Attitudes and Beliefs Related to the Canadian Critical Care Nutrition Practice Guidelines
Bibliographic record
Abstract
BACKGROUND: The objective of this study was to evaluate the attitudes of critical care practitioners toward the Canadian Critical Care Nutrition Clinical Practice Guidelines (CPGs) and compare them with actual practice. METHODS: An international Web-based survey was conducted. Respondents were asked to rate their strength of recommendation for 26 nutrition practices included in the Canadian CPGs. Attitudinal results were compared with actual practice on each recommendation. RESULTS: 514 practitioners from 27 countries completed the survey. The majority (91.4%) considered nutrition therapy to be very important for critically ill patients. There was strong endorsement for the following established practices: enteral nutrition (EN) used in preference to parenteral nutrition (PN), use of polymeric solutions and feeding protocols, and avoiding hyperglycemia. There was also strong endorsement for the following practices that are not routinely done in actual practice: EN initiated within 24 to 48 hours of admission, use of motility agents, head-of-bed elevation, use of glutamine and antioxidants, and maximizing EN before starting PN. There was diversity of opinion on the recommendations pertaining to arginine-supplemented diets, small bowel feeding, use of pharmaconutrients, intensive insulin therapy, and withholding soybean oil lipids in PN solutions and hypocaloric PN. CONCLUSIONS: Overall, attitudes toward the Canadian CPGs were positive. However, we identified some areas where there was diversity of opinion, highlighting a need for further research and education. System tools may be a useful strategy to integrate guideline recommendations into practice where there is strong endorsement but the recommendation is not happening in actual practice.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".