Emergency Medicine Perspectives on Quality of Life Outcomes After Emergency Laparotomy: A Systematic Review
Bibliographic record
Abstract
Emergency laparotomy is a life-saving intervention for acute abdominal conditions, yet its impact on patients' long-term quality of life (QOL) remains poorly understood. This systematic review synthesizes evidence on QOL outcomes following emergency laparotomy, with a focus on emergency medicine perspectives, including recovery trajectories, influencing factors, and implications for clinical practice. A comprehensive search of PubMed/Medline, Embase, Web of Science, and Scopus was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. In total, 11 studies were included, encompassing prospective and retrospective cohorts, cross-sectional surveys, and one randomized controlled trial. The risk of bias was assessed using the Newcastle-Ottawa Scale and the Cochrane Risk of Bias tool. Narrative synthesis was performed due to heterogeneity in QOL measures. Key findings revealed significant variability in QOL recovery. Survivors of peritonitis without malignancy reported acceptable QOL, while cancer and advanced age predicted worse outcomes. Chronic pain affected 19-45% of patients, particularly after small bowel obstruction surgery, and was linked to long-term functional impairment. Laparoscopy improved QOL in elderly patients compared to laparotomy. Frailty and prolonged hospitalization were associated with declines in physical and social functioning. Patient-reported outcome measures were feasible in emergency settings but highlighted unmet needs in psychological and social recovery. Emergency laparotomy significantly impacts QOL, with recovery shaped by surgical approach, comorbidities, and postoperative pain. Standardized QOL assessment, integrated multidisciplinary care, and targeted rehabilitation are needed to optimize long-term outcomes. Future research should prioritize prospective studies with uniform QOL metrics to guide patient-centered interventions.
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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 | 0.007 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.008 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".