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Record W2297844076 · doi:10.5489/cuaj.3295

Feasibility of planned mini-laparotomy and adhesiolysis at the time of robotic-assisted radical prostatectomy in patients with prior major abdominal surgery

2016· article· en· W2297844076 on OpenAlexafffundvenue
Emad Rajih, Naif Alhathal, Abdullah M. Al‐Enizi, Assaad El‐Hakim

Bibliographic record

VenueCanadian Urological Association Journal · 2016
Typearticle
Languageen
FieldMedicine
TopicIntestinal and Peritoneal Adhesions
Canadian institutionsUniversité de MontréalHôpital du Sacré-Cœur de Montréal
FundersUniversité de MontréalTaibah University
KeywordsMedicineProstatectomyLaparotomySurgeryIleusAbdominal surgeryOpen ProstatectomyDemographicsGeneral surgeryProstateInternal medicine

Abstract

fetched live from OpenAlex

INTRODUCTION: Our aim was to report our experience on the feasibility of completing radical prostatectomy robotically after planned open adhesiolysis for prior major abdominal surgery with previous midline laparotomy scar. METHODS: We searched our prospectively collected database of robotic assisted-radical prostatectomy (RARP) performed between October 2006 and October 2012 by a single fellowship-trained surgeon to identify all patients who underwent planned initial mini-laparotomy for release of abdominal adhesions at time of RARP. Among 250 RARP patients, five patients fulfilled these criteria. RESULTS: All patients had prostatectomy completed robotically. The mean values of patients' demographics were as follows: Age 61.8 years (range 54-69), body mass index 30.7 (range 24.3-45.3), and prostate volume 41.5 ml (range 30.8-54). Mean operative time was 245 min (range 190-280) and estimated blood loss 410 ml (range 300-650). Median hospital stay was one day (range 1-7). Postoperatively, there was one prolonged ileus, which resolved spontaneously, and one myocardial infarction. CONCLUSIONS: Robotic completion of radical prostatectomy after open adhesiolysis is feasible. This approach maintains most minimally invasive advantages of RARP, despite a slightly longer hospital stay. In the best interest of patients, robotic surgeons are encouraged to finish the case robotically rather than attempting an open approach.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
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)0.0020.000

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 head0.014
GPT teacher head0.223
Teacher spread0.209 · 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 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

Citations5
Published2016
Admission routes3
Has abstractyes

Explore more

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