Expanding Enhanced Recovery Protocols for Cardiac Surgery to Include the Patient Voice: a Scoping Review Protocol
Bibliographic record
Abstract
Abstract Background Cardiac surgery is becoming increasingly common in older, more vulnerable adults. A focus on timely and complete medical and functional recovery has led to the development of enhanced recovery protocols (ERPs) for a number of surgical procedures and subspecialties, including cardiac surgery (ERAS® Cardiac). An element that is often overlooked in the development and implementation of ERPs is the involvement of key stakeholder groups, including surgery patients and caregivers (e.g., family and/or friends). The aim of this study is to describe a protocol for a scoping review of cardiac patient and caregiver preferences and outcomes relevant to cardiac surgery ERPs. Methods Using Arskey and O’Malley’s six-stage framework for scoping review methodologies with adaptions from Levac et al., a scoping review of existing literature describing patient- and caregiver-identified preferences and outcomes as they relate to care received in the perioperative period of cardiac surgery will be undertaken. The search for relevant articles will be conducted using electronic databases (i.e., the Cochrane Library, Medline, PsycINFO, Scopus, and Embase), as well as through a search of the grey literature (e.g., CPG Infobase, Heart and Stroke Foundation, ProQuest Theses and Dissertations, Google Advanced and Prospero). Published and unpublished full-text articles written in English, published after the year 2000, and that relate to the research question will be included. Central to the design of this scoping review is our collaboration with two patient partners who possess lived experience as cardiac surgery patients. Discussion This review will identify strategies that can be integrated into ERPs for cardiac surgery which align with patient- and caregiver-defined values. Broadly, it is our goal to demonstrate the added value of patient engagement in research to aid in the success of system change processes.
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.
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 | 0.008 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| 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".