P.149 Enhanced Recovery after Surgery (ERAS) in Anterior Cervical Discectomy and Fusion (ACDF). A single center retrospective analysis of prospective collected data
Bibliographic record
Abstract
Background: Enhanced recovery after surgery (ERAS) concept has been implemented in many surgical specialties, with improved surgical and clinical outcomes, all while decreasing hospital cost. We have established a single center ERAS protocol for Anterior Cervical Discectomy and Fusion (ACDF) same-day surgeries. Methods: A retrospective analysis of prospective collected data of all patients undergoing one to two level ACDF surgeries at the CHUM based on a patient selection criteria’s list. Demographics, BMI, patient report outcome measures (NDI, VAS, mJOA), operative time, wake up time, time in recovery room and time till discharge were analysed. Complications were also noted. Results: When compared to our pre-ERAS group, our study showed that an ERAS protocol in select patients is not associated with any peri-operative complications, no 30-day / 90-day readmissions, nor any conversion to admission. All patients were safely discharged as planned. Operative length was similar. There was no dysphagia noted. There was improvement in all PROMs. Conclusions: ERAS protocol for ACDF same day surgeries in carefully selected patients is safe and provide same clinical outcomes. Meticulous surgical techniques, close post operative observation with a follow-up telephone call the next day are all key in assuring a safe and successful surgery and patient discharge.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".