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Record W2765862113 · doi:10.5489/cuaj.4471

Preoperative nutritional factors and outcomes after radical cystectomy: A narrative review

2017· review· en· W2765862113 on OpenAlexafffundvenue
Janie Allaire, Tal Ben‐Zvi, Benoı̂t Lamarche, Karine Robitaille, Yves Fradet, Louis Lacombe, Vincent Fradet

Bibliographic record

VenueCanadian Urological Association Journal · 2017
Typereview
Languageen
FieldMedicine
TopicBladder and Urothelial Cancer Treatments
Canadian institutionsUniversité LavalHôtel-Dieu de Québec
FundersCanadian Institutes of Health ResearchSanofiAstraZenecaPfizer
KeywordsCystectomyMedicineContext (archaeology)Intensive care medicineNarrative reviewProspective cohort studyAdverse effectIntervention (counseling)SurgeryBladder cancerInternal medicineCancer

Abstract

fetched live from OpenAlex

Only a few nutritional factors have been identified to predict the risk of developing complications after radical cystectomy (RC). This narrative review delineates the current known effects of preoperative nutritional status factors in this context. The report highlights the heterogeneity between study methods and results. We determined that low albuminemia values increase mortality risk and overall complications. In addition, obesity tends to increase the risk of developing venous thromboembolism and adverse events. Additional prospective studies, using standardized methods to both define and report complications, should be conducted to strengthen the connections between preoperative nutritional status factors and post-RC complications. Furthermore, intervention studies testing the impact of strategies to improve nutritional status on the risk of complications after RC are also needed.

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)0.001
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0030.004
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.049
GPT teacher head0.345
Teacher spread0.296 · 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 designNot applicable
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

Citations6
Published2017
Admission routes3
Has abstractyes

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