Adoption of Enhanced Recovery after Surgery Protocols in Breast Reconstruction in Alberta Is High before a Formal Program Implementation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background: Enhanced recovery after surgery (ERAS) techniques have consistently demonstrated improved patient outcomes across multiple surgical specialties. We have lead international consensus guidelines on ERAS protocols for breast reconstruction and recently implemented these guidelines in Alberta. This study looks at adoption rates of ERAS pathways for breast reconstruction within Alberta, whereas also addressing barriers to ERAS implementation. Methods: A retrospective analysis of online operative reports in the Synoptec database consisting of patients undergoing alloplastic or autogenous breast reconstruction in Alberta was conducted. Primary outcomes of interest included whether ERAS protocols were utilized and what the reported barriers to ERAS utilization were. Results: Of the 372 patients undergoing breast reconstruction surgery, 215 (57%) patients were placed on an ERAS protocol. Autogenous reconstruction patients were more likely than alloplastic reconstruction patients to be placed on ERAS protocols (72% versus 53%, P = 0.002). A lack of resources was the most commonly cited reason for not adopting ERAS protocols for both autogenous and alloplastic reconstruction groups (53% and 53%). Surgeons in Southern Alberta were more likely than surgeons in Northern Alberta to utilize ERAS protocols for their alloplastic (73% versus 8%, P < 0.001) and autogenous (99% versus 4%, P < 0.001) reconstructions. Conclusions: Adoption of ERAS protocols in Alberta was strong (57% adherence) before a formal program implementation. We are encouraged that the recent official launch of ERAS protocols in breast reconstruction within the province will further enhance the uptake and care of this unique surgical population.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.000 | 0.000 |
| 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 it