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Record W4403145846 · doi:10.1016/j.avsurg.2024.100339

Neoplastic material inducing acute limb ischemia during bilobectomy surgery for the treatment of lung cancer

2024· article· en· W4403145846 on OpenAlexaff
C. Marchand, Ievgen Gegiia, Félix H. Savoie-White, Pascal Rhéaume

Bibliographic record

VenueAnnals of Vascular Surgery - Brief Reports and Innovations · 2024
Typearticle
Languageen
FieldMedicine
TopicManagement of metastatic bone disease
Canadian institutionsHôpital Saint-François d'Assise
Fundersnot available
KeywordsMedicineLung cancerCancerLungLimb ischemiaSurgeryIschemiaPathologyInternal medicine

Abstract

fetched live from OpenAlex

• Acute limb ischemia caused by neoplastic embolism after bilobectomy surgery is rare but highly morbid. • Emergent vascular surgery consultation is essential in all cases of acute limb ischemia. • Routine pathological examination of all thrombectomy material should be standard to identify potential tumor embolism. Arterial tumor embolization is a severe but rare complication in lung cancer, especially during surgical interventions. We present the case of acute lower limb ischemia developed during a bilobectomy surgery for non-small cell lung carcinoma. Postoperative embolectomy was performed after a CT angiogram identified an occlusive thrombus in the left common iliac artery. Pathological analysis confirmed non-small cell lung carcinoma within the thrombus. Despite successful surgery, the patient later developed cerebral metastasis and chose medical assistance in dying. This case underscores the importance of adopting an open revascularization approach for patients suspected of acute arterial occlusion caused by intraluminal tumors.

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)0.000
metaresearch head score (Gemma)0.002
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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.046
GPT teacher head0.332
Teacher spread0.286 · 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
Published2024
Admission routes1
Has abstractyes

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Same venueAnnals of Vascular Surgery - Brief Reports and InnovationsSame topicManagement of metastatic bone diseaseFrench-language works237,207