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Record W2767700875

Clinical aspects of venous thromboembolism in special patient populations

2017· article· en· W2767700875 on OpenAlexfundno aff
Suzanne M. Bleker

Bibliographic record

VenueUvA-DARE (University of Amsterdam) · 2017
Typearticle
Languageen
FieldMedicine
TopicVenous Thromboembolism Diagnosis and Management
Canadian institutionsnot available
FundersCentre Hospitalier Universitaire de BordeauxAssistance publique-Hôpitaux de ParisUniversità degli Studi G. d'Annunzio Chieti - PescaraOttawa Hospital Research InstituteGeorge Washington University
KeywordsMedicinePulmonary embolismDeep veinIntensive care medicineThrombosisVenous thromboembolismDiseaseVenous thrombosisCancerEpidemiologyAnticoagulantPregnancySurgeryInternal medicine
DOInot available

Abstract

fetched live from OpenAlex

In the field of venous thromboembolism (VTE), comprising deep vein thrombosis (DVT) and pulmonary embolism (PE), incredible progression has been made throughout the centuries regarding our knowledge on the epidemiology, pathophysiology, prevention, diagnosis, treatment and prognosis of the disease. Various clinical aspects of the disease in specific patient populations and some rare forms of VTE have not yet been fully addressed. This thesis aims to evaluate several clinical elements of VTE in special patient populations. Part 1 describes several aspects of sex-specific VTE, in particular pregnancy, the use of hormonal contraceptives, and anticoagulant-associated vaginal bleeding. In part 2, the relationship between cancer and VTE is addressed, with a focus on unsuspected PE in cancer patients, which is an increasingly common finding. Part 3 aims to increase the knowledge on upper extremity deep vein thrombosis (UEDVT), a rare form of VTE. Several aspects are discussed. Finally, in part 4, insight is provided into the clinical impact of bleeding events with the use of oral factor Xa (fXa) inhibitors versus vitamin K antagonists (VKA) in patients with VTE.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.049
GPT teacher head0.310
Teacher spread0.261 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations0
Published2017
Admission routes1
Has abstractyes

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