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Record W4241173412 · doi:10.5489/cuaj.990

A technique using a resectoscope sheath under direct vision and nasogastric tube for difficult catheterization following TURP

2013· article· en· W4241173412 on OpenAlexvenueaboutno aff
Kenan Îsen

Bibliographic record

VenueCanadian Urological Association Journal · 2013
Typearticle
Languageen
FieldMedicine
TopicVascular anomalies and interventions
Canadian institutionsnot available
Fundersnot available
KeywordsURETEROSCOPEMedicineTube (container)SurgeryMaterials science

Abstract

fetched live from OpenAlex

We read with great interest the recent CUA guidelines on prostate biopsy methodology. 1 We note that the recommendation regarding high-grade prostatic intra-epithelial neoplasia (HGPIN) states that "in the current era of extended biopsy schemes, HGPIN is no longer considered a strict indication for repeat biopsy and patients should be followed clinically." 1 Our Canadian research group, set out to specifically address the issue of HGPIN on prostatic needle biopsy (PNB) after 2 large review articles authored by high profile urological pathologists, rendered differing conclusions regarding the significance of HGPIN on PNB. 2,3 We used a large Canadian database containing over 12 000 patients undergoing initial PNB and concluded that HGPIN, when multifocal, is a significant risk factor for prostate cancer (PCa) carrying an odds ratio (OR) of 1.38. On the repeat study, we again found the same results. Patients with multifocal HGPIN carry a significantly increased risk of detecting PCa on follow-up PNB compared to patients with benign findings on initial PNB. Our studies show that HGPIN, when multifocal, is still a significant independent risk factor for PCa, even in the current era of extended PNB protocols. While it is a sound recommendation that patients with unifocal HGPIN be followed clinically with PSA and DRE, it is our recommendation and practice that patients with multifocal HGPIN should undergo a repeat biopsy within 1 year even in the absence of PSA or DRE changes.

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)0.001
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 score0.128
Threshold uncertainty score0.332

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.015
GPT teacher head0.263
Teacher spread0.248 · 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

Citations0
Published2013
Admission routes2
Has abstractyes

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