Effect of indocyanine green near-infrared light imaging technique guided lymph node dissection on short-term clinical efficacy of minimally invasive radical gastric cancer surgery: a meta-analysis
Bibliographic record
Abstract
Objective: In recent years, the utilization of indocyanine green near-infrared (ICG NIR) light imaging-guided lymph node dissection in the context of minimally invasive radical gastric cancer has emerged as a novel avenue for investigation. The objective of this study was to assess the influence of employing this technique for guiding lymph node dissection on the short-term clinical outcomes of minimally invasive radical gastric cancer surgery. Methods: The present study conducted a comprehensive search for short-term clinical outcomes, comparing the group undergoing ICG NIR light imaging-guided lymph node dissection with the control group, by thoroughly examining relevant literature from the inception to July 2023 in renowned databases such as PubMed, Embase, Web of Science, and Cochrane Library. The primary endpoints encompassed postoperative complications, including abdominal infection, abdominal bleeding, pneumonia, anastomotic fistula, and overall incidence of complications (defined as any morbidity categorized as Clavien-Dindo class I or higher within 30 days post-surgery or during hospitalization). Additionally, secondary outcome measures consisted of the time interval until the initiation of postoperative gas and food intake, as well as various other parameters, namely postoperative hospital stay, operative time, intraoperative blood loss, total number of harvested lymph nodes, and the number of harvested metastatic lymph nodes. To ensure methodological rigor, the Cochrane Collaboration Risk of Bias Tool and the Newcastle-Ottawa Scale (NOS) were employed to assess the quality of the included studies, while statistical analyses were performed using Review Manager 5.4 software and Stata, version 12.0 software. Results: A total of 19 studies including 3103 patients were ultimately included (n=1276 in the ICG group and n=1827 in the non-ICG group). In this meta-analysis, the application of ICG near-infrared light imaging in minimally invasive radical gastric cancer surgery effectively improved the occurrence of postoperative Clavien-Dindo grade II or higher complications in patients (RR=0.72, 95% CI 0.52 to 1.00) with a statistically significant P=0.05; in reducing intraoperative blood loss and shortening While reducing intraoperative blood loss and shortening postoperative hospital stay, it could ensure the thoroughness of lymph node dissection in minimally invasive radical gastric cancer surgery (MD=5.575, 95% CI 3.677-7.473) with significant effect size (Z=5.76, p<0.00001). Conclusion: The utilization of indocyanine green near-infrared light imaging technology in the context of minimally invasive radical gastric cancer surgery demonstrates notable efficacy in mitigating the occurrence of postoperative complications surpassing Clavien-Dindo grade II, while concurrently augmenting both the overall quantity of lymph node dissections and the identification of positive lymph nodes, all the while ensuring the preservation of surgical safety. Furthermore, the implementation of this technique proves particularly advantageous in the realm of robotic-assisted radical gastric cancer surgery, thus bearing significance for enhancing the short-term prognostic outcomes of patients.
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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 | 0.015 | 0.028 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.051 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".