An examination of the post-discharge recovery experience of patients who have had heart surgery.
Bibliographic record
Abstract
Background: Although resources to promote recovery following Coronary Artery Bypass Graft (CABG) and Valve Replacement (VR) surgery are provided, over a quarter of all patients are being readmitted to hospitals with post-operative complications experienced during the first 3 months of recovery. A possible reason for the high rate of readmission following heart surgery is the quality of patient engagement in the performance of self-care behaviours. In particular, patients who have had CABG and/or VR may not be fully engaged in the required self-care behaviours during their first 3 months of recovery. Research Question: This review was conducted to address the clinically relevant question: What is the post-operative recovery experience of the individual who has had CABG and/or VR?. Methods: A review of studies that examined the post-operative recovery experience of patients who had CABG and/or VR was conducted. Results: Findings suggest the type of post-operative complication identified during the first 3 months of recovery following Coronary Artery Bypass Graft (CABG) and Valve Replacement (VR) was either cognitive or cardiac in nature. As well, the number of self-care behaviours patients engage in during their hospital discharge was slightly less than the number of behaviours patients performed while in hospital. Conclusion and Relevance to Clinical Practice: As close to half of the sample reported some form of cognitive impairment within the first 3 months following surgery, it is possible that this impairment may have influenced the type and number of self-care behaviours performed. Therefore, further research is needed to determine the best time to educate patients during their recovery following hospital 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 | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".