Impact of an Acute Care Surgery Model with a Dedicated Daytime Operating Room on Outcomes and Timeliness of Care in Patients with Biliary Tract Disease
Bibliographic record
Abstract
BACKGROUND: Although many acute care surgery (ACS) formats exist, the model established in 2006 at our academic, level 1 trauma center includes a dedicated daytime operating room. The goal of the present study was to evaluate the effect that an ACS model with a dedicated daytime operating suite would have on outcomes and timeliness of care in patients with biliary tract disease. METHODS: A retrospective cohort study was performed on all patients with biliary tract disease admitted to the University of Alberta Hospital pre- and post-ACS. Data collected included demographic information, medical diagnoses, procedures performed, and complications. Time points included the time from admission to operation, operative time, and length of hospital stay. Pre- and post-ACS groups were compared with the Pearson Chi square test and Student's t test (α = 0.05). RESULTS: There were 72 patients pre-ACS and 172 post-ACS. The two groups had similar demographics and co-morbidities. The post-ACS group had a shorter time from admission to operation (34.1 vs 24.8 h; p < 0.05). There was a decrease in the number of patients awaiting daytime operating room availability (95.8 vs 60.7 %; p < 0.05), with most surgeries being done within a 24 h period versus patients waiting upwards of 3 days pre-ACS. CONCLUSIONS: We observed a significant decrease in preoperative time by 10 h with increased access to a readily available operating room. Having a dedicated ACS team is important, but it is equally important to have a dedicated operating room with disposable time to care for unpredictable, emergent cases to realize the full potential benefit of the ACS model.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".