Impact of general or regional anaesthesia on recurrence of colorectal cancer after surgery: Systematic review
Bibliographic record
Abstract
Background and Aims: Studies have suggested that anaesthetic agents have modulatory effects on the immune system, leading to cancer recurrence. The association between colorectal cancer (CRC) recurrence and anaesthesia is still unclear. Therefore, this systematic review aimed to determine the association between the recurrence of CRC after surgery and anaesthesia. Methods: A database search of PubMed, Cochrane, Embase, and Scopus was performed for articles on the recurrence of CRC after surgeries under general anaesthesia (GA) and regional anaesthesia (RA), published between January 2002 and January 2023. Qualitative and risk-of-bias assessment of retrospective studies was performed using the Newcastle-Ottawa scale (NOS). Synthesis Without Meta-analysis guidelines were used to report data synthesis. The primary outcome was cancer recurrence, and the secondary outcomes were disease-free survival (DFS) and overall survival. The standardised metric to represent data synthesis was the median hazard ratio (HR). Evidence quality was rated as per GRADE pro-GDT. Results: = 0.20). The median HR for cancer recurrence was 0.895. DFS was not statistically significant with GA or RA, with a median HR of 1.06. Conclusion: No conclusive association was found between regional anaesthesia and colorectal cancer recurrence. However, due to a lack of studies reporting cancer recurrence and less data for comparison and different intervention groups, a conclusive association cannot be made.
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 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.008 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".