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Record W4387107175 · doi:10.2147/imcrj.s431377

Spontaneous Suburothelial Hemorrhage: The Crucial Role of Radiology in Preventing Unnecessary Interventions

2023· article· en· W4387107175 on OpenAlexaff
Amanuel Yegnanew Adela, Nebiyu Endrias Beshada, Adriano Basso Dias, Satheesh Krishna, Tesfaye Kebede

Bibliographic record

VenueInternational Medical Case Reports Journal · 2023
Typearticle
Languageen
FieldMedicine
TopicCase Reports on Hematomas
Canadian institutionsWomen's College HospitalUniversity of TorontoUniversity Health NetworkMount Sinai Hospital
Fundersnot available
KeywordsMedicineMalignancyRadiologyPresentation (obstetrics)Interventional radiologyAngiomyolipomaPsychological interventionLesionSurgeryPathologyInternal medicineKidney

Abstract

fetched live from OpenAlex

Spontaneous suburothelial hemorrhage (SSH), also known as Antopol Goldman lesion, is a rare condition characterized by spontaneous bleeding into the renal sinus and proximal ureter wall. This case report describes the clinical presentation, imaging findings, and management of SSH in a 20-year-old female initially suspected to have urothelial malignancy. Imaging features of SSH include pre-contrast hyperdensity and non-enhancing thickening of the pelviureteric wall, which can mimic transitional cell carcinoma (TCC) and lead to unnecessary interventions. Radiologists should maintain a high level of suspicion for SSH and be aware of its imaging characteristics to avoid misdiagnosis. Additionally, clinical data, such as bleeding dyscrasia, can aid in the imaging diagnosis. This report provides insights into the diagnosis and management of SSH while offering a comprehensive literature review on its clinical presentation and imaging features. Increased awareness of SSH will facilitate accurate diagnosis and appropriate management, avoiding unnecessary interventions for patients with this benign condition.

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)0.009
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0020.001

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 head0.023
GPT teacher head0.344
Teacher spread0.321 · 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

Citations2
Published2023
Admission routes1
Has abstractyes

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