Risk Factors for Prolonged Postoperative Ileus in Colorectal Surgery: A Systematic Review and Meta‐analysis
Bibliographic record
Abstract
BACKGROUND: Prolonged postoperative ileus (PPOI) represents a frequent complication following colorectal surgery, affecting approximately 10-15% of these patients. The objective of this study was to evaluate the perioperative risk factors for PPOI development in colorectal surgery. METHODS: The present systematic review and meta-analysis was conducted in accordance with the PRISMA Statement. PubMed, EMBASE, SciELO, and LILACS databases were searched, without language or time restrictions, from inception until December 2018. The keywords used were: Ileus, colon, colorectal, sigmoid, rectal, postoperative, postoperatory, surgery, risk, factors. The Newcastle-Ottawa scale and the Jadad scale were used for bias assessment, while the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach was used for quality assessment of evidence on outcome levels. RESULTS: Of the 64 studies included, 42 were evaluated in the meta-analysis, comprising 29,736 patients (51.84% males; mean age 62 years), of whom 2844 (9.56%) developed PPOI. Significant risk factors for PPOI development were: male sex (OR 1.43; 95% CI 1.25-1.63), age (MD 3.17; 95% CI 1.63-4.71), cardiac comorbidities (OR 1.54; 95% CI 1.19-2.00), previous abdominal surgery (OR 1.44; 95% CI 1.19, 1.75), laparotomy (OR 2.47; 95% CI 1.77-3.44), and ostomy creation (OR 1.44; 95% CI 1.04-1.98). Included studies evidenced a moderate heterogeneity. The quality of evidence was regarded as very low-moderate according to the GRADE approach. CONCLUSIONS: Multiple factors, including demographic characteristics, past medical history, and surgical approach, may increase the risk of developing PPOI in colorectal surgery patients. The awareness of these will allow a more accurate assessment of PPOI risk in order to take measures to decrease its impact on this population.
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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 | 0.009 | 0.022 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.036 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".