CAN FLUORESCENT ANGIOGRAPHY REDUCE THE LEAK RATE OF COLONIC ANASTOMOSES? (a meta-analysis)
Bibliographic record
Abstract
AIM: to evaluate of efficacy of fluorescence angiography (FA) in reducing the anastomotic leakage (AL) rate after colorectal surgery in meta-analysis. SEARCH STRATEGY: PubMed were searched up to May 2019 for studies comparing fluorescence imaging with standard approach. The primary outcome measure was colorectal anastomotic leakage (AL) rate. The Newcastle-Ottawa scale was used for quality assessment. A meta-analysis with random-effects model was performed to calculate odds ratios (ORs) from the original data. RESULTS: Two thousand four hundred and sixty-six patients from 7 non-randomized studies and 1 randomized study were included. Fluorescence imaging significantly reduced the AL rate in patients after colorectal surgery (OR 0.58; 95%CI 0.39-0.85; p=0.006) and after rectal cancer surgery (OR 0.28; 95%CI, 0.14-0.55; p=0.0002). A limitation of this meta-analysis is the inclusion of only one randomized study. CONCLUSION: Fluorescence angiography with indocyanine green is a method of preventing of leakage of colorectal anastomosis. The results of randomized clinical trials are needed to confirm the effectiveness of this technique.
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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 | 0.012 | 0.021 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.052 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".