MétaCan
Menu
Back to cohort
Record W2132587838 · doi:10.2174/1389450033491064

Anticoagulant Therapy for Acute Lung Injury or Pneumonia

2003· review· en· W2132587838 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

VenueCurrent Drug Targets · 2003
Typereview
Languageen
FieldMedicine
TopicSepsis Diagnosis and Treatment
Canadian institutionsInstitute of Infection and Immunity
Fundersnot available
KeywordsMedicinePneumoniaSepsisIntensive care medicineCoagulationLungAnticoagulant therapyAnticoagulantInternal medicine

Abstract

fetched live from OpenAlex

Pulmonary changes in thrombin formation in patients with acute lung injury or pneumonia are remarkably similar to systemic changes in coagulation observed in septic patients. Since anticoagulant therapy has proven to be successful in the treatment of patients with sepsis, the same therapeutic strategy may benefit patients with acute lung injury or pneumonia. Based on the fact that inflammation not only leads to dysregulation of the coagulation system, but vice versa, activation of coagulation amplifies inflammatory processes as well, it can be questioned whether the advantage of anticoagulant therapy is solely related to its influence on disturbed thrombin formation. In this paper we will discuss local changes in the haemostatic balance during acute lung injury, both in pre-clinical and clinical studies. Until now, pre-clinical studies have demonstrated that interventions aimed at correction of coagulation abnormalities may form an important strategy in patients with acute lung injury in the future. Pre-clinical studies on use of anticoagulants during pneumonia are presently performed and data are underway.

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.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.906
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.001
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 head0.168
GPT teacher head0.470
Teacher spread0.302 · 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