Risk factors for bowel resection among patients with incarcerated groin hernias: A meta-analysis
Bibliographic record
Abstract
BACKGROUND: Early recognition of the risk of bowel resection of patients with incarcerated groin hernia will facilitate the clinical decision making of surgeons and improve the outcomes of patients. This study aimed to quantitatively analyse the risk factors of bowel resection in incarcerated groin hernia patients. MATERIALS AND METHODS: A systematic literature search for studies on risk factors of bowel resection in incarcerated groin hernia patients was performed in the PubMed and Embase databases from inception until July 15, 2019. The Newcastle-Ottawa Scale was used to evaluate the quality of included study. Review Manager version 5.3 was used for data analysis. RESULTS: Seven articles with a total of 762 patients published between 2004 and 2017 were included. The total rate of bowel resection was 21.0% (160/762). Eight factors were significantly related to the risk of bowel resection in the pooled analysis: female sex, age, age (>65 years), femoral hernia, bowel obstruction, duration of incarceration (hours), white blood cell count, and neutrophilic leukocyte count. Patients who underwent bowel resection had a significantly increased hospitalization times and postoperative complications. CONCLUSION: The 8 risk factors mentioned above are significantly associated with bowel resection in incarcerated groin hernia patients. The results of this meta-analysis provide a strong reference for the decision making of surgeons in the treatment of incarcerated groin hernia, facilitating the timely surgery and improving the outcome of patients.
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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 | 0.008 | 0.018 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.034 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".