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Record W308164218 · doi:10.1503/cjs.013014

Colonic perforation with intraluminal stents and bevacizumab in advanced colorectal cancer: retrospective case series and literature review

2015· review· en· W308164218 on OpenAlexaffvenueabout
Amal Imbulgoda, Anthony R. MacLean, J. Heine, Sébastien Drolet, Michael M. Vickers

Bibliographic record

VenueCanadian Journal of Surgery · 2015
Typereview
Languageen
FieldMedicine
TopicColorectal Cancer Surgical Treatments
Canadian institutionsUniversity of CalgaryUniversité LavalUniversity of Ottawa
Fundersnot available
KeywordsMedicineBevacizumabFOLFIRIPerforationColorectal cancerChemotherapySurgeryRetrospective cohort studyInternal medicineCancerIrinotecan

Abstract

fetched live from OpenAlex

BACKGROUND: Self-expanding metal stents (SEMS) are increasingly used in the treatment of malignant large bowel obstruction in the setting of inoperable colorectal cancer. Perforation is a well-known complication associated with these devices. The addition of the vascular endothelial growth factor inhibitor bevacizumab is suspected to increase the rate, but the extent of the increase is not known. METHODS: We retrospectively reviewed the records of patients receiving SEMS in tertiary hospitals in Calgary, Alta., between October 2001 and January 2012. RESULTS: We reviewed the records of 87 patients with inoperable colorectal cancer who received SEMS during our study period. Nine perforations occurred in total: 4 of 30 (13%) patients who received no chemotherapy, 3 of 47 (6%) who received chemotherapy but no bevacizumab, and 2 of 10 (20%) who received chemotherapy and bevacizumab. These two patients received bevacizumab with FOLFIRI after SEMS placement, and they had peritoneal disease. CONCLUSION: Our case series and other studies suggest that bevacizumab may increase the risk of colonic perforation in the setting of SEMS. Caution should be used when combining these therapies.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.784
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.000
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)0.0000.000

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 head0.040
GPT teacher head0.321
Teacher spread0.281 · 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

Citations53
Published2015
Admission routes3
Has abstractyes

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