High-dose tranexamic acid involved a bolus of 30 mg.kg(-1) infused over 15 min followed by a 16 mg.kg(-1) .h(-1) infusion until chest closure with a 2 mg.kg(-1) load within the pump prime. Tranexamic acid followed first-order kinetics best described using a two-compartment model, with a total body clearance that approximated the glomerular filtration rate. Mean plasma tranexamic acid concentrations during the intra-operative period and in the first 6 postoperative hours were consistently higher than the suggested threshold to achieve 100% inhibition and 80% inhibition of tissue plasminogen activator. With recent studies implicating high-dose tranexamic acid as a possible aetiology of postoperative seizures following cardiac surgery, the minimum effective yet safe dose of tranexamic acid in high-risk cardiac surgery needs to be refined.

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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.023
GPT teacher head0.232
Teacher spread0.209 · 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
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

Citations69
Published2012
Admission routes2
Has abstractyes

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