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SpyGlass DS -Directed Radiofrequency Ablation with Double Biliary Metal Stent Placement for Managing Recurrent Obstructive Jaundice Secondary to Castleman Disease: A Case Report of a Rare Disease (with Videos)

2020· preprint· en· W3047958198 on OpenAlexaboutno aff
Lijia Wen, Liang Guo, Kai Liu

Bibliographic record

VenuePreprints.org · 2020
Typepreprint
Languageen
FieldMedicine
TopicViral-associated cancers and disorders
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineStentJaundiceBiliary stentRadiofrequency ablationObstructive jaundiceAbdominal painRadiologyAblationSurgeryGeneral surgeryInternal medicine

Abstract

fetched live from OpenAlex

Castleman disease (CD) rarely presents with obstructive jaundice, which poses a diagnostic and therapeutic challenge to the management of the disease. A 40-year-old man was referred to our hospital for emergent management of upper abdominal pain. An abdominal mass was removed, and the postoperative pathology showed retroperitoneum CD, which was subsequently managed by adjuvant therapy of combination chemotherapy and steroids. One month later, a biliary metal stent was placed due to the presentation of obstructive jaundice. After approximately 3 months, the patient experienced another episode of obstructive jaundice, and SpyGlass DS cholangioscopy (Boston Scientific, Natick, Mass, USA) was performed via the biliary track for biopsy, which pathologically showed biliary malignancies. Radiofrequency ablation was performed with a probe (EMcision, Montreal, Canada), and another uncovered metal stent was placed within the existing metal stent. No stent occlusion occurred during a 6-month follow-up period. In conclusion, CD rarely presents with obstructive jaundice, and a combination of radiofrequency ablation with metal stent implantation under cholangioscopy can prolong the stent patency time and the survival time of patients.

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)0.001
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 score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0030.002
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 head0.064
GPT teacher head0.329
Teacher spread0.265 · 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
Published2020
Admission routes1
Has abstractyes

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Same venuePreprints.org→Same topicViral-associated cancers and disorders→French-language works237,207→