MétaCan
Menu
Back to cohort
Record W2124587829 · doi:10.1136/eb-2012-100872

Tranexamic acid reduces blood transfusion in surgical patients while its effects on thromboembolic events and mortality are uncertain

2012· letter· en· W2124587829 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEvidence-Based Medicine · 2012
Typeletter
Languageen
FieldMedicine
TopicBlood transfusion and management
Canadian institutionsToronto Western HospitalUniversity of Toronto
Fundersnot available
KeywordsTranexamic acidMedicineAntifibrinolyticFibrinolysisPerioperativeBlood transfusionAnesthesiaSurgeryInternal medicineBlood loss

Abstract

fetched live from OpenAlex

Commentary on: Ker K, Edwards P, Perel P, et al. Effect of tranexamic acid on surgical bleeding: systematic review and cumulative meta-analysis. BMJ 2012;344:e3054.[OpenUrl][1][Abstract/FREE Full Text][2] Surgical trauma leads to the activation of local fibrinolysis, and surgical bleeding can be significant in certain types of surgery leading to acute anaemia and the need for blood transfusion. Clinical trends have led to reductions in acceptable haemoglobin transfusion thresholds. However, growing evidence from clinical and experimental studies suggests that acute haemodilutional anaemia may reduce tissue oxygen delivery and increase perioperative morbidity and mortality.1 Therefore, there is renewed interest in antifibrinolytic agents that may reduce surgical bleeding. Surgical trauma also leads to activation of the coagulation cascade and increases the risk for thromboembolic events. Therefore, the risks of thromboembolic and other adverse effects and the benefits of antifibrinolytic agents … [1]: {openurl}?query=rft.jtitle%253DBMJ%26rft_id%253Dinfo%253Adoi%252F10.1136%252Fbmj.e3054%26rft_id%253Dinfo%253Apmid%252F22611164%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [2]: /lookup/ijlink?linkType=ABST&journalCode=bmj&resid=344/may17_1/e3054&atom=%2Febmed%2F18%2F2%2F65.atom

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.

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Commentary
About the Canadian research system: no · About a Canadian topic: no
Not applicablelow
gptno category
Domain: not available · Genre: Commentary
About the Canadian research system: no · About a Canadian topic: no
Not applicablehigh
models agreeAgreement compares identical category sets and study designs across arms.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.370
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
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 head0.059
GPT teacher head0.307
Teacher spread0.247 · 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