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Record W2909528196 · doi:10.7759/cureus.3894

Combined Mucinous and Neuroendocrine Tumours of the Appendix Managed with Surgical Cytoreduction and Oxaliplatin-based Hyperthermic Intraperitoneal Chemotherapy

2019· article· en· W2909528196 on OpenAlexaff
Roy Hajjar, Pierre Dubé, Andrew Mitchell, Lucas Sidéris

Bibliographic record

VenueCureus · 2019
Typearticle
Languageen
FieldMedicine
TopicIntraperitoneal and Appendiceal Malignancies
Canadian institutionsHôpital Maisonneuve-RosemontUniversité de Montréal
Fundersnot available
KeywordsMedicineOxaliplatinAppendixIntraperitoneal chemotherapyHyperthermic intraperitoneal chemotherapyChemotherapyCytoreductive surgeryGeneral surgeryOncologySurgeryInternal medicineCancerColorectal cancerOvarian cancer

Abstract

fetched live from OpenAlex

Appendiceal neoplasms account for 1% of appendectomy specimens. Common subtypes include mucinous cystadenoma, adenocarcinoma, and neuroendocrine tumors (NETs). The simultaneous presence of appendicular mucinous and NETs is a rare event. Depending on the tumors' morphological distribution in the affected organ, they are qualified as either "collision" or "combined" tumours. We herein present the case of a 50-year-old male who presented with acute appendicitis and who was subsequently found to have pseudomyxoma peritonei (PMP) due to a perforated combined mucinous and neuroendocrine tumours. The patient was treated by right hemicolectomy and cytoreductive surgery (CRS) with oxaliplatin-based hyperthermic intraperitoneal chemotherapy (HIPEC). He was cancer free 20 months later. Due to the limited clinical experience with this presentation, no formal recommendations exist as to its management other than those applicable to each cancer alone. The efficacity of treatment on the long-term prognosis on these combined tumors is yet to be elucidated.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.295
Threshold uncertainty score0.450

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)0.0000.000

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 head0.005
GPT teacher head0.209
Teacher spread0.204 · 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 designObservational
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

Citations7
Published2019
Admission routes1
Has abstractyes

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