Role of dietitians in optimizing medical nutrition therapy in cardiac surgery patients: A secondary analysis of an international multicenter observational study
Bibliographic record
Abstract
BACKGROUND: Better understanding the impact of dietetic services on nutrition practices seems required as it may represent an opportunity for optimization in post-cardiac surgery patients. The present study aims to evaluate and compare nutrition practices and clinical outcomes in post-cardiac surgery intensive care unit (ICU) patients with and without dietetic services. METHODS: This is a secondary analysis of a multinational prospective observational study in patients (n = 237) with >72 h of post-cardiac surgical ICU stay with and without dietetic services describing nutrition practices and outcomes up to 12 days after ICU admission. RESULTS: Dietetic services were available in 61.5% (8 of 13) ICUs (1.0 ± 0.5 full-time equivalents/10 beds). Enteral nutrition was initiated <48 h from ICU admission in 49.6% and 59.1% of patients at sites with vs without dietetic services, respectively. Parenteral nutrition was started within 118.3 ± 56.5 and 131.5 ± 69.2 h at sites with vs without dietetic services, respectively. Energy target (23.7 ± 4.8 vs 24.6 ± 4.8 kcal/kg body weight/day) and actual supply (10.5 ± 6.7 vs 10.3 ± 6.2 kcal/kg body weight/day) did not differ between the groups. Protein targets (1.4 ± 0.4 vs 1.1 ± 1.3 g/kg body weight/day) and actual protein provision (0.6 ± 0.4 vs 0.4 ± 0.3 g/kg body weight/day) were higher in patients at sites with vs without dietetic services. CONCLUSION: Improvements in medical nutrition therapy practices in patients after cardiac surgery are needed in ICUs with and without dietetic services. Appropriately staffed dietetic services as essential members of the medical care team may be crucial to transfer knowledge on adequate medical nutrition therapy strategies into practice.
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 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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".