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Record W4324114385 · doi:10.1055/s-0037-1613054

Comparison of Venography and Ultrasound for the Diagnosis of Asymptomatic Deep Vein Thrombosis in the Upper Body in Children

2002· article· en· W4324114385 on OpenAlexaff
Christoph Male, Peter Chait, Jeffrey S. Ginsberg, Hanna Kim, Maureen Andrew, Ron J. Anderson, Patricia McCusker, Chih-Hang John Wu, Thomas C. Abshire, Irene Cherrick, Donald H. Mahoney, Lesley Mitchell

Bibliographic record

VenueThrombosis and Haemostasis · 2002
Typearticle
Languageen
FieldMedicine
TopicVenous Thromboembolism Diagnosis and Management
Canadian institutionsBC Children's HospitalChildren's Hospital of Western OntarioBayer (Canada)Alberta Children's HospitalChildren's Hospital of Eastern OntarioMcMaster UniversityHospital for Sick Children
Fundersnot available
KeywordsVenographyMedicineRadiologyThrombosisVenous thrombosisUltrasoundLower limbs venous ultrasonographyDeep veinAsymptomaticInternal jugular veinVeinSurgery

Abstract

fetched live from OpenAlex

Summary Deep vein thrombosis (DVT) in children occurs primarily in the upper body venous system. This prospective diagnostic study compared bilateral venography and ultrasound for detection of DVT in the upper venous system in 66 children with acute lymphoblastic leukemia. Results were interpreted by central blinded adjudication. Deep venous thrombosis occurred in 29% (19/66) patients. While 15/19 DVT were detected by venography (sensitivity 79%), only 7/19 were detected by ultrasound (sensitivity 37%). The 12 DVT detected by venography but not by ultrasound were located in the subclavian vein or more central veins. Three of 4 DVT detected by ultrasound but not by venography were in the jugular vein. We conclude that ultrasound is insensitive for DVT in the central upper venous system but may be more sensitive than venography in the jugular veins. A combination of both venography and ultrasound is required for screening for DVT in the upper venous system.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.636

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.059
GPT teacher head0.340
Teacher spread0.281 · 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 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

Citations152
Published2002
Admission routes1
Has abstractyes

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