Association between Vascular Calcification and Esophagojejunal Anastomotic Complications after Total Gastrectomy for Gastric Cancer: A Propensity-Matched Study
Bibliographic record
Abstract
Esophagojejunal anastomosis (EJA) complications after total gastrectomy are related to significant morbidity and mortality. The aim of this study was to evaluate the association between arterial calcifications and EJA complications such as leak and stricture for gastric cancer. Between January 2014 and October 2019, 30 patients with EJA complications after total gastrectomy were enrolled and matched to 30 patients without complications through retrospective data review. Arterial calcification grade on preoperative computed tomography (CT) was reported in the abdominal aorta and superior mesenteric artery (SMA) as “absent”, “minor”, or “major”, and in the jejunal vascular arcade (JVA) and left inferior phrenic artery (LIPA) as “absent” or “present”. A Chi-square test was used to compare the variables between the two groups. p-Value < 0.050 was considered statistically significant. Among 30 patients, the numbers of patients with leak and stricture were 23 and seven, respectively. Aortic calcifications were not associated with EJA complications regardless of their grade (p = 0.440). Only major SMA calcifications were associated with EJA complications, as they were present in five patients (16.7%) in the complication group and absent in the non-complication group (p = 0.020). Major SMA calcifications were more related to anastomotic stricture than leak. Three (13.0%) out of 23 patients with leak and two (28.6%) out of seven with stricture had major SMA calcifications (p = 0.028). No calcifications were detected in the JVA or LIPA in any of the 60 patients. Major SMA calcifications were found to be associated with EJA complications, especially in stricture.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".