Preoperative Risk Factors for Short-Term Postoperative Mortality of Acute Mesenteric Ischemia after Laparotomy: A Systematic Review and Meta-Analysis
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVE: Our objective was to comprehensively present the evidence of preoperative risk factors for short-term postoperative mortality of acute mesenteric ischemia after laparotomy. METHODS: PubMed, Embase, and Google Scholar were searched from January 2000 to January 2020. Studies evaluating the postoperative risk factors for short-term postoperative mortality of acute mesenteric ischemia after laparotomy were included. The outcome extracted were patients' demographics, medical history, and preoperative laboratory tests. RESULTS: Twenty studies (5011 patients) met the inclusion criteria. Studies were of high quality, with a median Newcastle-Ottawa Scale Score of 7. Summary short-term postoperative mortality was 44.38% (range, 18.80%-67.80%). Across included studies, 49 potential risk factors were examined, at least two studies. Meta-analysis of predictors based on more than three studies identified the following preoperative risk factors for higher short-term postoperative mortality risk: old age (odds ratio [OR], 1.90, 95% confidence interval [CI], 1.57-2.30), arterial occlusive mesenteric ischemia versus mesenteric venous thrombosis (OR, 2.45, 95% CI 1.12-5.33), heart failure (OR 1.33, 95% CI 1.03-1.72), renal disorders (OR 1.61, 95% CI 1.24-2.07), and peripheral vascular disease (OR 1.38, 95% CI 1.00-1.91). Nonsurvivors were older (standardized mean difference [SMD], 0.32, 95% CI 0.24-0.40), had higher creatinine levels (SMD 0.50, 95% CI 0.25-0.75), and had lower platelet counts (SMD -0.32, 95% CI -0.50 to -0.14). CONCLUSION: The short-term postoperative mortality of acute mesenteric ischemia who underwent laparotomy is still high. A better understanding of these risk factors may help in the early identification of high-risk patients, optimization of surgical procedure, and improvement of perioperative management.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.008 | 0.004 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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 it