Best evidence summary for prevention and management of enteral feeding intolerance in critically ill patients
Bibliographic record
Abstract
AIM: To evaluate and summarize the evidence for prevention and management of enteral feeding intolerance in critically ill patients and provide reference for clinical practice. DESIGN: This study was an evidence summary followed by the evidence summary reporting standard of Fudan University Center for Evidence-based Nursing. METHODS: Current literatures were systematically searched for the best evidence for prevention and management of enteral feeding intolerance in critically ill patients. Literature types included clinical guidelines, best practice information sheets, expert consensuses, systematic reviews, evidence summaries and cohort studies. DATA SOURCES: UpToDate, BMJ Best Practice, Joanna Briggs Institute, Guidelines International Network, National Institute for Health and Care Excellence, Registered Nurses Association of Ontario, Scottish Intercollegiate Guidelines Network, the Cochrane Library, Embase, PubMed, Sinomed, Web of Science, Yi Maitong Guidelines Network, DynaMed, MEDLINE, CNKI, WanFang database, Chinese Medical Journal Full-text Database, European Society for Clinical Nutrition and Metabolism website, the American Society for Parenteral and Enteral Nutrition website were searched from January 2012 to April 2023. RESULTS: We finally identified 18 articles that had high-quality results. We summarized the 24 pieces of best evidence from these articles, covering five aspects: screening and assessment of the risk of enteral nutritional tolerance; formulation of enteral nutrition preparations; enteral nutritional feeding implementation; feeding intolerance symptom prevention and management; and multidisciplinary management. Of these pieces of evidence, 19 were 'strong' and 5 were 'weak', 7 pieces of evidence were recommended in level one and 4 pieces of evidence were recommended in level two. CONCLUSION: The following 24 pieces of evidence for prevention and management of enteral feeding intolerance in critically ill patients were finally recommended. However, as these evidences came from different countries, relevant factors such as the clinical environment should be evaluated before application. Future studies should focus on more specific symptoms of feeding intolerance and more targeted prevention design applications. IMPLICATIONS FOR THE PROFESSION AND PATIENT CARE: The clinical medical staffs are recommended to take evidence-based recommendations for the implementation of standardized enteral nutrition to improve patient outcomes and decrease gastrointestinal intolerance in critically ill patients. IMPACT: The management of enteral nutrition feeding intolerance has always been a challenge and difficulty in critically ill patients. This study summarizes 24 pieces of the best evidence for prevention and management of enteral nutrition feeding intolerance in critically ill patients. Following and implementing these 24 pieces of evidence is beneficial to the prevention and management of feeding intolerance in clinical practice. The 24 pieces of evidence include five aspects, including screening and assessment of the risk of enteral nutritional tolerance, formulation of enteral nutrition preparations, enteral nutritional feeding implementation, feeding intolerance symptom prevention and management and multidisciplinary management. These five aspects constitute a good implementation process. Screening and assessment of enteral nutritional tolerance throughout intervention are important guarantees for developing a feasible nutrition program in critically ill patients. This study will be benefit to global medical workers in the nutritional management of critically ill patients. REPORTING METHOD: This evidence summary followed the evidence summary reporting specifications of Fudan University Center for Evidence-based Nursing, which were based on the methodological process for the summary of the evidence produced by the Joanna Briggs Institute (JBI). The reporting specifications include problem establishment, literature retrieval, literature screening, literature evaluation, the summary and grading of evidence and the formation of practical suggestions. This study was based on the evidence summary reporting specifications of the Fudan University Center for the Evidence-based Nursing, the register name is 'Best evidence summary for prevention and management of enteral feeding intolerance in critically ill patients', the registration number is 'ES20231823'.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".