Improved Maximal Workload and Systolic Blood Pressure After Cardiac Rehabilitation Following Thoracic Aortic Repair
Bibliographic record
Abstract
PURPOSE: It is of clinical importance to gain more knowledge about the risks and benefits of exercise in patients recovering from thoracic aortic repair. Therefore, the aim of this review was to perform a meta-analysis on changes in cardiorespiratory fitness, blood pressure, and the incidence of adverse events during cardiac rehabilitation (CR) in patients recovering from thoracic aortic repair. REVIEW METHODS: We performed a systematic review and random-effects meta-analysis of outcomes before versus after outpatient CR in patients recovering from thoracic aortic repair. The study protocol was registered (PROSPERO CRD42022301204) and published. MEDLINE, EMBASE, and CINAHL were systematically searched for eligible studies. Overall certainty of evidence was scored with Grading of Recommendations Assessment, Development, and Evaluation (GRADE). SUMMARY: We included five studies with data from in total 241 patients. Data from one study could not be used in our meta-analysis because they were provided in a different unit of measure. Four studies with data of 146 patients were included in the meta-analysis. The mean maximal workload increased with 28.7 W (95% CI: 21.8-35.6 W, n = 146, low certainty of evidence). The mean systolic blood pressure during exercise testing increased with 25.4 mm Hg (95% CI: 16.6-34.3, n = 133, low certainty of evidence). No exercise-induced adverse events were reported. These outcomes indicate that CR seems beneficial and safe to improve exercise tolerance in patients recovering from thoracic aortic repair, although outcomes were based on data from a small, heterogeneous group of patients.
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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 | 0.006 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.017 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".