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Record W2908466022 · doi:10.1186/s12913-018-3824-0

Beyond surgery: clinical and economic impact of Enhanced Recovery After Surgery programs

2018· article· en· W2908466022 on OpenAlexaff
Gaëtan‐Romain Joliat, Olle Ljungqvist, Tracy Wasylak, Oliver Peters, Nicolas Demartines

Bibliographic record

VenueBMC Health Services Research · 2018
Typearticle
Languageen
FieldMedicine
TopicEnhanced Recovery After Surgery
Canadian institutionsAlberta HealthAlberta Health Services
Fundersnot available
KeywordsMedicineMultidisciplinary approachHealth administrationHealth informaticsNursing researchAbdominal surgeryPerioperativeGeneral surgeryIntensive care medicineSurgeryPublic healthNursing

Abstract

fetched live from OpenAlex

BACKGROUND: Enhanced Recovery After Surgery (ERAS) is a perioperative management based on multimodality and multidisciplinary work. ERAS has been shown to have important clinical and economic benefits, but its spread remains slow worldwide. DISCUSSION: This manuscript reviews the overall program benefits and focuses on important aspects for implementation well beyond surgery. Implementation of ERAS pathways improves clinical outcomes and induces substantial economic gains. ERAS is the current surgical revolution.

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)0.008
metaresearch head score (Gemma)0.046
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.046
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0170.001

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 head0.079
GPT teacher head0.454
Teacher spread0.375 · 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

Citations75
Published2018
Admission routes1
Has abstractyes

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