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The prevention of hospital‐acquired venous thromboembolism in the United Kingdom

2008· review· en· W2007306250 on OpenAlexaff
Beverley J. Hunt

Bibliographic record

VenueBritish Journal of Haematology · 2008
Typereview
Languageen
FieldMedicine
TopicVenous Thromboembolism Diagnosis and Management
Canadian institutionsSt. Thomas Hospital
Fundersnot available
KeywordsNiceMedicineExcellenceVenous thromboembolismExpert opinionDabigatranIntensive care medicineFamily medicineMedical emergencySurgeryWarfarinInternal medicine

Abstract

fetched live from OpenAlex

Hospital-acquired venous thromboembolism (VTE) remains the number one safety issue in hospitals and is estimated to cause more preventable deaths than the more publicized hospital-acquired infection. There has been a failure of implementation of thromboprophylaxis (TP), mainly because of lack of awareness among health professionals, despite the large number of evidence-based studies available. The situation in the UK is gradually changing because of tireless campaigning by politicians, a charity and key opinion leaders. In response, the Department of Health has issued a national risk assessment tool, and National Institute of Clinical Excellence (NICE) guidelines for the prevention of VTE in all hospitalised patients, which will be available in August 2009. Although NICE guidelines are only applicable in England, it is to be hoped Northern Ireland, Wales and Scotland will also follow. Despite this, the consensus of expert opinion is that TP needs mandating to prevent pockets of non-adherence. Low molecular weight heparins are currently the gold standard pharmacological agent for TP; but are likely to be superseded within the next 5 years by new classes of oral anticoagulants, such as dabigatran and rivaroxiban, which are already licensed for TP after orthopaedic surgery.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.896
Threshold uncertainty score0.817

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.051
GPT teacher head0.342
Teacher spread0.290 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations37
Published2008
Admission routes1
Has abstractyes

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