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Record W2158212168

Current Surgical Management of Colorectal Cancer Liver Metastases: A Mini Review

2011· review· en· W2158212168 on OpenAlexvenueno aff
T. Pavlidis, Nikolaos Symeonidis, Kyriakos Psarras, Athanasios K. Sakantamis

Bibliographic record

VenueJournal of Current Surgery · 2011
Typereview
Languageen
FieldMedicine
TopicHepatocellular Carcinoma Treatment and Prognosis
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineColorectal cancerHepatectomyCancerCurative treatmentSurgeryDiseaseResectionGeneral surgeryOncologyInternal medicine
DOInot available

Abstract

fetched live from OpenAlex

C olorectal cancer is responsible for 10% of cancer related deaths and is the third most common cancer type in men and the second in women. Metastatic disease will develop in nearly 60% of patients with colorectal cancer, half of which will be located in the liver. At least 30% of the patients who underwent potentially curative primary tumor resection have liver micrometastases. A PubMed search of relevant articles published up to 2011 was performed to identify current information about colorectal liver metastases regarding diagnosis and management with emphasis to surgery. The results shows that hepatectomy is the only potentially curative option resulting in 5-year survival for one third of the patients, but only 10 - 30% of the patients are suitable for a radical procedure. Indications include ability to resect the tumor without residual disease, with removal of at least 1 cm of healthy tissue and clear margins, and the absence of extrahepatic metastatic disease. Specialized centers achieve mortality rate less than 5% and morbidity 20 - 50%. 5-year survival following hepatic resection is 25 - 40% with mean survival of 28 - 40 months. We conclude that current management of colorectal cancer liver metastases requires a multidisciplinary approach. Operative strategies and novel techniques that achieve wider excision areas with minimal blood loss make hepatectomy safe and effective.  doi:10.4021/jcs106e

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.752
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0060.005
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.329
GPT teacher head0.390
Teacher spread0.061 · 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.

Study designOther design
Domainnot available
GenreReview

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
Published2011
Admission routes1
Has abstractyes

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