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Record W3209684373 · doi:10.1186/s12301-021-00250-x

Endoscopic ultrasound-guided trans-duodenal fine-needle biopsy of a small renal mass: case report and review of the literature

2021· article· en· W3209684373 on OpenAlexaff
Justin Kwong, Gary R. May, Michael Ordon

Bibliographic record

VenueAfrican Journal of Urology · 2021
Typearticle
Languageen
FieldMedicine
TopicRenal cell carcinoma treatment
Canadian institutionsUniversity of TorontoSt. Michael's Hospital
Fundersnot available
KeywordsMedicineBiopsyHilum (anatomy)RadiologyPercutaneousDuodenumRenal hilumRenal massEndoscopic ultrasoundSurgeryKidneyNephrectomyInternal medicine

Abstract

fetched live from OpenAlex

Abstract Background The incidental detection of small renal masses (SRMs) is increasing and biopsy to obtain pathological diagnosis is increasingly proposed as a diagnostic tool to guide further management. Renal mass biopsies are traditionally performed via a percutaneous approach. However, this is not always feasible due to anatomical limitations. A rarely reported alternative biopsy approach for SRMs is endoscopic ultrasound (EUS)-guided fine-needle biopsy (FNB). Herein, we describe a case of EUS-guided trans-duodenal FNB for a SRM that was not amenable to standard percutaneous biopsy. Case presentation A 48-year-old man was incidentally found to have a right-sided SRM measuring 2.9 × 2.2 × 2.4 cm during evaluation for a hernia. It was anterior, interpolar, completely endophytic and near the renal hilum. The tumor was not amenable to traditional percutaneous biopsy due to its anterior location. However, the renal mass was in close proximity to the descending duodenum and so it was felt that an EUS-guided trans-duodenal FNB would be feasible. The procedure was successful without any complications. The specimen adequacy was satisfactory for evaluation and consistent with renal papillary carcinoma with WHO/ISUP grade 3 nuclear changes. Conclusion Our case report demonstrated that EUS-guided trans-duodenal FNB was a safe and feasible approach to obtaining biopsy tissue diagnosis of a SRM that was not amenable to percutaneous biopsy.

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)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.380
Threshold uncertainty score0.418

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
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 head0.022
GPT teacher head0.261
Teacher spread0.239 · 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 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

Citations1
Published2021
Admission routes1
Has abstractyes

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