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Record W2967713987 · doi:10.1080/02656736.2019.1635717

An update of peritonectomy procedures used in cytoreductive surgery for peritoneal malignancy

2019· article· en· W2967713987 on OpenAlexaff
Frédéric Mercier, Faheez Mohamed, Jean‐Baptiste Cazauran, Vahan Képénékian, Delphine Vaudoyer, Eddy Cotte, Olivier Gléhen, Guillaume Passot

Bibliographic record

VenueInternational Journal of Hyperthermia · 2019
Typearticle
Languageen
FieldMedicine
TopicIntraperitoneal and Appendiceal Malignancies
Canadian institutionsUniversité de MontréalCentre Hospitalier de l’Université de Montréal
Fundersnot available
KeywordsMedicineOmentectomySurgeryCytoreductive surgeryCancerChemotherapy

Abstract

fetched live from OpenAlex

Background: Complete cytoreduction is acknowledged to be an effective way to achieve macroscopic tumor clearance for a variety of tumors confined to the peritoneal cavity. Recent trials have shown that surgery respecting anatomical planes results in excellent outcomes and even the chance of cure for some from what was once thought to be life-limiting disease.Objective: To describe peritonectomy procedures in the current era.Method: A thorough and systematic method for cytoreductive surgery aimed at complete surgical resection of peritoneal metastases (PMs) was described.Results: The general principles of cytoreductive surgery were set out including preoperative preparation, patient positioning and incision. Strategies for assessing disease extent and planning surgical steps were outlined and established peritonectomy procedures such as Glisson’s capsulectomy, omentectomy, left and right diaphragmatic peritonectomy, lesser omentectomy, stripping of the omental bursa, and pelvic peritonectomy were described. Novel techniques such as anterior pancreatic peritonectomy, small bowel mesenteric peritonectomy and cardiophrenic lymph node dissection were explained, and illustrated with accompanying video.Conclusion: Peritoneal metastases present a challenge to the surgeon which calls for a unique skill set if optimal outcomes are to be achieved. Attempts to standardize the surgical techniques described will allow further refinement as new technological advances occur.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.216
Threshold uncertainty score0.481

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.013
GPT teacher head0.299
Teacher spread0.286 · 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 designBench or experimental
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

Citations22
Published2019
Admission routes1
Has abstractyes

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