Gastrointestinal Complications after Cardiopulmonary Bypass: Sixteen Years of Experience
Bibliographic record
Abstract
BACKGROUND: Gastrointestinal (GI) complications are one of the serious complications of cardiac surgery. Although rarely seen, they cause major morbidity and mortality. The aim of the present study was to retrospectively analyze the risk factors acting on the GI complications seen after cardiac operations performed under cardiopulmonary bypass. METHOD: The present study was designed to retrospectively evaluate 13,544 patients who underwent cardiac surgery under cardiopulmonary bypass, between 1988 and 2004 in the authors' clinic. RESULTS: The overall mortality was 346 (2.55%) of 13,544 patients. GI complications developed in 128 patients (0.94%). Among those, 18 (14.1%) died because of GI complications, the most common of which was bleeding. Mesenteric ischemia had the highest case-fatality rate at 71.4%. Valve surgery, concomitant valve and coronary artery bypass grafting surgery, preoperative chronic renal dysfunction, postoperative acute renal failure, deep sternal infection, prolonged ventilation, need for intra-aortic balloon pump and ejection fraction less than 30% were found to be risk factors acting on GI complications. CONCLUSION: GI complications remain a significant concern after cardiac surgery under cardiopulmonary bypass. Higher-risk patients can be identified and treated prophylactically and in the postoperative period.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".