Epidemiological patterns, outcomes, and mortality rates of abdominal surgical emergencies in Saudi Arabia: a systematic review and meta-analysis
Bibliographic record
Abstract
Abdominal surgical emergencies (ASEs), such as appendicitis, intestinal obstruction, perforated peptic ulcers, and abdominal trauma, pose significant global health challenges, contributing to high morbidity and mortality rates. In Saudi Arabia, a comprehensive understanding of these conditions' epidemiological patterns, outcomes, and mortality rates is limited. This study systematically reviewed and analyzed data to provide insights into patient demographics, complications, and outcomes related to ASEs in Saudi Arabia following PRISMA 2020 guidelines. PubMed, Scopus and Web of Science were searched for studies published in English reporting on ASEs in Saudi Arabia. Study quality was assessed using the Newcastle-Ottawa Scale (NOS). Random-effect models were used to calculate pooled prevalence estimates for gender distribution, complications, and mortality rates. Nine studies comprising 3,005 patients were included. A male predominance was observed, with a pooled prevalence of 69% (95% CI: 54%-83%). Mortality rates ranged from 0% in pediatric populations to 22.7% in high-risk groups, with a pooled rate of 2% (95% CI: 1%-5%). Surgical site infections (SSI) were reported in six studies, with a pooled prevalence of 10% (95% CI: 3%-21%). Other complications included sepsis, anastomotic leaks, and wound infections. Laparoscopic procedures were associated with fewer complications compared to open surgeries. Study quality ranged from moderate to high. This review highlighted significant variations in the epidemiology, outcomes, and complications of abdominal surgical emergencies in Saudi Arabia. While overall mortality was low, high-risk populations experienced worse outcomes. Standardized surgical protocols and improved perioperative practices are essential to reduce complications and enhance patient outcomes.
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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 | 0.010 | 0.025 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.029 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".