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Record W2460596546 · doi:10.1038/cti.2016.39

Platelets and coagulation in infection

2016· review· en· W2460596546 on OpenAlexaff
Rachelle P. Davis, Sarah Miller‐Dorey, Craig N. Jenne

Bibliographic record

VenueClinical & Translational Immunology · 2016
Typereview
Languageen
FieldImmunology and Microbiology
TopicNeutrophil, Myeloperoxidase and Oxidative Mechanisms
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsCoagulationPlateletMedicineImmunologyMicrobiologyBiologyInternal medicine

Abstract

fetched live from OpenAlex

Disseminated intravascular coagulation (DIC) is a frequent complication in sepsis that is associated with worse outcomes and higher mortality in patients. In addition to the uncontrolled generation of thrombi throughout the patient's vasculature, DIC often consumes large quantities of clotting factors leaving the patient susceptible to hemorrhaging. Owing to these complications, patients often receive anticoagulants to treat the uncontrolled clotting, often with mixed outcomes. This lack of success with the current array of anticoagulants can be partly explained by the fact that during sepsis clotting is often initiated by the immune system. Systemic inflammation has the capacity to activate and amplify coagulation and, as such, potential therapies for the treatment of sepsis-associated DIC need to address the interaction between inflammation and coagulation. Recent studies have suggested that platelets and neutrophil extracellular traps (NETs) are the key mediators of infection-induced coagulation. This review explores current anticoagulant therapies and discusses the development of future therapies to target platelet and NET-mediated coagulation.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.989
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.095
GPT teacher head0.400
Teacher spread0.305 · 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

Citations75
Published2016
Admission routes1
Has abstractyes

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