Effect of a Preoperative Intervention on Preoperative and Postoperative Outcomes in Low-Risk Patients Awaiting Elective Coronary Artery Bypass Graft Surgery
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Bibliographic record
Abstract
BACKGROUND: In publicly funded health care systems, a waiting period for such services as coronary artery bypass graft surgery (CABG) is common. The possibility of using the waiting period to improve patient outcomes should be investigated. OBJECTIVE: To examine the effect of a multidimensional preoperative intervention on presurgery and postsurgery outcomes in low-risk patients awaiting elective CABG. DESIGN: Randomized, controlled trial. SETTING: A regional cardiovascular surgery center in a tertiary care hospital, southwestern Ontario, Canada. PATIENTS: 249 patients on a waiting list for elective CABG whose surgeries were scheduled for a minimum of 10 weeks from the time of study recruitment. INTERVENTION: During the waiting period, the treatment group received exercise training twice per week, education and reinforcement, and monthly nurse-initiated telephone calls. After surgery, participation in a cardiac rehabilitation program was offered to all patients. MEASUREMENTS: Postoperative length of stay was the primary outcome. Secondary outcomes were exercise performance, general health-related quality of life, social support, anxiety, and utilization of health care services. RESULTS: Length of stay differed significantly between groups. Patients who received the preoperative intervention spent 1 less day [95% CI, 0.0 to 1.0 day] in the hospital overall (P = 0.002) and less time in the intensive care unit (median, 2.1 hours [CI, -1.2 to 16 hours]; P = 0.001). During the waiting period, patients in the intervention group had a better quality of life than controls. Improved quality of life continued up to 6 months after surgery. Mortality rates did not differ. CONCLUSION: The waiting period for elective procedures, such as CABG, may be used to enhance in-hospital and early-phase recovery, improving patients' functional abilities and quality of life while reducing their hospital stay.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| 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 it