Summary of the best evidence for preventing the occurrence of subcutaneous emphysema in laparoscopic surgery
Bibliographic record
Abstract
To retrieve, analyze, and extract evidence related to subcutaneous emphysema in patients undergoing laparoscopic surgery systematically, and provide evidence-based recommendations for reducing its incidence. By browsing the websites of the National Institute for Health and Clinical Excellence, the International Guideline Collaboration Network, the National Guideline Library of the United States, the Registered Nurses Association of Ontario, the Scottish Intercollegiate Guideline Network, the Clinical Practice Guidelines website of the Canadian Medical Association, UpToDate, Web of Science, PubMed, OVID, Cochrane Library, Embase, Chinese Biomedical Database, CNKI, VIP, and Wanfang Database, relevant literatures, guidelines, systematic reviews, evidence summaries, expert consensus, randomized controlled trials, etc. about subcutaneous emphysema in patients undergoing laparoscopic surgery were retrieved. All searches were limited to articles published between 1st January 2010 to 1st August 2023. 2245 articles were identified in total, 10 articles were included after exclude literature that does not meet the standards, including 3 clinical decision-making articles, 2 review papers, and 5 randomized controlled trials. Evidence summarization was conducted from 5 aspects: influencing factors, prevention, establishment and management of pneumoperitoneum, intraoperative monitoring, and intervention methods, 15 pieces of best evidences were summarized. Clinical staffs should transform and apply the evidence-based practices to decrease the incidence of subcutaneous emphysema and enhance the quality of life for patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.028 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.007 |
| Bibliometrics | 0.017 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".