Summary of best evidence for prevention of postoperative pulmonary complications after surgery for patients undergoing gastric cancer operations
Bibliographic record
Abstract
Background: Postoperative pulmonary complications in gastric cancer surgery significantly impact patient recovery and prognosis. These complications, including infections, can increase hospital stays and costs, and even lead to death. Numerous risk factors are involved, such as age, smoking history, and lung function. Although preventive measures exist, a unified and effective strategy is lacking. Therefore, researching and implementing effective prevention measures is crucial for improving patients' postoperative quality of life and survival rates. Aim: To collate and summarize the best available evidence for the prevention of pulmonary complications in patients undergoing gastric cancer surgery, thereby providing a reference for the clinical development of relevant intervention strategies. Methods: A literature search was conducted in databases including BMJ Best Practice, UpToDate, JBI, Cochrane Library, PubMed, Embase, the Ontario Nurses Registration Network, the U.S. National Clinical Practice Guidelines, and MedLine, for documents related to the prevention of pulmonary complications in gastric cancer surgery patients. The search period extended from the inception of these databases to July 25, 2024. The quality of the literature was evaluated according to the standards of the Joanna Briggs Institute (JBI) Evidence-Based Health Care Center, and evidence was extracted from the included documents. Results: A total of 27 documents were ultimately included. The extracted content encompassed three areas: preoperative assessment, risk prevention and intervention measures, totaling 31 best evidences across five categories. The findings of our study underscore the significance of comprehensive preoperative assessments, such as the ARISCAT index for pulmonary risk evaluation, and stress the importance of preoperative interventions like inspiratory muscle training, smoking cessation, and oral care in mitigating postoperative pulmonary complications (PPCs) following gastric cancer surgery. We also advocate for the adoption of protective lung ventilation strategies during surgery and continuous pulse oximetry monitoring postoperatively, along with targeted treatments for specific complications. Conclusion: The best evidence extracted for the prevention of complications in gastric cancer surgery patients serves as a basis for evidence-based practice for the prevention of pulmonary complications in this patient group. Further research topics on pulmonary complications of gastric cancer, we recommend further optimization of preoperative assessment tools, investigation into the efficacy of smoking cessation programs, comparative studies on intraoperative ventilation strategies, development of postoperative rehabilitation programs, and research into culturally and resource-sensitive interventions to broaden the global applicability of these practices.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".