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Joint consensus on abdominal robotic surgery and anesthesia from a task force of the SIAARTI and SIC

2018· review· en· W2894750371 on OpenAlexaff
Antonio Corcione, Pierluigi Angelini, Lapo Bencini, Elisabetta Bertellini, Felice Borghi, Claudio Buccelli, G Coletta, Clelia Esposito, Vincenzo Graziano, Fabio Guarracino, Domenico Marchi, P. Misitano, A Mori, Mariano Paternoster, Vincenzo Pennestrì, Vittorio Perrone, Luigi Pugliese, Stefano Romagnoli, Luigia Scudeller, Francesco Corcione

Bibliographic record

VenueMinerva Anestesiologica · 2018
Typereview
Languageen
FieldMedicine
TopicCardiac, Anesthesia and Surgical Outcomes
Canadian institutionsUniversity Hospital Foundation
Fundersnot available
KeywordsMedicineRobotic surgeryTask forceAbdominal surgeryInvasive surgeryLaparoscopyLaparoscopic surgeryTask (project management)Expert opinionMEDLINEGeneral surgeryMedical physicsSurgeryIntensive care medicine

Abstract

fetched live from OpenAlex

Minimally invasive surgical procedures have revolutionized the world of surgery in the past decades. While laparoscopy, the first minimally invasive surgical technique to be developed, is widely used and has been addressed by several guidelines and recommendations, the implementation of robotic-assisted surgery is still hindered by the lack of consensus documents that support healthcare professionals in the management of this novel surgical procedure. Here we summarize the available evidence and provide expert opinion aimed at improving the implementation and resolution of issues derived from robotic abdominal surgery procedures. A joint task force of Italian surgeons, anesthesiologists and clinical epidemiologists reviewed the available evidence on robotic abdominal surgery. Recommendations were graded according to the strength of evidence. Statements and recommendations are provided for general issues regarding robotic abdominal surgery, operating theatre organization, preoperative patient assessment and preparation, intraoperative management, and postoperative procedures and discharge. The consensus document provides evidence-based recommendations and expert statements aimed at improving the implementation and management of robotic abdominal surgery.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Not applicablelow
gptno category
Domain: not available · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Other designhigh
models splitAgreement compares identical category sets and study designs across arms.

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)0.019
metaresearch head score (Gemma)0.035
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 score0.019
Threshold uncertainty score0.099

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.035
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.004
Bibliometrics0.0100.005
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0030.003
Research integrity0.0050.004
Insufficient payload (model declined to judge)0.0070.002

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 head0.073
GPT teacher head0.288
Teacher spread0.215 · 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

Labeled directly by 2 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designNot applicable · Other 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

Citations26
Published2018
Admission routes1
Has abstractyes

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