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Record W1990654076 · doi:10.5489/cuaj.1224

Unanticipated intra-operative finding of pulmonary artery tumour thromboembolism during radical nephrectomy and caval thrombectomy: Case report and management

2013· article· en· W1990654076 on OpenAlexaffvenue
Rajan Sharda, Raymond Deutscher, Chris Christodoulou, David Horné, Darren H. Freed, Thomas McGregor

Bibliographic record

VenueCanadian Urological Association Journal · 2013
Typearticle
Languageen
FieldMedicine
TopicCardiac tumors and thrombi
Canadian institutionsSt. Boniface HospitalUniversity of Manitoba
Fundersnot available
KeywordsMedicineThrombusNephrectomyAsymptomaticPerioperativePulmonary arteryRadiologySurgeryInternal medicineKidney

Abstract

fetched live from OpenAlex

We report a case of an unanticipated intra-operative transesophageal echocardiography (TEE) finding of pulmonary artery thromboembolism in a 72-year-old woman being prepared for radical nephrectomy and caval thrombectomy. Upon intra-operative TEE to evaluate the extent of caval thrombus, we found a pulmonary artery tumour thromboembolism in an otherwise asymptomatic patient after induction and prior to surgery. A chest computed tomography confirmed a large saddle tumour thromboembolus. A multidisciplinary approach was used to facilitate radical nephrectomy with caval thrombectomy and pulmonary artery thromboembolectomy. This case shows the importance of adequate perioperative imaging and use of intra-operative TEE to evaluate the extent of disease. To our knowledge, we are the first to present a case of RCC with cava tumour thrombus in which the pulmonary artery tumour thromboembolism was detected incidentally on intraoperative TEE.

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)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.001
Science and technology studies0.0030.002
Scholarly communication0.0020.002
Open science0.0020.002
Research integrity0.0070.005
Insufficient payload (model declined to judge)0.0010.001

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 head0.011
GPT teacher head0.242
Teacher spread0.232 · 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 designCase report
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
Published2013
Admission routes2
Has abstractyes

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