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Record W2883184656 · doi:10.1002/jpen.1417

Implementation of an Enhanced Recovery After Surgery Program Can Change Nutrition Care Practice: A Multicenter Experience in Elective Colorectal Surgery

2018· article· en· W2883184656 on OpenAlex
Lisa Martin, Chelsia Gillis, Marlis Atkins, M. Gillam, Caroline E. Sheppard, Sue Buhler, Carlota Basualdo Hammond, Gregg Nelson, Leah Gramlich

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Parenteral and Enteral Nutrition · 2018
Typearticle
Languageen
FieldMedicine
TopicEnhanced Recovery After Surgery
Canadian institutionsAlberta Health ServicesUniversity of Alberta HospitalAlberta HealthUniversity of CalgaryUniversity of Alberta
FundersAlberta Innovates - Health SolutionsAmerican Society for Parenteral and Enteral Nutrition Rhoads Research Foundation
KeywordsMedicinePerioperativeColorectal surgeryOdds ratioLogistic regressionParenteral nutritionClinical nutritionOddsSurgeryEmergency medicineInternal medicineAbdominal surgery

Abstract

fetched live from OpenAlex

BACKGROUND: Enhanced recovery after surgery (ERAS) programs are multimodal evidenced-based care pathways for optimal recovery. Central to ERAS is integration of perioperative nutrition care into the overall management of the patient. This study describes changes to perioperative nutrition care after implementation of an ERAS program, and identifies factors that affect compliance to ERAS care elements and short-term postoperative outcomes. METHODS: Data were prospectively collected from patients undergoing elective colorectal surgery at 6 hospitals in Alberta, Canada, from 2013-2017. Compliance to nutrition care elements (nutrition risk screening, preoperative carbohydrate loading, early postoperative oral feeding, and mobilization) was recorded before ERAS implementation (pre-ERAS group, n = 487) and with ERAS implementation (ERAS group, n = 3536). Logistic regression identified factors that affect compliance to care elements, length of hospital stay (LOS), and postoperative complications. RESULTS: A total of 4023 patients were included. The rate of nutrition risk screening improved from 9% (pre-ERAS group) to 74% (ERAS group); 12% were at nutrition risk. Compliance increased for preoperative carbohydrate loading (4%-61%), early postoperative oral feeding (P < .001), and mobilization (P < .001). In multivariable logistic regression, nutrition risk independently predicted low overall compliance (<70%) to ERAS care elements (odds ratio [OR] 2.77; 95% CI, 2.11-3.64; P < .001) and a trend for LOS >5 days (OR 1.40; 95% CI, 1.00-1.96; P = .052). Low compliance to ERAS (<70%) predicted postoperative complications (OR 2.69; 95% CI, 2.23-3.24; P < .001). CONCLUSION: ERAS implementation positively impacted the adoption of standardized perioperative nutrition care practices. Nutrition risk screening identified patients less able to comply with postoperative nutrition care elements and who had longer LOS.

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.

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 score0.229
Threshold uncertainty score0.815

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.002
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 head0.026
GPT teacher head0.354
Teacher spread0.328 · 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