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Record W2995282550 · doi:10.1002/ajum.12188

Point‐of‐care ultrasound for deep venous thrombosis of the lower limb

2019· review· en· W2995282550 on OpenAlexaff
David Canty, Kavi Mufti, Lindsay Bridgford, André Denault

Bibliographic record

VenueAustralasian Journal of Ultrasound in Medicine · 2019
Typereview
Languageen
FieldMedicine
TopicVenous Thromboembolism Diagnosis and Management
Canadian institutionsUniversité de MontréalMontreal Heart Institute
FundersUniversity of Melbourne
KeywordsMedicineVenous thrombosisUltrasoundPoint of care ultrasoundRadiologyVenographyDuplex (building)PULMONARY EMBOLUSLower limbPulmonary embolismThrombosisSurgery

Abstract

fetched live from OpenAlex

The incidence and morbidity of deep venous thrombosis (DVT) and pulmonary embolus are high. Although efforts to increase screening for DVT have been recommended, this is limited by resources. Venous duplex ultrasound has replaced venography as the first-line investigation of choice for DVT, increasing availability and reducing patient exposure to radiation and intravenous contrast. Furthermore, an abbreviated ultrasound where DVT is inferred from incomplete venous compressibility has an equivalent accuracy to venous duplex, requiring less time and training enabling its widespread use by emergency, critical care and anaesthesia clinicians. In this review, the evolution and method of lower limb venous compression ultrasound is described along with evidence for its use in patients at high risk for DVT in these clinical settings.

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)0.002
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 score0.740
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0070.002
Bibliometrics0.0010.001
Science and technology studies0.0000.001
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 head0.044
GPT teacher head0.353
Teacher spread0.309 · 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 designNot applicable
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

Citations13
Published2019
Admission routes1
Has abstractyes

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