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Record W2922842526 · doi:10.1097/aco.0000000000000728

Tranexamic acid and perioperative bleeding in children

2019· review· en· W2922842526 on OpenAlexaff
Susan M. Goobie, David Faraoni

Bibliographic record

VenueCurrent Opinion in Anaesthesiology · 2019
Typereview
Languageen
FieldMedicine
TopicBlood transfusion and management
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsMedicineTranexamic acidDosingPerioperativeRegimenBlood managementBlood productAntifibrinolyticBlood transfusionAnesthesiaPharmacokineticsIntensive care medicineBlood lossSurgeryPharmacology

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: Perioperative bleeding and blood product transfusion are associated with significant morbidity and mortality. Prevention and optimal management of bleeding decreases risk and lowers costs. Tranexamic acid (TXA) is an antifibrinolytic agent that reduces bleeding and transfusion in a broad number of adult and pediatric surgeries, as well as in trauma and obstetrics. This review highlights the current pediatric indications and contraindications of TXA. The efficacy and safety profile, given current and evolving research, will be covered. RECENT FINDINGS: Based on the published evidence, prophylactic or therapeutic TXA administration is a well-tolerated and effective strategy to reduce bleeding, decrease allogeneic blood product transfusion, and improve pediatric patients' outcomes. TXA is now recommended in recent guidelines as an important part of pediatric blood management protocols. SUMMARY: Based on TXA pharmacokinetics, the authors recommend a dosing regimen of between 10 to 30 mg/kg loading dose followed by 5 to 10 mg/kg/h maintenance infusion rate for pediatric trauma and surgery. Maximal efficacy and minimal side-effects with this dosage regime will have to be determined in larger prospective trials including high-risk groups. Furthermore, future research should focus on determining the ideal TXA plasma therapeutic concentration for maximum efficacy and minimal side-effects.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.984
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.104
GPT teacher head0.390
Teacher spread0.286 · 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.

Study designOther design
Domainnot available
GenreReview

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

Citations98
Published2019
Admission routes1
Has abstractyes

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