A comparative analysis of open heart surgery and minimally invasive cardiac surgery in exercise-based cardiac rehabilitation
Bibliographic record
Abstract
BACKGROUND: Historically, the majority of patients admitted to inpatient exercise-based cardiac rehabilitation (EBCR) have undergone open heart surgery (OHS). However, with advances in minimally invasive cardiac surgery (MICS), these patient groups are also increasingly referred for inpatient EBCR. Herein, we aimed to compare the progress of these groups during rehabilitation. METHODS: In this prospective, nonrandomized study, 403 inpatient EBCR patients were recruited from December 2022 until September 2023 and stratified into two groups: OHS, and MICS. Participants completed a 3-4-week certified EBCR program. The primary endpoint was defined as a change in the 6-minute walk test (6MWT). Moreover, a comprehensive panel of quality-of-life (QoL) assessments were performed at admission and discharge. RESULTS: At baseline, patients with OHS were older (66 years [IQR 59 - 72]), more often male (83%), and underwent emergency/urgent procedures more often (20%) than patients with MICS. Furthermore, patients with MICS showed a better 6MWT at admission (426 meters [IQR 336 - 483]) compared to patients with OHS (381 meters [IQR 299 - 453]). While all patients were able to increase the distance in the 6MWT, regression analyses in fully adjusted models showed no difference in improvements between the two groups (β -5, 95% CI, -26 - 14, p = 0.58). Moreover, during EBCR, we observed significant improvements in all QoL measures in all groups. CONCLUSIONS: In this study, improvements in fitness, as assessed by the 6WMT were observed in all groups. Furthermore, multiple QoL measures improved equally across all groups. These encouraging results emphasize the importance of EBCR.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".