Best evidence summary for nutritional management of cancer patients with chyle leaks following surgery
Bibliographic record
Abstract
Background: Chyle leaks (CL) is a significant postoperative complication following lymph node dissection in cancer patients. Persistent CK is related to a series of adverse outcomes. Nutritional management is considered an effectively strategy that treat CL. However, the existing evidence on nutritional management for this patient cohort fails to provide actionable clinical guidance. Aim: This study was aimed to establish an evidence-based framework for nutritional management, offering reliable basis for clinical nursing practice. Methods: Utilizing the "6S" mode, we conducted a systematic search of UpToDate, BMJ, Best Practice, Cochrane Library, Joanna Briggs Institute (JBI) Center for Evidence-Based Health Care Database, National Guideline Clearinghouse (NGC), Guidelines International Network (GIN), National Institute for Health and Care Excellence (NICE), Scottish Intercollegiate Guidelines Network (SIGN), Registered Nurses' Association of Ontario (RNAO), World Health Organization, Medlive, American Society for Parenteral and Enteral Nutrition (ASPEN), European Society for Clinical Nutrition and Metabolism (ESPEN), Web of Science, PubMed, Embase, CINAHL, China Biology Medicine (CBM), and China National Knowledge Infrastructure (CNKI) for all evidence on the nutritional management of postoperative coeliac leakage in cancer patients. This search included guidelines, evidence summaries, expert consensus, clinical decision-making, recommended practices, systematic evaluations or Meta-analyses, randomized controlled trials (RCTs), and class experiments. The search timeframe was from the library's establishment to June 2024. Quality assessment of the literature was completed independently by two researchers with professional evidence-based training and expert advice, and evidence was extracted and summarized for those that met the quality criteria. Results: A total of 13 articles were included in the analysis, comprising two expert consensus, one guideline, one class of experimental studies, seven systematic evaluations, and two clinical decisions. We summarized 22 pieces of evidence across five categories: nutritional screening, assessment, and monitoring, timing of nutritional therapy, methods and approaches to nutritional therapy, nutrient requirements, and dietary modification strategies. Conclusion: This study presents key evidence for nutritional management in cancer patients with CL post-surgery, emphasizing nutritional screening, assessment, timing and methods of therapy, and dietary adjustment strategies. It emphasized the necessity of thorough screening tools for the assessment of nutritional condition, and the benefits of early enteral feeding. A multidisciplinary team approach is vital for conducting personalized dietary, while sustained nutritional support, dietary fat restrictions, and medium-chain triglycerides enhance nutrient absorption. Consistent monitoring of chylous fluid output and timely dietary adjustments are crucial for improving patient outcomes and recovery. Systematic review registration: http://ebn.nursing.fudan.edu.cn/registerResources, identifier ES20244732.
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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 | 0.010 | 0.069 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.011 |
| Bibliometrics | 0.010 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.015 | 0.002 |
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".