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Record W4387409004 · doi:10.1186/s13017-023-00519-2

Enhanced perioperative care in emergency general surgery: the WSES position paper

2023· review· en· W4387409004 on OpenAlexaff
Marco Ceresoli, Marco Braga, Nicola Zanini, Fikri M. Abu‐Zidan, Dario Parini, Thomas Länger, Massimo Sartelli, Dimitrios Damaskos, Walter L. Biffl, Francesco Amico, Luca Ansaloni, Zsolt J. Balogh, Luigi Bonavina, Ian Civil, Enrico Cicuttin, Mircéa Chirica, Yunfeng Cui, Belinda De Simone, Isidoro Di Carlo, Andreas Fette, Giuseppe Foti, Michele Fogliata, Gustavo Pereira Fraga, Paola Fugazzola, Joseph M. Galante, Solomon Gurmu Beka, Andreas Hecker, Johannes Jeekel, Andrew W. Kirkpatrick, Kaoru Koike, Ari Leppäniemi, İngo Marzi, Ernest E. Moore, Edoardo Picetti, Emmanouil Pikoulis, Michele Pisano, Mauro Podda, Boris Sakakushev, Vishal G. Shelat, Edward Tan, Giovanni Domenico Tebala, George C. Velmahos, Dieter Weber, Vanni Agnoletti, Yoram Kluger, Gian Luca Baiocchi, Fausto Catena, Federico Coccolini

Bibliographic record

VenueWorld Journal of Emergency Surgery · 2023
Typereview
Languageen
FieldMedicine
TopicCardiac, Anesthesia and Surgical Outcomes
Canadian institutionsFoothills Medical Centre
FundersUniversità degli Studi di Milano-Bicocca
KeywordsMedicinePerioperativeEmergency surgeryProtocol (science)Elective surgeryIntensive care medicinePosition statementPerioperative medicineSurgeryGeneral surgeryAlternative medicineFamily medicine

Abstract

fetched live from OpenAlex

Enhanced perioperative care protocols become the standard of care in elective surgery with a significant improvement in patients' outcome. The key element of the enhanced perioperative care protocol is the multimodal and interdisciplinary approach targeted to the patient, focused on a holistic approach to reduce surgical stress and improve perioperative recovery. Enhanced perioperative care in emergency general surgery is still a debated topic with little evidence available. The present position paper illustrates the existing evidence about perioperative care in emergency surgery patients with a focus on each perioperative intervention in the preoperative, intraoperative and postoperative phase. For each item was proposed and approved a statement by the WSES collaborative group.

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)0.005
metaresearch head score (Gemma)0.006
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 score0.005
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0030.002
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0040.001

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 head0.064
GPT teacher head0.361
Teacher spread0.297 · 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

Citations27
Published2023
Admission routes1
Has abstractyes

Explore more

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