A 30-day prospective audit of all inpatient complications following acute care surgery: How well do we really perform?
Bibliographic record
Abstract
Background: Acute care surgery (ACS) and emergency general surgery (EGS) services must provide timely care and intervention for patients who have some of the most challenging needs. Patients treated by ACS services are often critically ill and have both substantial comorbidities and poor physiologic reserve. Despite the widespread implemention of ACS/EGS services across North America, the true postoperative morbidity rates remain largely unknown. Methods: In this prospective study, inpatients at 8 high-volume ACS/EGS centres in geographically diverse locations in Canada who underwent operative interventions were followed for 30 days or until they were discharged. Readmissions during the 30-day window were also captured. Preoperative, intraoperative and postoperative variables were tracked. Standard statistical methodology was employed. Results: A total of 601 ACS/EGS patients were followed for up to 30 inpatient or readmission days after their index emergent operation. Fifty-one percent of patients were female, and the median age was 51 years. They frequently had substantial medical comorbidities (42%) and morbid obesity (15%). The majority of procedures were minimally invasive (66% laparoscopic). Median length of stay was 3.3 days and the early readmission (< 30 d) rate was 6%. Six percent of patients were admitted to the critical care unit. The overall complication and mortality rates were 34% and 2%, respectively. Cholecystitis (31%), appendicitis (21%), bowel obstruction (18%), incarcerated hernia (12%), gastrointestinal hemorrhage (7%) and soft tissue infections (7%) were the most common diagnoses. The morbidity and mortality rates for open surgical procedures were 73% and 5%, respectively. Conclusion: Nontrauma ACS/EGS procedures are associated with a high postoperative morbidity rate. This study will serve as a prospective benchmark for postoperative complications among ACS/EGS patients and subsequent quality improvement across Canada.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".