Evidence summary for the management of sleep disorders after malignant tumor surgery
Bibliographic record
Abstract
Introduction: This study aimed to extract, evaluate, and summarize the evidence related to the management of sleep disorders after malignant tumor surgery, providing a reference for evidence-based clinical practice. Methods: A systematic and hierarchical search strategy was used to identify relevant evidence from authoritative databases and resources. Following the "6S" evidence pyramid model, we conducted a comprehensive review of the following databases: BMJ Best Practice, CINAHL, Cochrane Library, Clinical Trials, Embase, PubMed, UpToDate, Web of Science, Guidelines International Network, National Guideline Clearinghouse, and the National Guidelines Database. Additionally, key institutional websites and specialized databases were consulted, such as the' National Institute for Health and Care Excellence in the United Kingdom, 'the Joanna Briggs Institute Centre for Evidence-Based Health Care in Australia, 'the Registered Nurses' Association of Ontario in Canada, the Scottish Intercollegiate Guidelines Network, China National Knowledge Infrastructure, China Biomedical Literature Database, Wan Fang Data, VIP Database, and Medlive. The search included clinical decisions, evidence summaries, guidelines, recommended practices, expert consensuses, systematic reviews, and randomized controlled trials. The retrieval period spanned from the inception of each database to December 31, 2024. Two researchers trained in evidence-based nursing independently evaluated the quality of the literature, extracted and synthesized the evidence, and incorporated expert recommendations as appropriate. This rigorous approach ensured comprehensive coverage of international and regional evidence-based resources, providing a solid foundation for our research. Results: Finally, we screened 12 articles with high-quality results (including 10 guidelines and 2 expert consensuses), providing 37 pieces of evidence covering four aspects: risk factors, evaluation methods, intervention measures, and effect evaluation after intervention. Discussion: The summarized evidence offers a reference for clinicians in managing sleep disorders in patients after malignant tumor surgery. However, the selection and application of evidence should be combined with specific circumstances to improve the postoperative rehabilitation of patients with malignant tumors.
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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 | 0.019 | 0.099 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.007 |
| Bibliometrics | 0.015 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 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".