Colorectal anastomotic leakage: a narrative review of definitions, grading systems, and consequences of leaks
Bibliographic record
Abstract
Background: Anastomotic leaks (ALs) are a significant and feared postoperative complication, with incidence of up to 30% despite advances in surgical techniques. With implications such as additional interventions, prolonged hospital stays, and hospital readmission, ALs have important impacts at the level of individual patients and healthcare providers, as well as healthcare systems as a whole. Challenges in developing unified definitions and grading systems for leaks have proved problematic, despite acknowledgement that colorectal AL is a critical issue in intestinal surgery with serious consequences. The aim of this study was to construct a narrative review of literature surrounding definitions and grading systems for ALs, and consequences of this postoperative complication. Methods: A literature review was conducted by examining databases including PubMed, Web of Science, OVID Embase, Google Scholar, and Cochrane library databases. Searches were performed with the following keywords: anastomosis, anastomotic leak, colorectal, surgery, grading system, complications, risk factors, and consequences. Publications that were retrieved underwent further assessment to ensure other relevant publications were identified and included. Results: A universally accepted definition and grading system for ALs continues to be lacking, leading to variability in reported incidence in the literature. Additional factors add to variability in estimates, including differences in the anastomotic site and institutional/individual differences in operative technique. Various groups have worked to publish guidelines for defining and grading AL, with the International Study Group of Rectal Cancer (ISGRC/ISREC) definition the current most recommended universal definition for colorectal AL. The burden of AL on patients, healthcare providers, and hospitals is well documented in evidence from leak consequences, such as increased morbidity and mortality, higher reoperation rates, and increased readmission rates, among others. Conclusions: Colorectal AL remains a significant challenge in intestinal surgery, despite medical advancements. Understanding the progress made in defining and grading leaks, as well as the range of negative outcomes that arise from AL, is crucial in improving patient care, reduce surgical mortality, and drive further advancements in earlier detection and treatment of AL.
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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 | 0.006 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.013 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".