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Record W1577818814 · doi:10.24871/1322012%p

Management of Nutrition in Gastric Emptying Preparation Before Medical Procedures

2012· article· en· W1577818814 on OpenAlexaboutno aff
Stella Evangeline Bela, Ari Fahrial Syam, Luciana Budiati Sutanto

Bibliographic record

VenueThe Indonesian Journal of Gastroenterology Hepatology and Digestive Endoscopy · 2012
Typearticle
Languageen
FieldMedicine
TopicEnhanced Recovery After Surgery
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineGastric emptyingParenteral nutritionGuidelineAnesthesiologyClinical nutritionPreoperative fastingIntubationGeneral surgeryPediatric surgeryElective surgeryGastrointestinal functionIntensive care medicineSurgeryStomachAnesthesiaInternal medicine

Abstract

fetched live from OpenAlex

Patient preparation before medical procedures, for example in elective surgery, abdominal ultrasonograhy (USG), endoscopy, intubation, etc., is by emptying the stomach. Attempt in emptying stomach is by fasting since the night before medical procedure with the intention to decrease the risk of aspiration. Management of nutrition guidelines in preparation of medical procedures currently refers to pre- surgery fasting which is recommended by American Society of Anaesthesiologist (ASA) and the Canadian Anaesthetists Society (CAS). In Indonesia, pre-surgery fasting guideline is suggested by Indonesia Society of Anesthesiology and Intensive Care. However, in various unit of service, fasting the patient since the night before is still performed. Development of nutrition management in medical procedures has experienced many changes, such as surgery which is aimed to restore organ normal function and to accelerate the healing of patients. Various studies on nutrition are developed in conjunction with the programs development to optimize pre-surgery preparation. Keywords: nutrition management, pre-surgery nutrition, aspiration

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)0.001
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 score0.008
Threshold uncertainty score0.388

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.010
GPT teacher head0.281
Teacher spread0.271 · 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

Citations0
Published2012
Admission routes1
Has abstractyes

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