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Record W2338299115 · doi:10.1080/14737175.2016.1181542

A critical balance: managing coagulation in patients with glioma

2016· review· en· W2338299115 on OpenAlexaff
Erin R. Morgan, Warren Mason, Catherine Maurice

Bibliographic record

VenueExpert Review of Neurotherapeutics · 2016
Typereview
Languageen
FieldMedicine
TopicVenous Thromboembolism Diagnosis and Management
Canadian institutionsUniversity of TorontoPrincess Margaret Cancer Centre
Fundersnot available
KeywordsMedicineThrombosisGliomaPerioperativeIntensive care medicineComplicationChemotherapyLow molecular weight heparinVenous thrombosisVenous thromboembolismSurgeryInternal medicine

Abstract

fetched live from OpenAlex

Cancer-associated thrombosis, including both arterial and venous thromboembolism (VTE), is a significant source of morbidity and mortality in patients with glioma. This risk is highest in the immediate postoperative period and is increased by chemotherapy, radiation, and corticosteroids. Systemic anticoagulation with low molecular weight heparin is the treatment of choice in both the therapeutic and prophylactic settings. However, these patients are also at risk of intracranial hemorrhage, a potentially catastrophic complication of anticoagulation, and this risk must be carefully balanced against the risk of VTE. In this review we outline the incidence, pathophysiology and management of thrombosis in patients with glioma, with a focus on clinical considerations including perioperative management, chemotherapy-induced thrombocytopenia, and end-of-life management.

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 score0.848
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.000
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 head0.033
GPT teacher head0.381
Teacher spread0.347 · 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

Citations8
Published2016
Admission routes1
Has abstractyes

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