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Record W2947225748

Ultrasound to assess gastric content and fluid volume: New kid on the block for aspiration risk assessment in critically ill patients?

2019· article· en· W2947225748 on OpenAlex

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.

Bibliographic record

VenuePure Amsterdam UMC · 2019
Typearticle
Languageen
FieldMedicine
TopicEnhanced Recovery After Surgery
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicinePoint of care ultrasoundCritically illIntensive care medicineUltrasoundRadiology
DOInot available

Abstract

fetched live from OpenAlex

Introduction: Aspiration is associated with significant morbidity and mortality. Fasting guidelines do not apply to critically ill and emergency patients. Gastric point-of-care ultrasound (PoCUS) is a promising approach to assess aspiration risk. This review discusses its feasibility, clinical implications, limitations and future perspectives. Methods: This is a narrative review. A search in PubMed and EMBASE to find relevant articles was performed. Results: Gastric PoCUS provides both qualitative and quantitative information about gastric content and fluid volume. Based on qualitative findings, the antrum is empty or contains fluids or solids. Based on quantitative findings, a fluid volume of up to 500 ml is accurately measured. Gastric PoCUS is feasible in over 90% of subjects. An algorithm for clinical application is presented. Conclusion: Gastric PoCUS is a promising tool to assess gastric content and fluid volume in critical care and emergency patients. Further research on whether the information obtained improves patient outcome is needed.

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)0.002
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 score0.031
Threshold uncertainty score0.642

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.028
GPT teacher head0.279
Teacher spread0.251 · 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