Dual-task training and cognitive performance in individuals with coronary artery disease and/or heart failure: a systematic review
Bibliographic record
Abstract
Introduction Dual-task training (DTT) emerged as a promising intervention strategy to improve cognition in individuals with cardiovascular diseases (CVDs). The aim of this study is to describe the literature on the relationship between motor-cognitive DTT and cognitive performance (CP) in individuals with coronary artery disease (CAD) and/or heart failure (HF). Method This systematic review includes intervention and observational studies that assessed motor-cognitive DTT on CP in individuals with CAD and/or HF. Searches were performed in the MEDLINE/Pubmed, Scielo, Lilacs, PEDro, and EMBASE databases. Methodological quality was assessed using the PEDro and ROBII scales for intervention studies and the Newcastle-Ottawa Scale for observational studies. The certainty of evidence was assessed using Grading of Recommendations, Assessment, Development and Evaluation (GRADE) approach. Results A total of 2,098 articles were retrieved, and 21 articles were selected for full reading. Among these, 16 were excluded according to pre-specified exclusion criteria, resulting in five studies conducted between 2018 and 2022, conducted in three countries (United States, Portugal, and Russia). The studies included 228 individuals, comprising one study with HF participants, one including women with CAD, two including individuals that underwent myocardial revascularization, and one with patients with CAD enrolled in a phase 2 of cardiac rehabilitation program. Each study used different combinations of motor and cognitive tasks, conducted sequentially (n = 2 studies) or simultaneously (n = 3 studies), with one study using virtual training. The overall certainty of evidence for CP was low according to GRADE approach. Reduction in postoperative cognitive dysfunction after myocardial revascularization was observed in two studies. Moreover, the results indicate that DTT may have a positive impact on memory, selective attention, and conflict resolution capacity. Conclusion The studies reviewed indicate motor-cognitive DTT as a potential approach to improve CP in individuals with CAD and/or HF. Systematic Review Registration www.crd.york.ac.uk/prospero/display_record.php?ID=CRD4202341516 , identifier (CRD 4202341516).
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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 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".