Cardiac rehabilitation wait times and relation to patient outcomes.
Bibliographic record
Abstract
BACKGROUND: Most cardiac rehabilitation (CR) associations have published guidelines recommending timely and early access. AIM: To review the effects of early CR initiation on patient outcomes, and to describe the wait times associated with positive outcomes. DESIGN: Studies were identified via a limited systematic search on key resource databases, including MEDLINE, EMBASE, and CINAHL. A focused Internet search was conducted with a concentrated grey literature search for evidence reports. POPULATION: Studies which enrolled adult cardiac patients who were eligible to participate in a CR program, based on CR guidelines, were considered. METHODS: Methodological filters limited retrieval for articles published between January 1, 2002-March 4, 2013. Two reviewers screened references which were identified by the search strategy by examining the titles and abstracts. If the abstract identified the appropriate patient group, and addressed CR wait times, the full article was obtained for inclusion consideration. Ten articles were included for review. Results were extracted from included studies, and results were synthesized narratively. RESULTS: Early access was generally shown to be safe, and to have positive effects in terms of cardiac function and patient enrollment. Positive effects on functional capacity were shown with CR initiation within 3 months from an index event. Effects on quality of life were null in the long-term. Wait times ranged from 8.5-127.0 days. Seventeen days may be the optimal wait time to balance benefit with risk. CONCLUSION: Timely access to cardiac rehab can achieve greater patient enrolment. Research on the effects of early access on heart healthy behaviors and mental health are needed. Evidence-based recommendations for wait times should be formulated by indication. CLINICAL REHABILITATION IMPACT: Delays to intake should be minimized, and wait times shortened significantly, so that patients can reap the maximum benefits from CR participation.
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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 | 0.010 | 0.088 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".