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Record W4396842051 · doi:10.1016/j.radcr.2024.04.055

Renal metastasis from esophageal adenocarcinoma: A rare recurrence

2024· article· en· W4396842051 on OpenAlexaff
Indranil Balki, David Wang

Bibliographic record

VenueRadiology Case Reports · 2024
Typearticle
Languageen
FieldMedicine
TopicEsophageal Cancer Research and Treatment
Canadian institutionsWestern University
Fundersnot available
KeywordsMedicineAdenocarcinomaMetastasisRenal cell carcinomaEsophageal cancerEsophagectomyBiopsyRenal pelvisCancerPopulationCarcinomaPathologyRadiologyOncologyInternal medicineKidney

Abstract

fetched live from OpenAlex

Esophageal cancer, consisting primarily of squamous cell carcinoma and adenocarcinoma pathology, is a leading cause of morbidity and mortality worldwide with rates of metastasis at time of diagnosis up to 50%. Renal metastasis is rare, with most pathological diagnosis yielding squamous cell carcinoma. We present the unique case of a 78-year-old man with biopsy proven adenocarcinoma metastasis to the kidney on routine surveillance following initial esophagectomy, chemoradiation and adjuvant immunotherapy. Imaging features of the solitary renal metastasis highly mimicked a primary renal cell carcinoma. Additional unique features included renal pelvis invasion and disease recurrence despite adjuvant immunotherapy. This case underscores the role of routine surveillance in this patient population, varied radiologic appearance, and importance for pathologic diagnosis.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.289
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0010.000

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 head0.030
GPT teacher head0.325
Teacher spread0.296 · 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 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

Citations2
Published2024
Admission routes1
Has abstractyes

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