Perioperative Vasopressors Are Associated with an Increased Risk of Gastrointestinal Anastomotic Leakage
Bibliographic record
Abstract
BACKGROUND: The purpose of this study was to investigate the effect of vasopressors on gastrointestinal (GI) anastomotic leaks. Vasopressors are commonly used in surgical patients admitted to the intensive care unit (ICU) and their effects on GI anastomotic integrity are unknown. PATIENTS AND METHODS: Surgical patients admitted to the ICU in our tertiary university hospital following the creation of a GI anastomosis were studied by a retrospective chart analysis for anastomotic leaks and complications RESULTS: A total of 223 patients with 259 GI anastomoses, mostly for cancer, were admitted to the ICU immediately after surgery. Twenty-two patients developed anastomotic leaks (9.9%). The two groups (leak versus no-leak) had similar demographics, surgery type and indication, type of anastomosis, co-morbidities, cancer, steroid use, blood transfusion, drains, and epidural catheters. Vasopressor use was associated with increased anastomotic leakage (p = 0.02, OR 3.25). Multiple vasopressors and prolonged exposure caused even higher leaking rates. This effect was independent of the medical status and operative morbidity (APACHE II, POSSUM). Blood pressure preceding vasopressor use was similar in both groups. Vasopressors might have been occasionally used to treat hypovolemia. Patients with leaks had higher reoperation rates (41% versus 1%, p < 0.0001) and mortality (21% versus 4%, p = 0.002). CONCLUSIONS: Vasopressors appear to increase anastomotic leaks threefold, independent of clinical/surgical status or hypotension. Evidence-based guidelines are warranted for the optimal use of vasopressors in postoperative patients admitted to the ICU.
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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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".