Protocol for the development of enhanced recovery after surgery (ERAS) recommendations for individuals undergoing surgery for degenerative cervical myelopathy
Bibliographic record
Abstract
STUDY DESIGN: Protocol for the development of enhanced recovery after surgery (ERAS) recommendations for DCM surgery. OBJECTIVES: To develop ERAS recommendations in collaboration with the ERAS Society to optimize care for individuals having surgery for degenerative cervical myelopathy (DCM)-the most common type of nontraumatic spinal cord injury. METHODS: The study protocol was developed in line with the AGREE II checklist for clinical practice guidelines and the ERAS Society standards for guideline development. A multidisciplinary international guideline development group (GDG) including a representative from the ERAS society, clinical experts in the surgical care of people with DCM, and people with lived experience of having surgery for DCM has been established. The recommendations will follow the GRADE methodology and will therefore include the following steps. 1) Framing the health care questions. 2) Selecting and rating the importance of outcomes for each ERAS candidate interventiont. 3) Summarizing the evidence for each ERAS candidate intervention. 4) Judging the quality of evidence for each ERAS candidate intervention. 5) Judging the strength of the recommendations for each ERAS candidate intervention. 6) Developing recommendations statements for the included ERAS interventions and achieving consensus on the ERAS intervention statements to be included in the final guideline. Following the recommendation statements' development, key stakeholders will be invited to externally review the guidelines. CONCLUSION: ERAS recommendations for DCM aim to reduce the incidence and severity of adverse events, optimize patient outcomes, improve the efficiency and quality of care, and patients' experience and satisfaction with care.
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How this classification was reachedexpand
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".