Complications of appendectomy and cholecystectomy in acute care surgery: A systematic review and meta-analysis
Bibliographic record
Abstract
INTRODUCTION: Acute care surgery (ACS) was initiated two decades ago to address timeliness and quality in emergency general surgery. We hypothesized that ACS has improved the management of acute appendicitis and biliary disease. METHODS: A comprehensive systematic review and meta-analysis of outcome studies for emergent appendectomy and cholecystectomy from 1966 to 2017, comparing studies prior to and following ACS implementation, were performed. RESULTS: Of 1,704 studies, 27 were selected for analysis (appendicitis, 16; biliary pathology, 7; both, 4). Following ACS introduction, the complication rate was significantly reduced in both appendectomy and cholecystectomy (risk ratios, 0.70; 95% confidence interval [CI], 0.57-0.85; I = 9.2% and relative risk, 0.62; 95% CI, 0.41-0.94; I = 63.5%) respectively. There was a significant reduction in the time from arrival in emergency until admission and from admission to operation (-1.37 hours: 95% CI, -1.93 to -0.80; -2.51 hours: 95% CI, -4.44 to -0.58) in the appendectomy cohort. Time to operation was shorter in the cholecystectomy group (-6.46 hours; 95% CI, -9.54 to -3.4). Length of hospital stay was reduced in both groups (appendectomy, -0.9 day; cholecystectomy, -1.09 day). There was a reduction in overall cost in cholecystectomy group (-US $854.37; 95% CI, -1,554.1 to -154.05). No statistical significance was detected for wound infection, abscess, conversion of laparoscopy to open technique, rate of negative appendectomy, after hours, readmission, and cost. CONCLUSION: The implementation of ACS models in general surgery emergency care has significantly improved system and patient outcomes for appendicitis and biliary pathology. LEVEL OF EVIDENCE: Systematic review and meta-analysis of a retrospective study, level III.
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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 | 0.011 | 0.030 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.039 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".