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Record W2963971165 · doi:10.1016/j.ijscr.2019.07.014

Massively distended, necrotic and hemorrhagic gallbladder in a long-term octreotide-treated patient with added everolimus

2019· article· en· W2963971165 on OpenAlexaff
Éric Bergeron, Michaël Bensoussan

Bibliographic record

VenueInternational Journal of Surgery Case Reports · 2019
Typearticle
Languageen
FieldMedicine
TopicNeuroendocrine Tumor Research Advances
Canadian institutionsHôpital Charles-Le Moyne
Fundersnot available
KeywordsMedicineOctreotideEverolimusGallstonesSomatostatinCholecystitisPasireotideGastroenterologyCholecystectomyInternal medicineGallbladderPopulationSurgeryHormoneAcromegaly

Abstract

fetched live from OpenAlex

INTRODUCTION: Long-term treatment with somatostatin analogs, such as octreotide, is well known to promote gallstones formation. Immunosuppressive therapy in renal transplantation is also associated with increased occurrence of gallstones. But acute cholecystitis develops only in a few cholelithiasis patients. However, it is not known whether long-term somatostatin analog therapy and immunosuppressants aggravate the severity of disease if the patient develops cholecystitis. CASE PRESENTATION: We present a case of severe cholecystitis in a patient with metastatic carcinoid cancer on octreotide long-acting release therapy for seven years with newly added immunosuppressant, everolimus. DISCUSSION: Cholelithiasis as well as cholecystitis develop more often in patients on somatostatin analogs and immunosuppressants than in general population. However, morbidity remains negligible. CONCLUSION: No conclusion can be drawn on the contribution of somatostatin analogs and immunosuppressant in the occurrence of severe cholecystitis. Prophylactic cholecystectomy is not indicated in patients with this medication.

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 score0.004
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0020.002
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0040.003
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 head0.016
GPT teacher head0.286
Teacher spread0.270 · 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

Citations3
Published2019
Admission routes1
Has abstractyes

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Same venueInternational Journal of Surgery Case ReportsSame topicNeuroendocrine Tumor Research AdvancesFrench-language works237,207