Summary of the Clinical Evidence for Non-Pharmacological Management of Postoperative Delirium in Adults: An Evidence Synthesis
Bibliographic record
Abstract
Sujin Yin,* Jingen Dai,* Lingling Lu Department of General Surgery, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou, 215000, People’s Republic of China*These authors contributed equally to this workCorrespondence: Lingling Lu, Department of General surgery, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, No. 26 of Daoqian Street, Suzhou District, Suzhou, 215000, People’s Republic of China, Tel +86 15262410849, Fax +86 51262362015, Email Lu_linglingyy@163.comObjective: To retrieve, evaluate, and summarise the clinical evidence for non-pharmacological interventions in adult postoperative delirium (POD), encompassing the preoperative, intraoperative, and postoperative phases.Methods: The methods included conducting searches on UpToDate Clinical Consultants, the Scottish Intercollegiate Guidelines Network, the National Institute for Health and Care Excellence, the Registered Nurses’ Association of Ontario, BMJ Best Practice, the Cochrane Library, Web of Science, PubMed, China National Knowledge Infrastructure, Wanfang, VIP, and the Chinese Biomedical Literature Service System. Clinical practice guidelines, clinical decision-making, evidence summaries, evidence synthesis, expert consensus, systematic reviews, and meta-analyses on non-pharmacological interventions for adult POD were examined, and the search period spanned between the establishment of each database and 30 October 2023.Results: A total of 17 documents were included, comprising three guidelines, one expert consensus, one clinical decision-making article, four evidence summaries, three systematic reviews, and five meta-analyses. These documents primarily focused on the following three aspects: preoperative, intraoperative, and postoperative care. In total, 30 “best evidence” instances were compiled.Conclusion: Considering the complexity and potential harm of adult POD, an accurate and timely evaluation of high-risk factors, alongside effective medical nursing strategies, is vital in its prevention and treatment. Non-pharmacological interventions remain the preferred choice for preventing and treating POD. Medical institutions should establish standardised processes for non-pharmacological intervention in adult POD, based on evidence-based medicine, to enhance the level of clinical care in this field.Keywords: adult postoperative delirium, non-pharmacological intervention, evidence-based nursing, perioperative care, evidence-based medicine
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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 | 0.026 | 0.103 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.013 | 0.014 |
| Bibliometrics | 0.015 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".