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Record W2399215081

Optimal port placement during laparoscopic radical prostatectomy.

2012· article· en· W2399215081 on OpenAlexaff
Ashis Chawla, Adnan Qureshi, Aziz Alamri, Edward D. Matsumoto

Bibliographic record

VenuePubMed · 2012
Typearticle
Languageen
FieldMedicine
TopicMinimally Invasive Surgical Techniques
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMedicineLaparoscopic radical prostatectomyPort (circuit theory)SurgeryProstatectomyBlood lossUmbilicus (mollusc)Prostate cancerInternal medicine
DOInot available

Abstract

fetched live from OpenAlex

INTRODUCTION: Placement of anterior abdominal wall trocars during laparoscopic radical prostatectomy (LRP) carries the risk of inadvertent injury to the inferior epigastric artery (IEA) and crossover confliction between midline and lateral ports. We described and evaluated a new measured port placement approach. MATERIALS AND METHODS: The intervention group included patients who underwent LRP with a specifically measured five port approach. The medial 10 mm ports were placed 5 cm from the patient's midline at a level mid-way between the anterior superior iliac spine (ASIS) and the umbilicus. The control group had five ports placed at the surgeon's discretion. We prospectively compared intraoperative blood loss, need for port repositioning, and incidence of adverse surgical events. RESULTS: In the interventional cohort patients (n = 112) the course of the IEA was found to be lateral to the medial 10 mm port in all cases. There were no adverse surgical outcomes in this group. In the control group patients (n = 97), three demonstrated IEA injuries (p <0.01) and three required port repositioning (p < 0.01). The mean blood loss reported between groups was not significant (p = 0.70). CONCLUSION: Our specifically measured port placement approach predictably allowed for the placement of the trocar medial to the IEA. This minimized the risk of injury to the IEA, allowed for adequate instrument manipulation and minimized the need to reposition ports.

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)0.000
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 score0.112
Threshold uncertainty score0.551

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.029
GPT teacher head0.269
Teacher spread0.239 · 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

Citations3
Published2012
Admission routes1
Has abstractyes

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