Enhanced Recovery After Surgery reduced length of stay after colorectal surgery in a small rural hospital in Ontario
Bibliographic record
Abstract
Abstract Background Enhanced Recovery After Surgery (ERAS) programs include preoperative, intraoperative and postoperative clinical pathways to improve quality of patient care while reducing length of stay and readmission. This study assessed the feasibility and outcomes of an ERAS protocol for colorectal surgery implemented over two-years in a small, resource-challenged rural hospital. Study design A prospective cohort study used retrospectively matched controls to assess the effect of ERAS on LOS in patients undergoing colorectal surgery in a small rural hospital in northern Ontario, Canada. ERAS patients were matched to two patients in the control group based on diagnosis, age and gender. Patients had open or laparoscopic colorectal surgeries, with those in the intervention group treated per ERAS protocol and given instructions on pre- and post-operative self-care. Results Most ERAS patients reported adherence to ERAS protocols prior to surgery. Approximately one quarter of patients chose not to complete the postoperative survey. Of those who completed the survey, adherence to protocol was strongest for chewing gum in the days after surgery. Most patients were sitting in a chair for their afternoon meal by the first day and most were walking down the hallway by the second day. The control and ERAS patient groups did not differ significantly (p≥0.07) in age ( years, sd=13.1), gender (52% male), nor in the Canadian Classification of Health Interventions 5-character code. The control group significantly higher (p<0.001) malignant neoplasm of colon (C18, 69% vs 35%), and significantly lower malignant neoplasm of rectum (C20, 0% vs 5%), relative to the ERAS group. The control group had an average ln-transformed LOS that was significantly longer (exponentiated as 1.7 days) than ERAS patients (t-test, p<0.001). Conclusion This study found that ERAS could be implemented in a small rural hospital and provided evidence for a reduced LOS of approximately two days.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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".